Automated Comparative Auditing of NCIT Genomic Roles Using NCBI

PubMed Central

Cohen, Barry; Oren, Marc; Min, Hua; Perl, Yehoshua; Halper, Michael

2008-01-01

Biomedical research has identified many human genes and various knowledge about them. The National Cancer Institute Thesaurus (NCIT) represents such knowledge as concepts and roles (relationships). Due to the rapid advances in this field, it is to be expected that the NCIT’s Gene hierarchy will contain role errors. A comparative methodology to audit the Gene hierarchy with the use of the National Center for Biotechnology Information’s (NCBI’s) Entrez Gene database is presented. The two knowledge sources are accessed via a pair of Web crawlers to ensure up-to-date data. Our algorithms then compare the knowledge gathered from each, identify discrepancies that represent probable errors, and suggest corrective actions. The primary focus is on two kinds of gene-roles: (1) the chromosomal locations of genes, and (2) the biological processes in which genes plays a role. Regarding chromosomal locations, the discrepancies revealed are striking and systematic, suggesting a structurally common origin. In regard to the biological processes, difficulties arise because genes frequently play roles in multiple processes, and processes may have many designations (such as synonymous terms). Our algorithms make use of the roles defined in the NCIT Biological Process hierarchy to uncover many probable gene-role errors in the NCIT. These results show that automated comparative auditing is a promising technique that can identify a large number of probable errors and corrections for them in a terminological genomic knowledge repository, thus facilitating its overall maintenance. PMID:18486558

A knowledge discovery object model API for Java

PubMed Central

Zuyderduyn, Scott D; Jones, Steven JM

2003-01-01

Background Biological data resources have become heterogeneous and derive from multiple sources. This introduces challenges in the management and utilization of this data in software development. Although efforts are underway to create a standard format for the transmission and storage of biological data, this objective has yet to be fully realized. Results This work describes an application programming interface (API) that provides a framework for developing an effective biological knowledge ontology for Java-based software projects. The API provides a robust framework for the data acquisition and management needs of an ontology implementation. In addition, the API contains classes to assist in creating GUIs to represent this data visually. Conclusions The Knowledge Discovery Object Model (KDOM) API is particularly useful for medium to large applications, or for a number of smaller software projects with common characteristics or objectives. KDOM can be coupled effectively with other biologically relevant APIs and classes. Source code, libraries, documentation and examples are available at . PMID:14583100

Systems Biology Graphical Notation: Entity Relationship language Level 1 Version 2.

PubMed

Sorokin, Anatoly; Le Novère, Nicolas; Luna, Augustin; Czauderna, Tobias; Demir, Emek; Haw, Robin; Mi, Huaiyu; Moodie, Stuart; Schreiber, Falk; Villéger, Alice

2015-09-04

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Entity Relationship language (ER) represents biological entities and their interactions and relationships within a network. SBGN ER focuses on all potential relationships between entities without considering temporal aspects. The nodes (elements) describe biological entities, such as proteins and complexes. The edges (connections) provide descriptions of interactions and relationships (or influences), e.g., complex formation, stimulation and inhibition. Among all three languages of SBGN, ER is the closest to protein interaction networks in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

Development of the Neuron Assessment for Measuring Biology Students’ Use of Experimental Design Concepts and Representations

PubMed Central

Dasgupta, Annwesa P.; Anderson, Trevor R.; Pelaez, Nancy J.

2016-01-01

Researchers, instructors, and funding bodies in biology education are unanimous about the importance of developing students’ competence in experimental design. Despite this, only limited measures are available for assessing such competence development, especially in the areas of molecular and cellular biology. Also, existing assessments do not measure how well students use standard symbolism to visualize biological experiments. We propose an assessment-design process that 1) provides background knowledge and questions for developers of new “experimentation assessments,” 2) elicits practices of representing experiments with conventional symbol systems, 3) determines how well the assessment reveals expert knowledge, and 4) determines how well the instrument exposes student knowledge and difficulties. To illustrate this process, we developed the Neuron Assessment and coded responses from a scientist and four undergraduate students using the Rubric for Experimental Design and the Concept-Reasoning Mode of representation (CRM) model. Some students demonstrated sound knowledge of concepts and representations. Other students demonstrated difficulty with depicting treatment and control group data or variability in experimental outcomes. Our process, which incorporates an authentic research situation that discriminates levels of visualization and experimentation abilities, shows potential for informing assessment design in other disciplines. PMID:27146159

Systems Biology Graphical Notation: Process Description language Level 1 Version 1.3.

PubMed

Moodie, Stuart; Le Novère, Nicolas; Demir, Emek; Mi, Huaiyu; Villéger, Alice

2015-09-04

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Process Description language represents biological entities and processes between these entities within a network. SBGN PD focuses on the mechanistic description and temporal dependencies of biological interactions and transformations. The nodes (elements) are split into entity nodes describing, e.g., metabolites, proteins, genes and complexes, and process nodes describing, e.g., reactions and associations. The edges (connections) provide descriptions of relationships (or influences) between the nodes, such as consumption, production, stimulation and inhibition. Among all three languages of SBGN, PD is the closest to metabolic and regulatory pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

Comparative analysis of knowledge representation and reasoning requirements across a range of life sciences textbooks.

PubMed

Chaudhri, Vinay K; Elenius, Daniel; Goldenkranz, Andrew; Gong, Allison; Martone, Maryann E; Webb, William; Yorke-Smith, Neil

2014-01-01

Using knowledge representation for biomedical projects is now commonplace. In previous work, we represented the knowledge found in a college-level biology textbook in a fashion useful for answering questions. We showed that embedding the knowledge representation and question-answering abilities in an electronic textbook helped to engage student interest and improve learning. A natural question that arises from this success, and this paper's primary focus, is whether a similar approach is applicable across a range of life science textbooks. To answer that question, we considered four different textbooks, ranging from a below-introductory college biology text to an advanced, graduate-level neuroscience textbook. For these textbooks, we investigated the following questions: (1) To what extent is knowledge shared between the different textbooks? (2) To what extent can the same upper ontology be used to represent the knowledge found in different textbooks? (3) To what extent can the questions of interest for a range of textbooks be answered by using the same reasoning mechanisms? Our existing modeling and reasoning methods apply especially well both to a textbook that is comparable in level to the text studied in our previous work (i.e., an introductory-level text) and to a textbook at a lower level, suggesting potential for a high degree of portability. Even for the overlapping knowledge found across the textbooks, the level of detail covered in each textbook was different, which requires that the representations must be customized for each textbook. We also found that for advanced textbooks, representing models and scientific reasoning processes was particularly important. With some additional work, our representation methodology would be applicable to a range of textbooks. The requirements for knowledge representation are common across textbooks, suggesting that a shared semantic infrastructure for the life sciences is feasible. Because our representation overlaps heavily with those already being used for biomedical ontologies, this work suggests a natural pathway to include such representations as part of the life sciences curriculum at different grade levels.

Biological knowledge bases using Wikis: combining the flexibility of Wikis with the structure of databases.

PubMed

Brohée, Sylvain; Barriot, Roland; Moreau, Yves

2010-09-01

In recent years, the number of knowledge bases developed using Wiki technology has exploded. Unfortunately, next to their numerous advantages, classical Wikis present a critical limitation: the invaluable knowledge they gather is represented as free text, which hinders their computational exploitation. This is in sharp contrast with the current practice for biological databases where the data is made available in a structured way. Here, we present WikiOpener an extension for the classical MediaWiki engine that augments Wiki pages by allowing on-the-fly querying and formatting resources external to the Wiki. Those resources may provide data extracted from databases or DAS tracks, or even results returned by local or remote bioinformatics analysis tools. This also implies that structured data can be edited via dedicated forms. Hence, this generic resource combines the structure of biological databases with the flexibility of collaborative Wikis. The source code and its documentation are freely available on the MediaWiki website: http://www.mediawiki.org/wiki/Extension:WikiOpener.

StrateGene: object-oriented programming in molecular biology.

PubMed

Carhart, R E; Cash, H D; Moore, J F

1988-03-01

This paper describes some of the ways that object-oriented programming methodologies have been used to represent and manipulate biological information in a working application. When running on a Xerox 1100 series computer, StrateGene functions as a genetic engineering workstation for the management of information about cloning experiments. It represents biological molecules, enzymes, fragments, and methods as classes, subclasses, and members in a hierarchy of objects. These objects may have various attributes, which themselves can be defined and classified. The attributes and their values can be passed from the classes of objects down to the subclasses and members. The user can modify the objects and their attributes while using them. New knowledge and changes to the system can be incorporated relatively easily. The operations on the biological objects are associated with the objects themselves. This makes it easier to invoke them correctly and allows generic operations to be customized for the particular object.

The biology of cultural conflict

PubMed Central

Berns, Gregory S.; Atran, Scott

2012-01-01

Although culture is usually thought of as the collection of knowledge and traditions that are transmitted outside of biology, evidence continues to accumulate showing how biology and culture are inseparably intertwined. Cultural conflict will occur only when the beliefs and traditions of one cultural group represent a challenge to individuals of another. Such a challenge will elicit brain processes involved in cognitive decision-making, emotional activation and physiological arousal associated with the outbreak, conduct and resolution of conflict. Key targets to understand bio-cultural differences include primitive drives—how the brain responds to likes and dislikes, how it discounts the future, and how this relates to reproductive behaviour—but also higher level functions, such as how the mind represents and values the surrounding physical and social environment. Future cultural wars, while they may bear familiar labels of religion and politics, will ultimately be fought over control of our biology and our environment. PMID:22271779

The biology of cultural conflict.

PubMed

Berns, Gregory S; Atran, Scott

2012-03-05

Although culture is usually thought of as the collection of knowledge and traditions that are transmitted outside of biology, evidence continues to accumulate showing how biology and culture are inseparably intertwined. Cultural conflict will occur only when the beliefs and traditions of one cultural group represent a challenge to individuals of another. Such a challenge will elicit brain processes involved in cognitive decision-making, emotional activation and physiological arousal associated with the outbreak, conduct and resolution of conflict. Key targets to understand bio-cultural differences include primitive drives-how the brain responds to likes and dislikes, how it discounts the future, and how this relates to reproductive behaviour-but also higher level functions, such as how the mind represents and values the surrounding physical and social environment. Future cultural wars, while they may bear familiar labels of religion and politics, will ultimately be fought over control of our biology and our environment.

Data to knowledge: how to get meaning from your result.

PubMed

Berman, Helen M; Gabanyi, Margaret J; Groom, Colin R; Johnson, John E; Murshudov, Garib N; Nicholls, Robert A; Reddy, Vijay; Schwede, Torsten; Zimmerman, Matthew D; Westbrook, John; Minor, Wladek

2015-01-01

Structural and functional studies require the development of sophisticated 'Big Data' technologies and software to increase the knowledge derived and ensure reproducibility of the data. This paper presents summaries of the Structural Biology Knowledge Base, the VIPERdb Virus Structure Database, evaluation of homology modeling by the Protein Model Portal, the ProSMART tool for conformation-independent structure comparison, the LabDB 'super' laboratory information management system and the Cambridge Structural Database. These techniques and technologies represent important tools for the transformation of crystallographic data into knowledge and information, in an effort to address the problem of non-reproducibility of experimental results.

Statistics for Learning Genetics

ERIC Educational Resources Information Center

Charles, Abigail Sheena

2012-01-01

This study investigated the knowledge and skills that biology students may need to help them understand statistics/mathematics as it applies to genetics. The data are based on analyses of current representative genetics texts, practicing genetics professors' perspectives, and more directly, students' perceptions of, and performance in, doing…

Ontology of physics for biology: representing physical dependencies as a basis for biological processes.

PubMed

Cook, Daniel L; Neal, Maxwell L; Bookstein, Fred L; Gennari, John H

2013-12-02

In prior work, we presented the Ontology of Physics for Biology (OPB) as a computational ontology for use in the annotation and representations of biophysical knowledge encoded in repositories of physics-based biosimulation models. We introduced OPB:Physical entity and OPB:Physical property classes that extend available spatiotemporal representations of physical entities and processes to explicitly represent the thermodynamics and dynamics of physiological processes. Our utilitarian, long-term aim is to develop computational tools for creating and querying formalized physiological knowledge for use by multiscale "physiome" projects such as the EU's Virtual Physiological Human (VPH) and NIH's Virtual Physiological Rat (VPR). Here we describe the OPB:Physical dependency taxonomy of classes that represent of the laws of classical physics that are the "rules" by which physical properties of physical entities change during occurrences of physical processes. For example, the fluid analog of Ohm's law (as for electric currents) is used to describe how a blood flow rate depends on a blood pressure gradient. Hooke's law (as in elastic deformations of springs) is used to describe how an increase in vascular volume increases blood pressure. We classify such dependencies according to the flow, transformation, and storage of thermodynamic energy that occurs during processes governed by the dependencies. We have developed the OPB and annotation methods to represent the meaning-the biophysical semantics-of the mathematical statements of physiological analysis and the biophysical content of models and datasets. Here we describe and discuss our approach to an ontological representation of physical laws (as dependencies) and properties as encoded for the mathematical analysis of biophysical processes.

Development of the Neuron Assessment for Measuring Biology Students' Use of Experimental Design Concepts and Representations.

PubMed

Dasgupta, Annwesa P; Anderson, Trevor R; Pelaez, Nancy J

2016-01-01

Researchers, instructors, and funding bodies in biology education are unanimous about the importance of developing students' competence in experimental design. Despite this, only limited measures are available for assessing such competence development, especially in the areas of molecular and cellular biology. Also, existing assessments do not measure how well students use standard symbolism to visualize biological experiments. We propose an assessment-design process that 1) provides background knowledge and questions for developers of new "experimentation assessments," 2) elicits practices of representing experiments with conventional symbol systems, 3) determines how well the assessment reveals expert knowledge, and 4) determines how well the instrument exposes student knowledge and difficulties. To illustrate this process, we developed the Neuron Assessment and coded responses from a scientist and four undergraduate students using the Rubric for Experimental Design and the Concept-Reasoning Mode of representation (CRM) model. Some students demonstrated sound knowledge of concepts and representations. Other students demonstrated difficulty with depicting treatment and control group data or variability in experimental outcomes. Our process, which incorporates an authentic research situation that discriminates levels of visualization and experimentation abilities, shows potential for informing assessment design in other disciplines. © 2016 A. P. Dasgupta et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

The mammary gland in domestic ruminants: a systems biology perspective.

PubMed

Ferreira, Ana M; Bislev, Stine L; Bendixen, Emøke; Almeida, André M

2013-12-06

Milk and dairy products are central elements in the human diet. It is estimated that 108kg of milk per year are consumed per person worldwide. Therefore, dairy production represents a relevant fraction of the economies of many countries, being cattle, sheep, goat, water buffalo, and other ruminants the main species used worldwide. An adequate management of dairy farming cannot be achieved without the knowledge on the biological mechanisms behind lactation in ruminants. Thus, understanding the morphology, development and regulation of the mammary gland in health, disease and production is crucial. Presently, innovative and high-throughput technologies such as genomics, transcriptomics, proteomics and metabolomics allow a much broader and detailed knowledge on such issues. Additionally, the application of a systems biology approach to animal science is vastly growing, as new advances in one field of specialization or animal species lead to new lines of research in other areas or/and are expanded to other species. This article addresses how modern research approaches may help us understand long-known issues in mammary development, lactation biology and dairy production. Dairy production depends upon the knowledge of the morphology and regulation of the mammary gland and lactation. High-throughput technologies allow a much broader and detailed knowledge on the biology of the mammary gland. This paper reviews the major contributions that genomics, transcriptomics, metabolomics and proteomics approaches have provided to understand the regulation of the mammary gland in health, disease and production. In the context of mammary gland "omics"-based research, the integration of results using a Systems Biology Approach is of key importance. © 2013.

Knowledge representation and qualitative simulation of salmon redd functioning. Part I: qualitative modeling and simulation.

PubMed

Guerrin, F; Dumas, J

2001-02-01

This work aims at representing empirical knowledge of freshwater ecologists on the functioning of salmon redds (spawning areas of salmon) and its impact on mortality of early stages. For this, we use Qsim, a qualitative simulator. In this first part, we provide unfamiliar readers with the underlying qualitative differential equation (QDE) ontology of Qsim: representing quantities, qualitative variables, qualitative constraints, QDE structure. Based on a very simple example taken of the salmon redd application, we show how informal biological knowledge may be represented and simulated using an approach that was first intended to analyze qualitatively ordinary differential equations systems. A companion paper (Part II) gives the full description and simulation of the salmon redd qualitative model. This work was part of a project aimed at assessing the impact of the environment on salmon populations dynamics by the use of models of processes acting at different levels: catchment, river, and redds. Only the latter level is dealt with in this paper.

Data to knowledge: how to get meaning from your result

PubMed Central

Berman, Helen M.; Gabanyi, Margaret J.; Groom, Colin R.; Johnson, John E.; Murshudov, Garib N.; Nicholls, Robert A.; Reddy, Vijay; Schwede, Torsten; Zimmerman, Matthew D.; Westbrook, John; Minor, Wladek

2015-01-01

Structural and functional studies require the development of sophisticated ‘Big Data’ technologies and software to increase the knowledge derived and ensure reproducibility of the data. This paper presents summaries of the Structural Biology Knowledge Base, the VIPERdb Virus Structure Database, evaluation of homology modeling by the Protein Model Portal, the ProSMART tool for conformation-independent structure comparison, the LabDB ‘super’ laboratory information management system and the Cambridge Structural Database. These techniques and technologies represent important tools for the transformation of crystallographic data into knowledge and information, in an effort to address the problem of non-reproducibility of experimental results. PMID:25610627

The Gene Ontology of eukaryotic cilia and flagella.

PubMed

Roncaglia, Paola; van Dam, Teunis J P; Christie, Karen R; Nacheva, Lora; Toedt, Grischa; Huynen, Martijn A; Huntley, Rachael P; Gibson, Toby J; Lomax, Jane

2017-01-01

Recent research into ciliary structure and function provides important insights into inherited diseases termed ciliopathies and other cilia-related disorders. This wealth of knowledge needs to be translated into a computational representation to be fully exploitable by the research community. To this end, members of the Gene Ontology (GO) and SYSCILIA Consortia have worked together to improve representation of ciliary substructures and processes in GO. Members of the SYSCILIA and Gene Ontology Consortia suggested additions and changes to GO, to reflect new knowledge in the field. The project initially aimed to improve coverage of ciliary parts, and was then broadened to cilia-related biological processes. Discussions were documented in a public tracker. We engaged the broader cilia community via direct consultation and by referring to the literature. Ontology updates were implemented via ontology editing tools. So far, we have created or modified 127 GO terms representing parts and processes related to eukaryotic cilia/flagella or prokaryotic flagella. A growing number of biological pathways are known to involve cilia, and we continue to incorporate this knowledge in GO. The resulting expansion in GO allows more precise representation of experimentally derived knowledge, and SYSCILIA and GO biocurators have created 199 annotations to 50 human ciliary proteins. The revised ontology was also used to curate mouse proteins in a collaborative project. The revised GO and annotations, used in comparative 'before and after' analyses of representative ciliary datasets, improve enrichment results significantly. Our work has resulted in a broader and deeper coverage of ciliary composition and function. These improvements in ontology and protein annotation will benefit all users of GO enrichment analysis tools, as well as the ciliary research community, in areas ranging from microscopy image annotation to interpretation of high-throughput studies. We welcome feedback to further enhance the representation of cilia biology in GO.

A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2.

PubMed

Thiele, Ines; Hyduke, Daniel R; Steeb, Benjamin; Fankam, Guy; Allen, Douglas K; Bazzani, Susanna; Charusanti, Pep; Chen, Feng-Chi; Fleming, Ronan M T; Hsiung, Chao A; De Keersmaecker, Sigrid C J; Liao, Yu-Chieh; Marchal, Kathleen; Mo, Monica L; Özdemir, Emre; Raghunathan, Anu; Reed, Jennifer L; Shin, Sook-il; Sigurbjörnsdóttir, Sara; Steinmann, Jonas; Sudarsan, Suresh; Swainston, Neil; Thijs, Inge M; Zengler, Karsten; Palsson, Bernhard O; Adkins, Joshua N; Bumann, Dirk

2011-01-18

Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of this reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. Taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.

A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella Typhimurium LT2

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thiele, Ines; Hyduke, Daniel R.; Steeb, Benjamin

2011-01-01

Metabolic reconstructions (MRs) are common denominators in systems biology and represent biochemical, genetic, and genomic (BiGG) knowledge-bases for target organisms by capturing currently available information in a consistent, structured manner. Salmonella enterica subspecies I serovar Typhimurium is a human pathogen, causes various diseases and its increasing antibiotic resistance poses a public health problem. Here, we describe a community-driven effort, in which more than 20 experts in S. Typhimurium biology and systems biology collaborated to reconcile and expand the S. Typhimurium BiGG knowledge-base. The consensus MR was obtained starting from two independently developed MRs for S. Typhimurium. Key results of thismore » reconstruction jamboree include i) development and implementation of a community-based workflow for MR annotation and reconciliation; ii) incorporation of thermodynamic information; and iii) use of the consensus MR to identify potential multi-target drug therapy approaches. Finally, taken together, with the growing number of parallel MRs a structured, community-driven approach will be necessary to maximize quality while increasing adoption of MRs in experimental design and interpretation.« less

Ontology of physics for biology: representing physical dependencies as a basis for biological processes

PubMed Central

2013-01-01

Background In prior work, we presented the Ontology of Physics for Biology (OPB) as a computational ontology for use in the annotation and representations of biophysical knowledge encoded in repositories of physics-based biosimulation models. We introduced OPB:Physical entity and OPB:Physical property classes that extend available spatiotemporal representations of physical entities and processes to explicitly represent the thermodynamics and dynamics of physiological processes. Our utilitarian, long-term aim is to develop computational tools for creating and querying formalized physiological knowledge for use by multiscale “physiome” projects such as the EU’s Virtual Physiological Human (VPH) and NIH’s Virtual Physiological Rat (VPR). Results Here we describe the OPB:Physical dependency taxonomy of classes that represent of the laws of classical physics that are the “rules” by which physical properties of physical entities change during occurrences of physical processes. For example, the fluid analog of Ohm’s law (as for electric currents) is used to describe how a blood flow rate depends on a blood pressure gradient. Hooke’s law (as in elastic deformations of springs) is used to describe how an increase in vascular volume increases blood pressure. We classify such dependencies according to the flow, transformation, and storage of thermodynamic energy that occurs during processes governed by the dependencies. Conclusions We have developed the OPB and annotation methods to represent the meaning—the biophysical semantics—of the mathematical statements of physiological analysis and the biophysical content of models and datasets. Here we describe and discuss our approach to an ontological representation of physical laws (as dependencies) and properties as encoded for the mathematical analysis of biophysical processes. PMID:24295137

Prostate cancer molecular profiling: the Achilles heel for the implementation of precision medicine.

PubMed

Oliveira-Barros, Eliane Gouvêa; Nicolau-Neto, Pedro; Da Costa, Nathalia Meireles; Pinto, Luís Felipe Ribeiro; Palumbo, Antonio; Nasciutti, Luiz Eurico

2017-11-01

Cancer has been mainly treated by traditional therapeutic approaches which do not consider the human genetic diversity and present limitations, probably as a consequence of a poor knowledge of both patient's genetic background and tumor biology. Due to genome project conclusion and large-scale gene analyses emergence, the therapeutic management of several prevalent and aggressive tumors has dramatically improved and represents the closest examples of a precision medicine intervention in this field. Nonetheless, prostate cancer (PCa) remains as a challenge to personalized medicine implementation, probably due to its notorious heterogeneous molecular profile. Cancer treatment personalized approaches rely on the premise that a well-defined panorama of tumor molecular alterations can help selecting new and specific therapeutic targets for its treatment and potentially discriminate tumors which behave differentially. Lately, molecular and genetic studies have been investigating PCa basis, revealing multiple recurrent genomic alterations that include mutations, DNA copy-number variations, rearrangements, and gene fusions, among others. In addition to the increment on PCa molecular biology knowledge, mapping the molecular alterations pattern of this neoplasia, especially the differences existent between tumors displaying distinct behaviors, could represent a great improvement concerning the identification of new targets, personalized medicine, and patients' management and prognosis. © 2017 International Federation for Cell Biology.

Integrated Bio-Entity Network: A System for Biological Knowledge Discovery

PubMed Central

Bell, Lindsey; Chowdhary, Rajesh; Liu, Jun S.; Niu, Xufeng; Zhang, Jinfeng

2011-01-01

A significant part of our biological knowledge is centered on relationships between biological entities (bio-entities) such as proteins, genes, small molecules, pathways, gene ontology (GO) terms and diseases. Accumulated at an increasing speed, the information on bio-entity relationships is archived in different forms at scattered places. Most of such information is buried in scientific literature as unstructured text. Organizing heterogeneous information in a structured form not only facilitates study of biological systems using integrative approaches, but also allows discovery of new knowledge in an automatic and systematic way. In this study, we performed a large scale integration of bio-entity relationship information from both databases containing manually annotated, structured information and automatic information extraction of unstructured text in scientific literature. The relationship information we integrated in this study includes protein–protein interactions, protein/gene regulations, protein–small molecule interactions, protein–GO relationships, protein–pathway relationships, and pathway–disease relationships. The relationship information is organized in a graph data structure, named integrated bio-entity network (IBN), where the vertices are the bio-entities and edges represent their relationships. Under this framework, graph theoretic algorithms can be designed to perform various knowledge discovery tasks. We designed breadth-first search with pruning (BFSP) and most probable path (MPP) algorithms to automatically generate hypotheses—the indirect relationships with high probabilities in the network. We show that IBN can be used to generate plausible hypotheses, which not only help to better understand the complex interactions in biological systems, but also provide guidance for experimental designs. PMID:21738677

ISOL@: an Italian SOLAnaceae genomics resource.

PubMed

Chiusano, Maria Luisa; D'Agostino, Nunzio; Traini, Alessandra; Licciardello, Concetta; Raimondo, Enrico; Aversano, Mario; Frusciante, Luigi; Monti, Luigi

2008-03-26

Present-day '-omics' technologies produce overwhelming amounts of data which include genome sequences, information on gene expression (transcripts and proteins) and on cell metabolic status. These data represent multiple aspects of a biological system and need to be investigated as a whole to shed light on the mechanisms which underpin the system functionality. The gathering and convergence of data generated by high-throughput technologies, the effective integration of different data-sources and the analysis of the information content based on comparative approaches are key methods for meaningful biological interpretations. In the frame of the International Solanaceae Genome Project, we propose here ISOLA, an Italian SOLAnaceae genomics resource. ISOLA (available at http://biosrv.cab.unina.it/isola) represents a trial platform and it is conceived as a multi-level computational environment.ISOLA currently consists of two main levels: the genome and the expression level. The cornerstone of the genome level is represented by the Solanum lycopersicum genome draft sequences generated by the International Tomato Genome Sequencing Consortium. Instead, the basic element of the expression level is the transcriptome information from different Solanaceae species, mainly in the form of species-specific comprehensive collections of Expressed Sequence Tags (ESTs). The cross-talk between the genome and the expression levels is based on data source sharing and on tools that enhance data quality, that extract information content from the levels' under parts and produce value-added biological knowledge. ISOLA is the result of a bioinformatics effort that addresses the challenges of the post-genomics era. It is designed to exploit '-omics' data based on effective integration to acquire biological knowledge and to approach a systems biology view. Beyond providing experimental biologists with a preliminary annotation of the tomato genome, this effort aims to produce a trial computational environment where different aspects and details are maintained as they are relevant for the analysis of the organization, the functionality and the evolution of the Solanaceae family.

Protease Inhibitors of Parasitic Flukes: Emerging Roles in Parasite Survival and Immune Defence.

PubMed

Ranasinghe, Shiwanthi L; McManus, Donald P

2017-05-01

Protease inhibitors play crucial roles in parasite development and survival, counteracting the potentially damaging immune responses of their vertebrate hosts. However, limited information is currently available on protease inhibitors from schistosomes and food-borne trematodes. Future characterization of these molecules is important not only to expand knowledge on parasitic fluke biology but also to determine whether they represent novel vaccine and/or drug targets. Moreover, protease inhibitors from flukes may represent lead compounds for the development of a new range of therapeutic agents against inflammatory disorders and cancer. This review discusses already identified protease inhibitors of fluke origin, emphasizing their biological function and their possible future development as new intervention targets. Copyright © 2016 Elsevier Ltd. All rights reserved.

Knowledge Discovery from Biomedical Ontologies in Cross Domains.

PubMed

Shen, Feichen; Lee, Yugyung

2016-01-01

In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability systems and practices. Semantic interoperability is difficult to achieve in these systems as the conceptual models underlying datasets are not fully exploited. In this paper, we propose a semantic framework, called Medical Knowledge Discovery and Data Mining (MedKDD), that aims to build a topic hierarchy and serve the semantic interoperability between different ontologies. For the purpose, we fully focus on the discovery of semantic patterns about the association of relations in the heterogeneous information network representing different types of objects and relationships in multiple biological ontologies and the creation of a topic hierarchy through the analysis of the discovered patterns. These patterns are used to cluster heterogeneous information networks into a set of smaller topic graphs in a hierarchical manner and then to conduct cross domain knowledge discovery from the multiple biological ontologies. Thus, patterns made a greater contribution in the knowledge discovery across multiple ontologies. We have demonstrated the cross domain knowledge discovery in the MedKDD framework using a case study with 9 primary biological ontologies from Bio2RDF and compared it with the cross domain query processing approach, namely SLAP. We have confirmed the effectiveness of the MedKDD framework in knowledge discovery from multiple medical ontologies.

Knowledge Discovery from Biomedical Ontologies in Cross Domains

PubMed Central

Shen, Feichen; Lee, Yugyung

2016-01-01

In recent years, there is an increasing demand for sharing and integration of medical data in biomedical research. In order to improve a health care system, it is required to support the integration of data by facilitating semantic interoperability systems and practices. Semantic interoperability is difficult to achieve in these systems as the conceptual models underlying datasets are not fully exploited. In this paper, we propose a semantic framework, called Medical Knowledge Discovery and Data Mining (MedKDD), that aims to build a topic hierarchy and serve the semantic interoperability between different ontologies. For the purpose, we fully focus on the discovery of semantic patterns about the association of relations in the heterogeneous information network representing different types of objects and relationships in multiple biological ontologies and the creation of a topic hierarchy through the analysis of the discovered patterns. These patterns are used to cluster heterogeneous information networks into a set of smaller topic graphs in a hierarchical manner and then to conduct cross domain knowledge discovery from the multiple biological ontologies. Thus, patterns made a greater contribution in the knowledge discovery across multiple ontologies. We have demonstrated the cross domain knowledge discovery in the MedKDD framework using a case study with 9 primary biological ontologies from Bio2RDF and compared it with the cross domain query processing approach, namely SLAP. We have confirmed the effectiveness of the MedKDD framework in knowledge discovery from multiple medical ontologies. PMID:27548262

Systems Biology Graphical Notation: Activity Flow language Level 1 Version 1.2.

PubMed

Mi, Huaiyu; Schreiber, Falk; Moodie, Stuart; Czauderna, Tobias; Demir, Emek; Haw, Robin; Luna, Augustin; Le Novère, Nicolas; Sorokin, Anatoly; Villéger, Alice

2015-09-04

The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail. The SBGN Activity Flow language represents the influences of activities among various entities within a network. Unlike SBGN PD and ER that focus on the entities and their relationships with others, SBGN AF puts the emphasis on the functions (or activities) performed by the entities, and their effects to the functions of the same or other entities. The nodes (elements) describe the biological activities of the entities, such as protein kinase activity, binding activity or receptor activity, which can be easily mapped to Gene Ontology molecular function terms. The edges (connections) provide descriptions of relationships (or influences) between the activities, e.g., positive influence and negative influence. Among all three languages of SBGN, AF is the closest to signaling pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.

Teachers' instructional goals for science practice: Identifying knowledge gaps using cultural-historical activity theory (CHAT)

NASA Astrophysics Data System (ADS)

Farrar, Cynthia Hamen

In AP Biology, the course goal, with respect to scientific acts and reasoning, has recently shifted toward a reform goal of science practice, where the goal is for students to have a scientific perspective that views science as a practice of a community rather than a body of knowledge. Given this recent shift, this study is interested in the gaps that may exist between an individual teacher's instructional goal and the goals of the AP Biology course. A Cultural-Historical Activity Theory (CHAT) methodology and perspective is used to analyze four teachers' knowledge, practice, and learning. Teachers have content knowledge for teaching, a form of knowledge that is unique for teaching called specialized content knowledge. This specialized content knowledge (SCK) defines their instructional goals, the student outcomes they ultimately aim to achieve with their students. The study employs a cultural-historical continuum of scientific acts and reasoning, which represents the development of the AP Biology goal over time, to study gaps in their instructional goal. The study also analyzes the contradictions within their teaching practice and how teachers address those contradictions to shift their instructional practice and learn. The findings suggest that teachers have different interpretations of the AP Biology goals of science practice, placing their instructional goal at different points along the continuum. Based on the location of their instructional goal, different micro-communities of teachers exist along the continuum, comprised of teachers with a shared goal, language, and culture of their AP Biology teaching. The in-depth study of one teacher's AP Biology teaching, using a CHAT perspective, provides a means for studying the mechanisms that connect SCK to classroom actions and ultimately to instructional practice. CHAT also reveals the nature and importance of contradictions or cognitive dissonance in teacher learning and the types of support teachers need to recognize contradictions and to internalize and set their instructional goal, facilitating their learning. Without recognition of contradictions, some of these micro-communities are not aware that their instruction is not in line with the AP Biology goal of science practice. An in-depth look at teacher learning revealed the criticality of reflective practice and the need for an "expert" within a teacher's community to facilitate = learning and develop SCK to incorporate science practice in classroom instruction.

Why build a virtual brain? Large-scale neural simulations as jump start for cognitive computing

NASA Astrophysics Data System (ADS)

Colombo, Matteo

2017-03-01

Despite the impressive amount of financial resources recently invested in carrying out large-scale brain simulations, it is controversial what the pay-offs are of pursuing this project. One idea is that from designing, building, and running a large-scale neural simulation, scientists acquire knowledge about the computational performance of the simulating system, rather than about the neurobiological system represented in the simulation. It has been claimed that this knowledge may usher in a new era of neuromorphic, cognitive computing systems. This study elucidates this claim and argues that the main challenge this era is facing is not the lack of biological realism. The challenge lies in identifying general neurocomputational principles for the design of artificial systems, which could display the robust flexibility characteristic of biological intelligence.

The polygonal model: A simple representation of biomolecules as a tool for teaching metabolism.

PubMed

Bonafe, Carlos Francisco Sampaio; Bispo, Jose Ailton Conceição; de Jesus, Marcelo Bispo

2018-01-01

Metabolism involves numerous reactions and organic compounds that the student must master to understand adequately the processes involved. Part of biochemical learning should include some knowledge of the structure of biomolecules, although the acquisition of such knowledge can be time-consuming and may require significant effort from the student. In this report, we describe the "polygonal model" as a new means of graphically representing biomolecules. This model is based on the use of geometric figures such as open triangles, squares, and circles to represent hydroxyl, carbonyl, and carboxyl groups, respectively. The usefulness of the polygonal model was assessed by undergraduate students in a classroom activity that consisted of "transforming" molecules from Fischer models to polygonal models and vice and versa. The survey was applied to 135 undergraduate Biology and Nursing students. Students found the model easy to use and we noted that it allowed identification of students' misconceptions in basic concepts of organic chemistry, such as in stereochemistry and organic groups that could then be corrected. The students considered the polygonal model easier and faster for representing molecules than Fischer representations, without loss of information. These findings indicate that the polygonal model can facilitate the teaching of metabolism when the structures of biomolecules are discussed. Overall, the polygonal model promoted contact with chemical structures, e.g. through drawing activities, and encouraged student-student dialog, thereby facilitating biochemical learning. © 2017 by The International Union of Biochemistry and Molecular Biology, 46(1):66-75, 2018. © 2017 The International Union of Biochemistry and Molecular Biology.

Trends in reproductive health knowledge following a health education intervention among adolescents in Zimbabwe.

PubMed

Rusakaniko, S; Mbizvo, M T; Kasule, J; Gupta, V; Kinoti, S N; Mpanju-Shumbushu, W; Sebina-Zziwa, J; Mwateba, R; Padayachy, J

1997-01-01

Unwanted teenage pregnancy, sexually transmitted infections and the attendant morbidity and mortality necessitate the need for understanding factors influencing adolescent sexuality and the implementation of programmes designed to improve their knowledge, reproductive behaviour, sexual and reproductive health. To determine the impact of an intervention package on knowledge levels of various reproductive health issues through trend analysis. Randomized controlled trial of a health education intervention in schools stratified for representativeness. Rural and urban secondary schools in Zimbabwe. 1,689 students recruited from 11 secondary schools in Mashonaland Central. Knowledge level before and after intervention. The demographic characteristics of the pupils at baseline, five months and nine months were comparable between the two groups. There was an overall increase in knowledge on menstruation. Students from the intervention schools were more likely to have correct knowledge over time on aspects of reproductive biology. A significant linear trend (p = 0.017) was observed in the area of family planning and contraception. A linear decreasing trend (p = 0.001) was observed on pregnancy risk. Though not significantly linear, the general trend of knowledge levels in all the areas of reproductive health, pregnancy risk, STDs and HIV/AIDS showed an upward trend, from 20% to 96%. Worth noting was that in all the areas the intervention group had knowledge above that in the control group. The reproductive health education intervention had an impact on aspects of reproductive biology and contraception as measured by the increased scoring at follow up when comparing intervention and control schools. The overall findings point to the need for early school based reproductive health education programmes incooperating correct information on reproductive biology and the prevention of subsequent reproductive morbidity by imparting information on non-risk behaviour during the early developmental years.

Synthetic Biology: A Unifying View and Review Using Analog Circuits.

PubMed

Teo, Jonathan J Y; Woo, Sung Sik; Sarpeshkar, Rahul

2015-08-01

We review the field of synthetic biology from an analog circuits and analog computation perspective, focusing on circuits that have been built in living cells. This perspective is well suited to pictorially, symbolically, and quantitatively representing the nonlinear, dynamic, and stochastic (noisy) ordinary and partial differential equations that rigorously describe the molecular circuits of synthetic biology. This perspective enables us to construct a canonical analog circuit schematic that helps unify and review the operation of many fundamental circuits that have been built in synthetic biology at the DNA, RNA, protein, and small-molecule levels over nearly two decades. We review 17 circuits in the literature as particular examples of feedforward and feedback analog circuits that arise from special topological cases of the canonical analog circuit schematic. Digital circuit operation of these circuits represents a special case of saturated analog circuit behavior and is automatically incorporated as well. Many issues that have prevented synthetic biology from scaling are naturally represented in analog circuit schematics. Furthermore, the deep similarity between the Boltzmann thermodynamic equations that describe noisy electronic current flow in subthreshold transistors and noisy molecular flux in biochemical reactions has helped map analog circuit motifs in electronics to analog circuit motifs in cells and vice versa via a `cytomorphic' approach. Thus, a body of knowledge in analog electronic circuit design, analysis, simulation, and implementation may also be useful in the robust and efficient design of molecular circuits in synthetic biology, helping it to scale to more complex circuits in the future.

TILDA-V: A full-differential code for proton tracking in biological matter

DOE PAGES

Quinto, M. A.; Monti, J. M.; Week, Philippe F.; ...

2015-09-07

Understanding the radiation-induced effects at the cellular level is of prime importance for predicting the fate of irradiated biological organisms. Thus, whether it is in radiobiology to identify the DNA critical lesions or in medicine to adapt the radio-therapeutic protocols, an accurate knowledge of the numerous interactions induced by charged particles in living matter is required. Monte-Carlo track-structure simulations represent the most suitable and powerful tools, in particular for modelling the full slowing-down of the ionizing particles in biological matter. Furthermore more of the existing codes are based on semi-empirical cross sections as well as the use of water asmore » surrogate of the biological matter.« less

An Undergraduate Course to Bridge the Gap between Textbooks and Scientific Research

PubMed Central

Wiegant, Fred; Scager, Karin; Boonstra, Johannes

2011-01-01

This article reports on a one-semester Advanced Cell Biology course that endeavors to bridge the gap between gaining basic textbook knowledge about cell biology and learning to think and work as a researcher. The key elements of this course are 1) learning to work with primary articles in order to get acquainted with the field of choice, to learn scientific reasoning, and to identify gaps in our current knowledge that represent opportunities for further research; 2) formulating a research project with fellow students; 3) gaining thorough knowledge of relevant methodology and technologies used within the field of cell biology; 4) developing cooperation and leadership skills; and 5) presenting and defending research projects before a jury of experts. The course activities were student centered and focused on designing a genuine research program. Our 5-yr experience with this course demonstrates that 1) undergraduate students are capable of delivering high-quality research designs that meet professional standards, and 2) the authenticity of the learning environment in this course strongly engages students to become self-directed and critical thinkers. We hope to provide colleagues with an example of a course that encourages and stimulates students to develop essential research thinking skills. PMID:21364103

An undergraduate course to bridge the gap between textbooks and scientific research.

PubMed

Wiegant, Fred; Scager, Karin; Boonstra, Johannes

2011-01-01

This article reports on a one-semester Advanced Cell Biology course that endeavors to bridge the gap between gaining basic textbook knowledge about cell biology and learning to think and work as a researcher. The key elements of this course are 1) learning to work with primary articles in order to get acquainted with the field of choice, to learn scientific reasoning, and to identify gaps in our current knowledge that represent opportunities for further research; 2) formulating a research project with fellow students; 3) gaining thorough knowledge of relevant methodology and technologies used within the field of cell biology; 4) developing cooperation and leadership skills; and 5) presenting and defending research projects before a jury of experts. The course activities were student centered and focused on designing a genuine research program. Our 5-yr experience with this course demonstrates that 1) undergraduate students are capable of delivering high-quality research designs that meet professional standards, and 2) the authenticity of the learning environment in this course strongly engages students to become self-directed and critical thinkers. We hope to provide colleagues with an example of a course that encourages and stimulates students to develop essential research thinking skills.

Biological standards for the Knowledge-Based BioEconomy: What is at stake.

PubMed

de Lorenzo, Víctor; Schmidt, Markus

2018-01-25

The contribution of life sciences to the Knowledge-Based Bioeconomy (KBBE) asks for the transition of contemporary, gene-based biotechnology from being a trial-and-error endeavour to becoming an authentic branch of engineering. One requisite to this end is the need for standards to measure and represent accurately biological functions, along with languages for data description and exchange. However, the inherent complexity of biological systems and the lack of quantitative tradition in the field have largely curbed this enterprise. Fortunately, the onset of systems and synthetic biology has emphasized the need for standards not only to manage omics data, but also to increase reproducibility and provide the means of engineering living systems in earnest. Some domains of biotechnology can be easily standardized (e.g. physical composition of DNA sequences, tools for genome editing, languages to encode workflows), while others might be standardized with some dedicated research (e.g. biological metrology, operative systems for bio-programming cells) and finally others will require a considerable effort, e.g. defining the rules that allow functional composition of biological activities. Despite difficulties, these are worthy attempts, as the history of technology shows that those who set/adopt standards gain a competitive advantage over those who do not. Copyright © 2017 Elsevier B.V. All rights reserved.

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables.

PubMed

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C; Downing, James R; Lamba, Jatinder

2009-08-15

In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org.

A semantic web ontology for small molecules and their biological targets.

PubMed

Choi, Jooyoung; Davis, Melissa J; Newman, Andrew F; Ragan, Mark A

2010-05-24

A wide range of data on sequences, structures, pathways, and networks of genes and gene products is available for hypothesis testing and discovery in biological and biomedical research. However, data describing the physical, chemical, and biological properties of small molecules have not been well-integrated with these resources. Semantically rich representations of chemical data, combined with Semantic Web technologies, have the potential to enable the integration of small molecule and biomolecular data resources, expanding the scope and power of biomedical and pharmacological research. We employed the Semantic Web technologies Resource Description Framework (RDF) and Web Ontology Language (OWL) to generate a Small Molecule Ontology (SMO) that represents concepts and provides unique identifiers for biologically relevant properties of small molecules and their interactions with biomolecules, such as proteins. We instanced SMO using data from three public data sources, i.e., DrugBank, PubChem and UniProt, and converted to RDF triples. Evaluation of SMO by use of predetermined competency questions implemented as SPARQL queries demonstrated that data from chemical and biomolecular data sources were effectively represented and that useful knowledge can be extracted. These results illustrate the potential of Semantic Web technologies in chemical, biological, and pharmacological research and in drug discovery.

Directed area search using socio-biological vision algorithms and cognitive Bayesian reasoning

NASA Astrophysics Data System (ADS)

Medasani, S.; Owechko, Y.; Allen, D.; Lu, T. C.; Khosla, D.

2010-04-01

Volitional search systems that assist the analyst by searching for specific targets or objects such as vehicles, factories, airports, etc in wide area overhead imagery need to overcome multiple problems present in current manual and automatic approaches. These problems include finding targets hidden in terabytes of information, relatively few pixels on targets, long intervals between interesting regions, time consuming analysis requiring many analysts, no a priori representative examples or templates of interest, detecting multiple classes of objects, and the need for very high detection rates and very low false alarm rates. This paper describes a conceptual analyst-centric framework that utilizes existing technology modules to search and locate occurrences of targets of interest (e.g., buildings, mobile targets of military significance, factories, nuclear plants, etc.), from video imagery of large areas. Our framework takes simple queries from the analyst and finds the queried targets with relatively minimum interaction from the analyst. It uses a hybrid approach that combines biologically inspired bottom up attention, socio-biologically inspired object recognition for volitionally recognizing targets, and hierarchical Bayesian networks for modeling and representing the domain knowledge. This approach has the benefits of high accuracy, low false alarm rate and can handle both low-level visual information and high-level domain knowledge in a single framework. Such a system would be of immense help for search and rescue efforts, intelligence gathering, change detection systems, and other surveillance systems.

The emergence of mind and brain: an evolutionary, computational, and philosophical approach.

PubMed

Mainzer, Klaus

2008-01-01

Modern philosophy of mind cannot be understood without recent developments in computer science, artificial intelligence (AI), robotics, neuroscience, biology, linguistics, and psychology. Classical philosophy of formal languages as well as symbolic AI assume that all kinds of knowledge must explicitly be represented by formal or programming languages. This assumption is limited by recent insights into the biology of evolution and developmental psychology of the human organism. Most of our knowledge is implicit and unconscious. It is not formally represented, but embodied knowledge, which is learnt by doing and understood by bodily interacting with changing environments. That is true not only for low-level skills, but even for high-level domains of categorization, language, and abstract thinking. The embodied mind is considered an emergent capacity of the brain as a self-organizing complex system. Actually, self-organization has been a successful strategy of evolution to handle the increasing complexity of the world. Genetic programs are not sufficient and cannot prepare the organism for all kinds of complex situations in the future. Self-organization and emergence are fundamental concepts in the theory of complex dynamical systems. They are also applied in organic computing as a recent research field of computer science. Therefore, cognitive science, AI, and robotics try to model the embodied mind in an artificial evolution. The paper analyzes these approaches in the interdisciplinary framework of complex dynamical systems and discusses their philosophical impact.

The impact of a prospective survey-based workplace intervention program on employee health, biologic stress markers, and organizational productivity.

PubMed

Anderzén, Ingrid; Arnetz, Bengt B

2005-07-01

To study whether knowledge about psychosocial work indicators and a structured method to implement changes based on such knowledge comprise an effective management tool for enhancing organizational as well as employee health and well-being. White- collar employees representing 22 different work units were assessed before and after a 1-year intervention program. Subjective ratings on health and work environment, biologic markers, absenteeism, and productivity were measured. Significant improvements in performance feedback, participatory management, employeeship, skills development, efficiency, leadership, employee well-being, and work-related exhaustion were identified. The restorative hormone testosterone increased during the intervention and changes correlated with increased overall organizational well-being. Absenteeism decreased and productivity improved. Fact-based psychosocial workplace interventions are suggested to be an important process for enhancing employee well-being as well as organizational performance.

Managing bioengineering complexity with AI techniques.

PubMed

Beal, Jacob; Adler, Aaron; Yaman, Fusun

2016-10-01

Our capabilities for systematic design and engineering of biological systems are rapidly increasing. Effectively engineering such systems, however, requires the synthesis of a rapidly expanding and changing complex body of knowledge, protocols, and methodologies. Many of the problems in managing this complexity, however, appear susceptible to being addressed by artificial intelligence (AI) techniques, i.e., methods enabling computers to represent, acquire, and employ knowledge. Such methods can be employed to automate physical and informational "routine" work and thus better allow humans to focus their attention on the deeper scientific and engineering issues. This paper examines the potential impact of AI on the engineering of biological organisms through the lens of a typical organism engineering workflow. We identify a number of key opportunities for significant impact, as well as challenges that must be overcome. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Biodiversity's big wet secret: the global distribution of marine biological records reveals chronic under-exploration of the deep pelagic ocean.

PubMed

Webb, Thomas J; Vanden Berghe, Edward; O'Dor, Ron

2010-08-02

Understanding the distribution of marine biodiversity is a crucial first step towards the effective and sustainable management of marine ecosystems. Recent efforts to collate location records from marine surveys enable us to assemble a global picture of recorded marine biodiversity. They also effectively highlight gaps in our knowledge of particular marine regions. In particular, the deep pelagic ocean--the largest biome on Earth--is chronically under-represented in global databases of marine biodiversity. We use data from the Ocean Biogeographic Information System to plot the position in the water column of ca 7 million records of marine species occurrences. Records from relatively shallow waters dominate this global picture of recorded marine biodiversity. In addition, standardising the number of records from regions of the ocean differing in depth reveals that regardless of ocean depth, most records come either from surface waters or the sea bed. Midwater biodiversity is drastically under-represented. The deep pelagic ocean is the largest habitat by volume on Earth, yet it remains biodiversity's big wet secret, as it is hugely under-represented in global databases of marine biological records. Given both its value in the provision of a range of ecosystem services, and its vulnerability to threats including overfishing and climate change, there is a pressing need to increase our knowledge of Earth's largest ecosystem.

RNA interference: from biology to drugs and therapeutics.

PubMed

Appasani, Krishnarao

2004-07-01

RNA interference (RNAi) is a newly discovered and popular technology platform among researchers not only in the fields of RNA biology and molecular cell biology. It has created excitement in clinical sciences such as oncology, neurology, endocrinology, infectious diseases and drug discovery. There is an urgent need to educate and connect academic and industry researchers for the purpose of knowledge transfer. Thus, GeneExpression Systems of Waltham organized its Second International Conference in Waltham City (May 2-4, 2004, MA, USA) on the theme of 'RNA interference: From Biology to Drugs & Therapeutics.' About 200 participants and 32 speakers attended this two and half-day event which was arranged in six scientific and three technology sessions and ended with a panel discussion. This report covers a few representative talks from academia, biotech and the drug industry.

Home-Based vs. Laboratory-Based Practical Activities in the Learning of Human Physiology: The Perception of Students

ERIC Educational Resources Information Center

Neves, Ben-Hur S.; Altermann, Caroline; Gonçalves, Rithiele; Lara, Marcus Vinícius; Mello-Carpes, Pâmela B.

2017-01-01

Different tools have been used to facilitate the teaching and learning process in different areas of knowledge. Practical activities represent a form of teaching in which students not only listen to theoretical concepts but are also able to link theory and practice, and their importance in the biological sciences is notable. Sometimes, however,…

From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data.

PubMed

Vella, Danila; Zoppis, Italo; Mauri, Giancarlo; Mauri, Pierluigi; Di Silvestre, Dario

2017-12-01

The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processes. This knowledge helped biologists to understand the complexity of the biological systems evidencing that most biological functions do not arise from individual molecules; thus, realizing that the emergent properties of the biological systems cannot be explained or be predicted by investigating individual molecules without taking into consideration their relations. Thanks to the improvement of the current -omics technologies and the increasing understanding of the molecular relationships, even more studies are evaluating the biological systems through approaches based on graph theory. Genomic and proteomic data are often combined with protein-protein interaction (PPI) networks whose structure is routinely analyzed by algorithms and tools to characterize hubs/bottlenecks and topological, functional, and disease modules. On the other hand, co-expression networks represent a complementary procedure that give the opportunity to evaluate at system level including organisms that lack information on PPIs. Based on these premises, we introduce the reader to the PPI and to the co-expression networks, including aspects of reconstruction and analysis. In particular, the new idea to evaluate large-scale proteomic data by means of co-expression networks will be discussed presenting some examples of application. Their use to infer biological knowledge will be shown, and a special attention will be devoted to the topological and module analysis.

Aliphatic, Cyclic, and Aromatic Organic Acids, Vitamins, and Carbohydrates in Soil: A Review

PubMed Central

Vranova, Valerie; Rejsek, Klement; Formanek, Pavel

2013-01-01

Organic acids, vitamins, and carbohydrates represent important organic compounds in soil. Aliphatic, cyclic, and aromatic organic acids play important roles in rhizosphere ecology, pedogenesis, food-web interactions, and decontamination of sites polluted by heavy metals and organic pollutants. Carbohydrates in soils can be used to estimate changes of soil organic matter due to management practices, whereas vitamins may play an important role in soil biological and biochemical processes. The aim of this work is to review current knowledge on aliphatic, cyclic, and aromatic organic acids, vitamins, and carbohydrates in soil and to identify directions for future research. Assessments of organic acids (aliphatic, cyclic, and aromatic) and carbohydrates, including their behaviour, have been reported in many works. However, knowledge on the occurrence and behaviour of D-enantiomers of organic acids, which may be abundant in soil, is currently lacking. Also, identification of the impact and mechanisms of environmental factors, such as soil water content, on carbohydrate status within soil organic matter remains to be determined. Finally, the occurrence of vitamins in soil and their role in biological and biochemical soil processes represent an important direction for future research. PMID:24319374

Aliphatic, cyclic, and aromatic organic acids, vitamins, and carbohydrates in soil: a review.

PubMed

Vranova, Valerie; Rejsek, Klement; Formanek, Pavel

2013-11-10

Organic acids, vitamins, and carbohydrates represent important organic compounds in soil. Aliphatic, cyclic, and aromatic organic acids play important roles in rhizosphere ecology, pedogenesis, food-web interactions, and decontamination of sites polluted by heavy metals and organic pollutants. Carbohydrates in soils can be used to estimate changes of soil organic matter due to management practices, whereas vitamins may play an important role in soil biological and biochemical processes. The aim of this work is to review current knowledge on aliphatic, cyclic, and aromatic organic acids, vitamins, and carbohydrates in soil and to identify directions for future research. Assessments of organic acids (aliphatic, cyclic, and aromatic) and carbohydrates, including their behaviour, have been reported in many works. However, knowledge on the occurrence and behaviour of D-enantiomers of organic acids, which may be abundant in soil, is currently lacking. Also, identification of the impact and mechanisms of environmental factors, such as soil water content, on carbohydrate status within soil organic matter remains to be determined. Finally, the occurrence of vitamins in soil and their role in biological and biochemical soil processes represent an important direction for future research.

Effects of model structural uncertainty on carbon cycle projections: biological nitrogen fixation as a case study

NASA Astrophysics Data System (ADS)

Wieder, William R.; Cleveland, Cory C.; Lawrence, David M.; Bonan, Gordon B.

2015-04-01

Uncertainties in terrestrial carbon (C) cycle projections increase uncertainty of potential climate feedbacks. Efforts to improve model performance often include increased representation of biogeochemical processes, such as coupled carbon-nitrogen (N) cycles. In doing so, models are becoming more complex, generating structural uncertainties in model form that reflect incomplete knowledge of how to represent underlying processes. Here, we explore structural uncertainties associated with biological nitrogen fixation (BNF) and quantify their effects on C cycle projections. We find that alternative plausible structures to represent BNF result in nearly equivalent terrestrial C fluxes and pools through the twentieth century, but the strength of the terrestrial C sink varies by nearly a third (50 Pg C) by the end of the twenty-first century under a business-as-usual climate change scenario representative concentration pathway 8.5. These results indicate that actual uncertainty in future C cycle projections may be larger than previously estimated, and this uncertainty will limit C cycle projections until model structures can be evaluated and refined.

Guidelines for biosafety laboratory competency: CDC and the Association of Public Health Laboratories.

PubMed

Delany, Judy R; Pentella, Michael A; Rodriguez, Joyce A; Shah, Kajari V; Baxley, Karen P; Holmes, David E

2011-04-15

These guidelines for biosafety laboratory competency outline the essential skills, knowledge, and abilities required for working with biologic agents at the three highest biosafety levels (BSLs) (levels 2, 3, and 4). The competencies are tiered to a worker's experience at three levels: entry level, midlevel (experienced), and senior level (supervisory or managerial positions). These guidelines were developed on behalf of CDC and the Association of Public Health Laboratories (APHL) by an expert panel comprising 27 experts representing state and federal public health laboratories, private sector clinical and research laboratories, and academic centers. They were then reviewed by approximately 300 practitioners representing the relevant fields. The guidelines are intended for laboratorians working with hazardous biologic agents, obtained from either samples or specimens that are maintained and manipulated in clinical, environmental, public health, academic, and research laboratories.

Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection.

PubMed

Guthke, Reinhard; Möller, Ulrich; Hoffmann, Martin; Thies, Frank; Töpfer, Susanne

2005-04-15

The immune response to bacterial infection represents a complex network of dynamic gene and protein interactions. We present an optimized reverse engineering strategy aimed at a reconstruction of this kind of interaction networks. The proposed approach is based on both microarray data and available biological knowledge. The main kinetics of the immune response were identified by fuzzy clustering of gene expression profiles (time series). The number of clusters was optimized using various evaluation criteria. For each cluster a representative gene with a high fuzzy-membership was chosen in accordance with available physiological knowledge. Then hypothetical network structures were identified by seeking systems of ordinary differential equations, whose simulated kinetics could fit the gene expression profiles of the cluster-representative genes. For the construction of hypothetical network structures singular value decomposition (SVD) based methods and a newly introduced heuristic Network Generation Method here were compared. It turned out that the proposed novel method could find sparser networks and gave better fits to the experimental data. Reinhard.Guthke@hki-jena.de.

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables

PubMed Central

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R.; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C.; Downing, James R.; Lamba, Jatinder

2009-01-01

Motivation: In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Results: Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Availability: Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org. Contact: stanley.pounds@stjude.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19528086

Computing biological functions using BioΨ, a formal description of biological processes based on elementary bricks of actions

PubMed Central

Pérès, Sabine; Felicori, Liza; Rialle, Stéphanie; Jobard, Elodie; Molina, Franck

2010-01-01

Motivation: In the available databases, biological processes are described from molecular and cellular points of view, but these descriptions are represented with text annotations that make it difficult to handle them for computation. Consequently, there is an obvious need for formal descriptions of biological processes. Results: We present a formalism that uses the BioΨ concepts to model biological processes from molecular details to networks. This computational approach, based on elementary bricks of actions, allows us to calculate on biological functions (e.g. process comparison, mapping structure–function relationships, etc.). We illustrate its application with two examples: the functional comparison of proteases and the functional description of the glycolysis network. This computational approach is compatible with detailed biological knowledge and can be applied to different kinds of systems of simulation. Availability: www.sysdiag.cnrs.fr/publications/supplementary-materials/BioPsi_Manager/ Contact: sabine.peres@sysdiag.cnrs.fr; franck.molina@sysdiag.cnrs.fr Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20448138

Local knowledge and perception of biological soil crusts by land users in the Sahel (Niger)

NASA Astrophysics Data System (ADS)

J-M Ambouta, K.; Hassan Souley, B.; Malam Issa, O.; Rajot, J. L.; Mohamadou, A.

2012-04-01

Local knowledge, i.e. knowledge based on accumulation of observations is of great interest for many scientific fields as it can help for identification, evaluation and selection of relevant indicators and furthermore for progress through conservation goals. This study aimed at gathering and understanding the local knowledge and perception of biological soil crusts (BSC) by users of land, pastoralists that cross the Sahel and sedentary farmers. The methodological approach is based on a semi-direct surveys conducted on a north-south rainfall gradient (350 to 650 mm/year) including agricultural- and pastoral-dominated areas in western Niger. Denomination, formation processes, occurrence, distribution and role of biological soil crusts are among the major issues of the inquiry. The results of the surveys showed that BSC are mainly identified by the names of "Bankwado" and "Korobanda", respectively in hausa and zarma langages, what means "toad back". Other denominations varying according to region, ethnic groups and users are used. They are all related to the aspects, colors and behaviour of BSC with regard wetting and drying cycle. From the point of view of users depressed areas and land lied fallow are favourable places for the occurrence of BSC, while cultivation and observed changes in rainfall regimes represent negative factors. The formation processes of BSC are mainly related to the occurrence and the impact of rain and wind on soil surface. Their roles in protecting soil against degradation or as an indicator of soil fertility were recognised by at least 83% of farmers and breeders. This study reveals significant aspects of BSC already validated by scientific knowledge. Integrating the two forms of knowledge will help to define relevant indicators of soil surface dynamics and to perform practices to minimize farming and grazing impacts on BSCs.

An Optimization-Based Framework for the Transformation of Incomplete Biological Knowledge into a Probabilistic Structure and Its Application to the Utilization of Gene/Protein Signaling Pathways in Discrete Phenotype Classification.

PubMed

Esfahani, Mohammad Shahrokh; Dougherty, Edward R

2015-01-01

Phenotype classification via genomic data is hampered by small sample sizes that negatively impact classifier design. Utilization of prior biological knowledge in conjunction with training data can improve both classifier design and error estimation via the construction of the optimal Bayesian classifier. In the genomic setting, gene/protein signaling pathways provide a key source of biological knowledge. Although these pathways are neither complete, nor regulatory, with no timing associated with them, they are capable of constraining the set of possible models representing the underlying interaction between molecules. The aim of this paper is to provide a framework and the mathematical tools to transform signaling pathways to prior probabilities governing uncertainty classes of feature-label distributions used in classifier design. Structural motifs extracted from the signaling pathways are mapped to a set of constraints on a prior probability on a Multinomial distribution. Being the conjugate prior for the Multinomial distribution, we propose optimization paradigms to estimate the parameters of a Dirichlet distribution in the Bayesian setting. The performance of the proposed methods is tested on two widely studied pathways: mammalian cell cycle and a p53 pathway model.

A protocol for generating a high-quality genome-scale metabolic reconstruction.

PubMed

Thiele, Ines; Palsson, Bernhard Ø

2010-01-01

Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process.

A protocol for generating a high-quality genome-scale metabolic reconstruction

PubMed Central

Thiele, Ines; Palsson, Bernhard Ø.

2011-01-01

Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have developed over the past 10 years. These reconstructions represent structured knowledge-bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates myriad computational biological studies including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics, and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge-bases. Here, we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction as well as common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process. PMID:20057383

Defending definitions of life.

PubMed

Mix, Lucas John

2015-01-01

Over the past 10 years, it has become unpopular to talk about definitions of life, under the assumption that attempts at a precise definition are counterproductive. Recent attempts have failed to meet strict philosophical criteria for definitions and have failed to reach consensus. I argue that provisional definitions are necessary for clear communications. Our current knowledge of biology justifies a number of universal claims about the category of life. Whether or not "life" represents a natural category, it maps to a number of important, observable processes. Given the importance of those processes and the extent of our knowledge, plural explicit definitions of life (and related categories) will be necessary for progress in astrobiology and origin-of-life studies as well as biology in general. I propose concrete categories related to, but not necessarily coextensive with, life for clear communication and hypothesis formation: Woese life, Darwin life, Haldane life.

Molecular Pharmacology of Malignant Pleural Mesothelioma: Challenges and Perspectives From Preclinical and Clinical Studies.

PubMed

Thellung, Stefano; Favoni, Roberto E; Würth, Roberto; Nizzari, Mario; Pattarozzi, Alessandra; Daga, Antonio; Florio, Tullio; Barbieri, Federica

2016-01-01

Malignant pleural mesothelioma (MPM) is one of the deadliest and most heterogeneous tumors, highly refractory to multimodal therapeutic approach, including surgery, chemo- and radiotherapy. Preclinical and clinical studies exploring the efficacy of drugs targeting tyrosine kinases, angiogenesis and histone deacetylases, did not fulfil the expected clinical benefits. Thus, novel molecular targets should be identified from a definite knowledge of the unique biology and most relevant transduction pathways of MPM cells. Cancer stem cells (CSCs) are a subset of malignant precursors responsible for initiation, progression, resistance to cytotoxic drugs, recurrence and metastatic diffusion of tumor cells. CSCs are putative driving factors for MPM development and contribute to its clinical and biological heterogeneity; hence, targeted eradication of CSCs represents an ineludible goal to counteract MPM aggressiveness. In this context, innovative preclinical models could be exploited to identify novel intracellular pathway inhibitors able to target CSC viability. Novel drug targets have been identified among key factors responsible for the oncogenic transformation of mesothelial cells, often directly induced by asbestos. These include mitogenic and anti-apoptotic signaling that may also be activated by autocrine and paracrine cytokine pathways controlling cell plasticity. Both signaling pathways affecting proto-oncogene and transcription factor expression, or genetic and epigenetic alterations, such as mutations in cell cycle genes and silencing of tumor suppressor genes, represent promising disease-specific targets. In this review we describe current knowledge of MPM cell biology, focusing on potential targets to be tested in pharmacological studies, and highlighting results and challenges of clinical translation.

Long Non-coding RNAs and Their Biological Roles in Plants

PubMed Central

Liu, Xue; Hao, Lili; Li, Dayong; Zhu, Lihuang; Hu, Songnian

2015-01-01

With the development of genomics and bioinformatics, especially the extensive applications of high-throughput sequencing technology, more transcriptional units with little or no protein-coding potential have been discovered. Such RNA molecules are called non-protein-coding RNAs (npcRNAs or ncRNAs). Among them, long npcRNAs or ncRNAs (lnpcRNAs or lncRNAs) represent diverse classes of transcripts longer than 200 nucleotides. In recent years, the lncRNAs have been considered as important regulators in many essential biological processes. In plants, although a large number of lncRNA transcripts have been predicted and identified in few species, our current knowledge of their biological functions is still limited. Here, we have summarized recent studies on their identification, characteristics, classification, bioinformatics, resources, and current exploration of their biological functions in plants. PMID:25936895

Foundational concepts and underlying theories for majors in "biochemistry and molecular biology".

PubMed

Tansey, John T; Baird, Teaster; Cox, Michael M; Fox, Kristin M; Knight, Jennifer; Sears, Duane; Bell, Ellis

2013-01-01

Over the past two years, through an NSF RCN UBE grant, the ASBMB has held regional workshops for faculty members and science educators from around the country that focused on identifying: 1) core principles of biochemistry and molecular biology, 2) essential concepts and underlying theories from physics, chemistry, and mathematics, and 3) foundational skills that undergraduate majors in biochemistry and molecular biology must understand to complete their major coursework. Using information gained from these workshops, as well as from the ASBMB accreditation working group and the NSF Vision and Change report, the Core Concepts working group has developed a consensus list of learning outcomes and objectives based on five foundational concepts (evolution, matter and energy transformation, homeostasis, information flow, and macromolecular structure and function) that represent the expected conceptual knowledge base for undergraduate degrees in biochemistry and molecular biology. This consensus will aid biochemistry and molecular biology educators in the development of assessment tools for the new ASBMB recommended curriculum. © 2013 by The International Union of Biochemistry and Molecular Biology.

Biodiversity's Big Wet Secret: The Global Distribution of Marine Biological Records Reveals Chronic Under-Exploration of the Deep Pelagic Ocean

PubMed Central

Webb, Thomas J.; Vanden Berghe, Edward; O'Dor, Ron

2010-01-01

Background Understanding the distribution of marine biodiversity is a crucial first step towards the effective and sustainable management of marine ecosystems. Recent efforts to collate location records from marine surveys enable us to assemble a global picture of recorded marine biodiversity. They also effectively highlight gaps in our knowledge of particular marine regions. In particular, the deep pelagic ocean – the largest biome on Earth – is chronically under-represented in global databases of marine biodiversity. Methodology/Principal Findings We use data from the Ocean Biogeographic Information System to plot the position in the water column of ca 7 million records of marine species occurrences. Records from relatively shallow waters dominate this global picture of recorded marine biodiversity. In addition, standardising the number of records from regions of the ocean differing in depth reveals that regardless of ocean depth, most records come either from surface waters or the sea bed. Midwater biodiversity is drastically under-represented. Conclusions/Significance The deep pelagic ocean is the largest habitat by volume on Earth, yet it remains biodiversity's big wet secret, as it is hugely under-represented in global databases of marine biological records. Given both its value in the provision of a range of ecosystem services, and its vulnerability to threats including overfishing and climate change, there is a pressing need to increase our knowledge of Earth's largest ecosystem. PMID:20689845

Discovery of chitin in skeletons of non-verongiid Red Sea demosponges.

PubMed

Ehrlich, Hermann; Shaala, Lamiaa A; Youssef, Diaa T A; Żółtowska-Aksamitowska, Sonia; Tsurkan, Mikhail; Galli, Roberta; Meissner, Heike; Wysokowski, Marcin; Petrenko, Iaroslav; Tabachnick, Konstantin R; Ivanenko, Viatcheslav N; Bechmann, Nicole; Joseph, Yvonne; Jesionowski, Teofil

2018-01-01

Marine demosponges (Porifera: Demospongiae) are recognized as first metazoans which have developed over millions of years of evolution effective survival strategies based on unique metabolic pathways to produce both biologically active secondary metabolites and biopolymer-based stiff skeletons with 3D architecture. Up to date, among marine demosponges, only representatives of the Verongiida order have been known to synthetize biologically active substances as well as skeletons made of structural polysaccharide chitin. This work, to our knowledge, demonstrates for the first time that chitin is an important structural component within skeletons of non-verongiid demosponges Acarnus wolffgangi and Echinoclathria gibbosa collected in the Red Sea. Calcofluor white staining, FTIR and Raman analysis, ESI-MS, SEM, and fluorescence microscopy as well as a chitinase digestion assay were applied in order to confirm, with strong evidence, the finding of α-chitin in the skeleton of both species. We suggest that, the finding of chitin within these representatives of Poecilosclerida order is a promising step in the evaluation of these sponges as novel renewable sources for both biologically active metabolites and chitin, which are of prospective application for pharmacology and biomedicine.

Biomaterial Selection for Tooth Regeneration

PubMed Central

Yuan, Zhenglin; Nie, Hemin; Wang, Shuang; Lee, Chang Hun; Li, Ang; Fu, Susan Y.; Zhou, Hong

2011-01-01

Biomaterials are native or synthetic polymers that act as carriers for drug delivery or scaffolds for tissue regeneration. When implanted in vivo, biomaterials should be nontoxic and exert intended functions. For tooth regeneration, biomaterials have primarily served as a scaffold for (1) transplanted stem cells and/or (2) recruitment of endogenous stem cells. This article critically synthesizes our knowledge of biomaterial use in tooth regeneration, including the selection of native and/or synthetic polymers, three-dimensional scaffold fabrication, stem cell transplantation, and stem cell homing. A tooth is a complex biological organ. Tooth loss represents the most common organ failure. Tooth regeneration encompasses not only regrowth of an entire tooth as an organ, but also biological restoration of individual components of the tooth including enamel, dentin, cementum, or dental pulp. Regeneration of tooth root represents perhaps more near-term opportunities than the regeneration of the whole tooth. In the adult, a tooth owes its biological vitality, arguably more, to the root than the crown. Biomaterials are indispensible for the regeneration of tooth root, tooth crown, dental pulp, or an entire tooth. PMID:21699433

Genetic heterogeneity in autism: From single gene to a pathway perspective.

PubMed

An, Joon Yong; Claudianos, Charles

2016-09-01

The extreme genetic heterogeneity of autism spectrum disorder (ASD) represents a major challenge. Recent advances in genetic screening and systems biology approaches have extended our knowledge of the genetic etiology of ASD. In this review, we discuss the paradigm shift from a single gene causation model to pathway perturbation model as a guide to better understand the pathophysiology of ASD. We discuss recent genetic findings obtained through next-generation sequencing (NGS) and examine various integrative analyses using systems biology and complex networks approaches that identify convergent patterns of genetic elements associated with ASD. Copyright © 2016 Elsevier Ltd. All rights reserved.

Primary thermosensory events in cells.

PubMed

Digel, Ilya

2011-01-01

Temperature sensing is essential for the survival of living organisms. Since thermal gradients are almost everywhere, thermoreception could represent one of the oldest sensory transduction processes that evolved in organisms. There are many examples of temperature changes affecting the physiology of living cells. Almost all classes of biological macromolecules in a cell (nucleic acids, lipids, proteins) can serve as a target of the temperature-related stimuli. This review is devoted to some common features of different classes of temperature-sensing molecules as well as molecular and biological processes involved in thermosensation. Biochemical, structural and thermodynamic approaches are discussed in order to overview the existing knowledge on molecular mechanisms of thermosensation.

Self-Organizing Hidden Markov Model Map (SOHMMM): Biological Sequence Clustering and Cluster Visualization.

PubMed

Ferles, Christos; Beaufort, William-Scott; Ferle, Vanessa

2017-01-01

The present study devises mapping methodologies and projection techniques that visualize and demonstrate biological sequence data clustering results. The Sequence Data Density Display (SDDD) and Sequence Likelihood Projection (SLP) visualizations represent the input symbolical sequences in a lower-dimensional space in such a way that the clusters and relations of data elements are depicted graphically. Both operate in combination/synergy with the Self-Organizing Hidden Markov Model Map (SOHMMM). The resulting unified framework is in position to analyze automatically and directly raw sequence data. This analysis is carried out with little, or even complete absence of, prior information/domain knowledge.

Optimization of Graphene Sensors to Detect Biological Warfare Agents

DTIC Science & Technology

2014-03-27

conductor and a metal at room temperature [53] and in some cases, it acts like a p- type semiconductor [54]. The knowledge of the conductivity ...aptamer functionalized graphene layer interaction was available. Silicon wafers with thermal oxide coats were explored as a next step. The available...picked due to its high electrical conductivity (100,00cm/Vs) and functionalization properties [17]. Figure 1 conceptually represents a graphene-field

Systematic reconstruction of TRANSPATH data into Cell System Markup Language

PubMed Central

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-01-01

Background Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. Results We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. Conclusion By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions. PMID:18570683

Systematic reconstruction of TRANSPATH data into cell system markup language.

PubMed

Nagasaki, Masao; Saito, Ayumu; Li, Chen; Jeong, Euna; Miyano, Satoru

2008-06-23

Many biological repositories store information based on experimental study of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, or regulations of transcription factors and miRNA. Unfortunately, it is difficult to directly use such information when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level. We selected the TRANSPATH database, a manually curated high-quality pathway database, which provides a plentiful source of cellular events in humans, mice, and rats, collected from over 31,500 publications. In this work, we have developed 16 modeling rules based on hybrid functional Petri net with extension (HFPNe), which is suitable for graphical representing and simulating biological processes. In the modeling rules, each Petri net element is incorporated with Cell System Ontology to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO also defines biological terminology and corresponding icons. By combining HFPNe with the CSO features, it is possible to make TRANSPATH data to simulation-based and semantically valid models. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. By using the 16 modeling rules, 97% of the reactions in TRANSPATH are converted into simulation-based models represented in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.

Direction discovery: A science enrichment program for high school students.

PubMed

Sikes, Suzanne S; Schwartz-Bloom, Rochelle D

2009-03-01

Launch into education about pharmacology (LEAP) is an inquiry-based science enrichment program designed to enhance competence in biology and chemistry and foster interest in science careers especially among under-represented minorities. The study of how drugs work, how they enter cells, alter body chemistry, and exit the body engages students to conceptualize fundamental precepts in biology, chemistry, and math. Students complete an intensive three-week course in the fundamentals of pharmacology during the summer followed by a mentored research component during the school year. Following a 5E learning paradigm, the summer course captures student interest by introducing controversial topics in pharmacology and provides a framework that guides them to explore topics in greater detail. The 5E learning cycle is recapitulated as students extend their knowledge to design and to test an original research question in pharmacology. LEAP students demonstrated significant gains in biology and chemistry knowledge and interests in pursuing science. Several students earned honors for the presentation of their research in regional and state science fairs. Success of the LEAP model in its initial 2 years argues that coupling college-level coursework of interest to teens with an authentic research experience enhances high school student success in and enthusiasm for science. Copyright © 2009 International Union of Biochemistry and Molecular Biology, Inc.

Long non-coding RNAs and their biological roles in plants.

PubMed

Liu, Xue; Hao, Lili; Li, Dayong; Zhu, Lihuang; Hu, Songnian

2015-06-01

With the development of genomics and bioinformatics, especially the extensive applications of high-throughput sequencing technology, more transcriptional units with little or no protein-coding potential have been discovered. Such RNA molecules are called non-protein-coding RNAs (npcRNAs or ncRNAs). Among them, long npcRNAs or ncRNAs (lnpcRNAs or lncRNAs) represent diverse classes of transcripts longer than 200 nucleotides. In recent years, the lncRNAs have been considered as important regulators in many essential biological processes. In plants, although a large number of lncRNA transcripts have been predicted and identified in few species, our current knowledge of their biological functions is still limited. Here, we have summarized recent studies on their identification, characteristics, classification, bioinformatics, resources, and current exploration of their biological functions in plants. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

[Occupational biological hazard in veterinary medicine: an area for priority interventions].

PubMed

Cediel, Natalia M; Villamil, Luis C

2004-01-01

Veterinary medicine is an activity related to several health hazards; during the last years, studies about the biological hazard associated to animals have been conducted, such hazards represented by the zoonotic diseases and the allergic reactions in exposed workers. Despite its importance, in Colombia the knowledge about the occupational biohazard is scarce, its magnitude is overlooked and in addition a passive attitude from practitioners exists. The few research spaces available and the scattered actions for its prevention, influence directly on the workers' health, on the quality of the services offered and obviously on the quality of life in society. The present article discusses the causes and consequences of biological hazards in veterinary medicine, shows a panorama of the national problem and contributes with alternatives for its solutions.

Using graph theory to analyze biological networks

PubMed Central

2011-01-01

Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system. PMID:21527005

DFT study of quercetin activated forms involved in antiradical, antioxidant, and prooxidant biological processes.

PubMed

Fiorucci, Sébastien; Golebiowski, Jérôme; Cabrol-Bass, Daniel; Antonczak, Serge

2007-02-07

Quercetin, one of the most representative flavonoid compounds, is involved in antiradical, antioxidant, and prooxidant biological processes. Despite a constant increase of knowledge on both positive and negative activities of quercetin, it is unclear which activated form (quinone, semiquinone, or deprotonated) actually plays a role in each of these processes. Structural, electronic, and energetic characteristics of quercetin, as well as the influence of a copper ion on all of these parameters, are studied by means of quantum chemical electronic structure calculations. Introduction of thermodynamic cycles together with the role of coreactive compounds, such as reactive oxygen species, gives a glimpse of the most probable reaction schemes. Such a theoretical approach provides another hint to clarify which reaction is likely to occur within the broad range of quercetin biological activities.

An investigation of the relationships between junior high school students' (8th and 9th grades) background variables and structure of knowledge recall of biological content

NASA Astrophysics Data System (ADS)

Demetrius, Olive Joyce

The purpose of this study was to examine the relationships between Junior High School students' (8th and 9th grades) background variables (e.g. cognitive factors, prior knowledge, preference for science versus non-science activities, formal and informal activities) and structure of information recall of biological content. In addition, this study will illustrate how flow maps, a graphic display, designed to represent the sequential flow and cross linkage of ideas in information recalled by the learner can be used as a tool for analyzing science learning data. The participants (46 junior high school students) were taught a lesson on the human digestive system during which they were shown a model of the human torso. Their pattern of information recall was determined by using an interview technique to elicit their understanding of the functional anatomy of the human digestive system. The taped responses were later transcribed for construction of the flow map. The interview was also used to assess knowledge recall of biological content. The flow map, science interest questionnaire and the cognitive operations (based on content analysis of student's narrative) were used to analyze data from each respondent. This is a case study using individual subjects and interview techniques. The findings of this study are: (1) Based on flow map data higher academic ability students have more networking of ideas than low ability students. (2) A large percentage of 9th grade low ability students intend to pursue science/applied science course work after leaving school but they lack well organized ways of representing science knowledge in memory. (3) Content analysis of the narratives shows that students with more complex ideational networks use higher order cognitive thought processes compared to those with less networking of ideas. If students are to make a successful transition from low academic performance to high academic performance it seems that more emphasis should be placed on information networking skills. This is specifically likely to be productive for student currently performing on low academic ability levels and yet have high aspirations for pursuing science as a career.

Systems biology by the rules: hybrid intelligent systems for pathway modeling and discovery.

PubMed

Bosl, William J

2007-02-15

Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication. A novel approach for biological pathway modeling based on hybrid intelligent systems or soft computing technologies is presented here. Intelligent hybrid systems, which refers to several related computing methods such as fuzzy logic, neural nets, genetic algorithms, and statistical analysis, has become ubiquitous in engineering applications for complex control system modeling and design. Biological pathways may be considered to be complex control systems, which medicine tries to manipulate to achieve desired results. Thus, hybrid intelligent systems may provide a useful tool for modeling biological system dynamics and computational exploration of new drug targets. A new modeling approach based on these methods is presented in the context of hedgehog regulation of the cell cycle in granule cells. Code and input files can be found at the Bionet website: www.chip.ord/~wbosl/Software/Bionet. This paper presents the algorithmic methods needed for modeling complicated biochemical dynamics using rule-based models to represent expert knowledge in the context of cell cycle regulation and tumor growth. A notable feature of this modeling approach is that it allows biologists to build complex models from their knowledge base without the need to translate that knowledge into mathematical form. Dynamics on several levels, from molecular pathways to tissue growth, are seamlessly integrated. A number of common network motifs are examined and used to build a model of hedgehog regulation of the cell cycle in cerebellar neurons, which is believed to play a key role in the etiology of medulloblastoma, a devastating childhood brain cancer.

The Effect of Knowledge Linking Levels in Biology Lessons upon Students' Knowledge Structure

ERIC Educational Resources Information Center

Wadouh, Julia; Liu, Ning; Sandmann, Angela; Neuhaus, Birgit J.

2014-01-01

Knowledge structure is an important aspect for defining students' competency in biology learning, but how knowledge structure is influenced by the teaching process in naturalistic biology classroom settings has scarcely been empirically investigated. In this study, 49 biology lessons in the teaching unit "blood and circulatory system" in…

The Metals in the Biological Periodic System of the Elements: Concepts and Conjectures

PubMed Central

Maret, Wolfgang

2016-01-01

A significant number of chemical elements are either essential for life with known functions, or present in organisms with poorly defined functional outcomes. We do not know all the essential elements with certainty and we know even less about the functions of apparently non-essential elements. In this article, I discuss a basis for a biological periodic system of the elements and that biochemistry should include the elements that are traditionally part of inorganic chemistry and not only those that are in the purview of organic chemistry. A biological periodic system of the elements needs to specify what “essential” means and to which biological species it refers. It represents a snapshot of our present knowledge and is expected to undergo further modifications in the future. An integrated approach of biometal sciences called metallomics is required to understand the interactions of metal ions, the biological functions that their chemical structures acquire in the biological system, and how their usage is fine-tuned in biological species and in populations of species with genetic variations (the variome). PMID:26742035

The evaluation of sources of knowledge underlying different conceptual categories.

PubMed

Gainotti, Guido; Spinelli, Pietro; Scaricamazza, Eugenia; Marra, Camillo

2013-01-01

According to the "embodied cognition" theory and the "sensory-motor model of semantic knowledge": (a) concepts are represented in the brain in the same format in which they are constructed by the sensory-motor system and (b) various conceptual categories differ according to the weight of different kinds of information in their representation. In this study, we tried to check the second assumption by asking normal elderly subjects to subjectively evaluate the role of various perceptual, motor and language-mediated sources of knowledge in the construction of different semantic categories. Our first aim was to rate the influence of different sources of knowledge in the representation of animals, plant life and artifact categories, rather than in living and non-living beings, as many previous studies on this subject have done. We also tried to check the influence of age and stimulus modality on these evaluations of the "sources of knowledge" underlying different conceptual categories. The influence of age was checked by comparing results obtained in our group of elderly subjects with those obtained in a previous study, conducted with a similar methodology on a sample of young students. And the influence of stimulus modality was assessed by presenting the stimuli in the verbal modality to 50 subjects and in the pictorial modality to 50 other subjects. The distinction between "animals" and "plant life" in the "living" categories was confirmed by analyzing their prevalent sources of knowledge and by a cluster analysis, which allowed us to distinguish "plant life" items from animals. Furthermore, results of the study showed: (a) that our subjects considered the visual modality as the main source of knowledge for all categories taken into account; and (b) that in biological categories the next most important source of information was represented by other perceptual modalities, whereas in artifacts it was represented by the actions performed with them. Finally, age and stimulus modality did not significantly influence judgment of relevance of the sources of knowledge involved in the construction of different conceptual categories.

Exploring biological, chemical and geomorphological patterns in fluvial ecosystems with Structural Equation Modelling

NASA Astrophysics Data System (ADS)

Bizzi, S.; Surridge, B.; Lerner, D. N.:

2009-04-01

River ecosystems represent complex networks of interacting biological, chemical and geomorphological processes. These processes generate spatial and temporal patterns in biological, chemical and geomorphological variables, and a growing number of these variables are now being used to characterise the status of rivers. However, integrated analyses of these biological-chemical-geomorphological networks have rarely been undertaken, and as a result our knowledge of the underlying processes and how they generate the resulting patterns remains weak. The apparent complexity of the networks involved, and the lack of coherent datasets, represent two key challenges to such analyses. In this paper we describe the application of a novel technique, Structural Equation Modelling (SEM), to the investigation of biological, chemical and geomorphological data collected from rivers across England and Wales. The SEM approach is a multivariate statistical technique enabling simultaneous examination of direct and indirect relationships across a network of variables. Further, SEM allows a-priori conceptual or theoretical models to be tested against available data. This is a significant departure from the solely exploratory analyses which characterise other multivariate techniques. We took biological, chemical and river habitat survey data collected by the Environment Agency for 400 sites in rivers spread across England and Wales, and created a single, coherent dataset suitable for SEM analyses. Biological data cover benthic macroinvertebrates, chemical data relate to a range of standard parameters (e.g. BOD, dissolved oxygen and phosphate concentration), and geomorphological data cover factors such as river typology, substrate material and degree of physical modification. We developed a number of a-priori conceptual models, reflecting current research questions or existing knowledge, and tested the ability of these conceptual models to explain the variance and covariance within the dataset. The conceptual models we developed were able to explain correctly the variance and covariance shown by the datasets, proving to be a relevant representation of the processes involved. The models explained 65% of the variance in indices describing benthic macroinvertebrate communities. Dissolved oxygen was of primary importance, but geomorphological factors, including river habitat type and degree of habitat degradation, also had significant explanatory power. The addition of spatial variables, such as latitude or longitude, did not provide additional explanatory power. This suggests that the variables already included in the models effectively represented the eco-regions across which our data were distributed. The models produced new insights into the relative importance of chemical and geomorphological factors for river macroinvertebrate communities. The SEM technique proved a powerful tool for exploring complex biological-chemical-geomorphological networks, for example able to deal with the co-correlations that are common in rivers due to multiple feedback mechanisms.

Research Priorities for Fertility and Conception Research as Identified by Multidisciplinary Health Care Practitioners and Researchers.

PubMed

Moran, Lisa J; Spencer, Laura; Russell, Darryl L; Hull, Mary Louise; Robertson, Sarah A; Varcoe, Tamara J; Davies, Michael J; Brown, Hannah M; Rodgers, Raymond J

2016-01-13

The Robinson Research Institute of the University of Adelaide convened a multidisciplinary group of n = 33 clinicians, researchers and representatives of government organisations on the 2 October 2014 for a workshop entitled "Promoting fertility and healthy conception. How do we generate greater reproductive health awareness?" The key aim of the workshop was to assess the body of knowledge that informs clinical practice and government policy, and to identify questions and additional information needed by health practitioners and government representatives working in the field of reproductive health and to frame future research and policy. The workshop identified topics that fell mostly into three categories: lifestyle-related, societal and biological factors. The lifestyle topics included nutrition and diet, exercise, obesity, shift work and other factors deemed to be modifiable at the level of the individual. The societal topics included discussions of matters that are structural, and resistant to change by individuals, including specific ethical issues, social disadvantage, government and educational policies. The biological factors are intrinsic physical states of the individual, and included many factors where there is a dense body of scientific knowledge which may not be readily accessible in less academic language. This workshop thus provided an opportunity to identify further actions that could be undertaken to meet the needs of diverse organisations and groups of professionals with an interest in human fertility. Since so many factors in our social and biological environment can impact fertility and preconception health, it is imperative to involve many disciplines or levels of government or societal organisations that have not traditionally been involved in this area.

Use artificial neural network to align biological ontologies.

PubMed

Huang, Jingshan; Dang, Jiangbo; Huhns, Michael N; Zheng, W Jim

2008-09-16

Being formal, declarative knowledge representation models, ontologies help to address the problem of imprecise terminologies in biological and biomedical research. However, ontologies constructed under the auspices of the Open Biomedical Ontologies (OBO) group have exhibited a great deal of variety, because different parties can design ontologies according to their own conceptual views of the world. It is therefore becoming critical to align ontologies from different parties. During automated/semi-automated alignment across biological ontologies, different semantic aspects, i.e., concept name, concept properties, and concept relationships, contribute in different degrees to alignment results. Therefore, a vector of weights must be assigned to these semantic aspects. It is not trivial to determine what those weights should be, and current methodologies depend a lot on human heuristics. In this paper, we take an artificial neural network approach to learn and adjust these weights, and thereby support a new ontology alignment algorithm, customized for biological ontologies, with the purpose of avoiding some disadvantages in both rule-based and learning-based aligning algorithms. This approach has been evaluated by aligning two real-world biological ontologies, whose features include huge file size, very few instances, concept names in numerical strings, and others. The promising experiment results verify our proposed hypothesis, i.e., three weights for semantic aspects learned from a subset of concepts are representative of all concepts in the same ontology. Therefore, our method represents a large leap forward towards automating biological ontology alignment.

Sex Differences in General Knowledge: Meta-Analysis and New Data on the Contribution of School-Related Moderators among High-School Students

PubMed Central

Tran, Ulrich S.; Hofer, Agnes A.; Voracek, Martin

2014-01-01

Research from various countries consistently reported an advantage of boys over girls in general knowledge and was also suggestive of some overall trends regarding specific domains of general knowledge that were speculated to stem from biologically differentiated interests. However, results were heterogeneous and, as of yet, had not been evaluated meta-analytically. Moreover, previous research drew on overly homogeneous high-school or undergraduate samples whose representativeness appears problematic; mostly, likely moderators, such as school type, student age or parental education, were also not directly investigated or controlled for. We provide a meta-analytical aggregation of available results regarding sex differences in general knowledge and present new data, investigating the psychometric properties of the General Knowledge Test (GKT), on which previous research primarily relied, and explored sex differences in a large and heterogeneous Austrian high-school student sample (N = 1088). The aggregated sex effect in general knowledge was of medium size in previous research, but differences in specific domains were heterogeneous across countries and only modest at best. Large sex differences in our data could be explained to a large part by school-related moderators (school type, school, student age, parental education) and selection processes. Boys had a remaining advantage over girls that was only small in size and that was consistent with the magnitude of sex differences in general intelligence. Analysis of the GKT yielded no evidence of biologically differentiated interests, but of a specific interest in the humanities among girls. In conclusion, previous research likely overestimated sex differences in general knowledge. PMID:25347190

Sex differences in general knowledge: meta-analysis and new data on the contribution of school-related moderators among high-school students.

PubMed

Tran, Ulrich S; Hofer, Agnes A; Voracek, Martin

2014-01-01

Research from various countries consistently reported an advantage of boys over girls in general knowledge and was also suggestive of some overall trends regarding specific domains of general knowledge that were speculated to stem from biologically differentiated interests. However, results were heterogeneous and, as of yet, had not been evaluated meta-analytically. Moreover, previous research drew on overly homogeneous high-school or undergraduate samples whose representativeness appears problematic; mostly, likely moderators, such as school type, student age or parental education, were also not directly investigated or controlled for. We provide a meta-analytical aggregation of available results regarding sex differences in general knowledge and present new data, investigating the psychometric properties of the General Knowledge Test (GKT), on which previous research primarily relied, and explored sex differences in a large and heterogeneous Austrian high-school student sample (N = 1088). The aggregated sex effect in general knowledge was of medium size in previous research, but differences in specific domains were heterogeneous across countries and only modest at best. Large sex differences in our data could be explained to a large part by school-related moderators (school type, school, student age, parental education) and selection processes. Boys had a remaining advantage over girls that was only small in size and that was consistent with the magnitude of sex differences in general intelligence. Analysis of the GKT yielded no evidence of biologically differentiated interests, but of a specific interest in the humanities among girls. In conclusion, previous research likely overestimated sex differences in general knowledge.

What Combined Measurements From Structures and Imaging Tell Us About DNA Damage Responses

PubMed Central

Brosey, Chris A.; Ahmed, Zamal; Lees-Miller, Susan P.; Tainer, John A.

2017-01-01

DNA damage outcomes depend upon the efficiency and fidelity of DNA damage responses (DDRs) for different cells and damage. As such, DDRs represent tightly regulated prototypical systems for linking nanoscale biomolecular structure and assembly to the biology of genomic regulation and cell signaling. However, the dynamic and multifunctional nature of DDR assemblies can render elusive the correlation between the structures of DDR factors and specific biological disruptions to the DDR when these structures are altered. In this chapter, we discuss concepts and strategies for combining structural, biophysical, and imaging techniques to investigate DDR recognition and regulation, and thus bridge sequence-level structural biochemistry to quantitative biological outcomes visualized in cells. We focus on representative DDR responses from PARP/PARG/AIF damage signaling in DNA single-strand break repair and nonhomologous end joining complexes in double-strand break repair. Methods with exemplary experimental results are considered with a focus on strategies for probing flexibility, conformational changes, and assembly processes that shape a predictive understanding of DDR mechanisms in a cellular context. Integration of structural and imaging measurements promises to provide foundational knowledge to rationally control and optimize DNA damage outcomes for synthetic lethality and for immune activation with resulting insights for biology and cancer interventions. PMID:28668129

Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online

PubMed Central

Forsberg, Erica M; Huan, Tao; Rinehart, Duane; Benton, H Paul; Warth, Benedikt; Hilmers, Brian; Siuzdak, Gary

2018-01-01

Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LCLC)–mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5–10 min, depending on user experience; data processing typically takes 1–3 h, and data analysis takes ~30 min. PMID:29494574

Discrete Logic Modelling Optimization to Contextualize Prior Knowledge Networks Using PRUNET

PubMed Central

Androsova, Ganna; del Sol, Antonio

2015-01-01

High-throughput technologies have led to the generation of an increasing amount of data in different areas of biology. Datasets capturing the cell’s response to its intra- and extra-cellular microenvironment allows such data to be incorporated as signed and directed graphs or influence networks. These prior knowledge networks (PKNs) represent our current knowledge of the causality of cellular signal transduction. New signalling data is often examined and interpreted in conjunction with PKNs. However, different biological contexts, such as cell type or disease states, may have distinct variants of signalling pathways, resulting in the misinterpretation of new data. The identification of inconsistencies between measured data and signalling topologies, as well as the training of PKNs using context specific datasets (PKN contextualization), are necessary conditions to construct reliable, predictive models, which are current challenges in the systems biology of cell signalling. Here we present PRUNET, a user-friendly software tool designed to address the contextualization of a PKNs to specific experimental conditions. As the input, the algorithm takes a PKN and the expression profile of two given stable steady states or cellular phenotypes. The PKN is iteratively pruned using an evolutionary algorithm to perform an optimization process. This optimization rests in a match between predicted attractors in a discrete logic model (Boolean) and a Booleanized representation of the phenotypes, within a population of alternative subnetworks that evolves iteratively. We validated the algorithm applying PRUNET to four biological examples and using the resulting contextualized networks to predict missing expression values and to simulate well-characterized perturbations. PRUNET constitutes a tool for the automatic curation of a PKN to make it suitable for describing biological processes under particular experimental conditions. The general applicability of the implemented algorithm makes PRUNET suitable for a variety of biological processes, for instance cellular reprogramming or transitions between healthy and disease states. PMID:26058016

Synthetic biology between technoscience and thing knowledge.

PubMed

Gelfert, Axel

2013-06-01

Synthetic biology presents a challenge to traditional accounts of biology: Whereas traditional biology emphasizes the evolvability, variability, and heterogeneity of living organisms, synthetic biology envisions a future of homogeneous, humanly engineered biological systems that may be combined in modular fashion. The present paper approaches this challenge from the perspective of the epistemology of technoscience. In particular, it is argued that synthetic-biological artifacts lend themselves to an analysis in terms of what has been called 'thing knowledge'. As such, they should neither be regarded as the simple outcome of applying theoretical knowledge and engineering principles to specific technological problems, nor should they be treated as mere sources of new evidence in the general pursuit of scientific understanding. Instead, synthetic-biological artifacts should be viewed as partly autonomous research objects which, qua their material-biological constitution, embody knowledge about the natural world-knowledge that, in turn, can be accessed via continuous experimental interrogation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mapping of courses on vector biology and vector-borne diseases systems: time for a worldwide effort.

PubMed

Casas, Jérôme; Lazzari, Claudio; Insausti, Teresita; Launois, Pascal; Fouque, Florence

2016-11-01

Major emergency efforts are being mounted for each vector-borne disease epidemiological crisis anew, while knowledge about the biology of arthropods vectors is dwindling slowly but continuously, as is the number of field entomologists. The discrepancy between the rates of production of knowledge and its use and need for solving crises is widening, in particular due to the highly differing time spans of the two concurrent processes. A worldwide web based search using multiple key words and search engines of onsite and online courses in English, Spanish, Portuguese, French, Italian and German concerned with the biology of vectors identified over 140 courses. They are geographically and thematically scattered, the vast majority of them are on-site, with very few courses using the latest massive open online course (MOOC) powerfulness. Over two third of them is given in English and Western Africa is particularity poorly represented. The taxonomic groups covered are highly unbalanced towards mosquitoes. A worldwide unique portal to guide students of all grades and levels of expertise, in particular those in remote locations, is badly needed. This is the objective a new activity supported by the Special Programme for Research and Training in Tropical Diseases (TDR).

A computational platform to maintain and migrate manual functional annotations for BioCyc databases.

PubMed

Walsh, Jesse R; Sen, Taner Z; Dickerson, Julie A

2014-10-12

BioCyc databases are an important resource for information on biological pathways and genomic data. Such databases represent the accumulation of biological data, some of which has been manually curated from literature. An essential feature of these databases is the continuing data integration as new knowledge is discovered. As functional annotations are improved, scalable methods are needed for curators to manage annotations without detailed knowledge of the specific design of the BioCyc database. We have developed CycTools, a software tool which allows curators to maintain functional annotations in a model organism database. This tool builds on existing software to improve and simplify annotation data imports of user provided data into BioCyc databases. Additionally, CycTools automatically resolves synonyms and alternate identifiers contained within the database into the appropriate internal identifiers. Automating steps in the manual data entry process can improve curation efforts for major biological databases. The functionality of CycTools is demonstrated by transferring GO term annotations from MaizeCyc to matching proteins in CornCyc, both maize metabolic pathway databases available at MaizeGDB, and by creating strain specific databases for metabolic engineering.

Mapping of courses on vector biology and vector-borne diseases systems: time for a worldwide effort

PubMed Central

Casas, Jérôme; Lazzari, Claudio; Insausti, Teresita; Launois, Pascal; Fouque, Florence

2016-01-01

Major emergency efforts are being mounted for each vector-borne disease epidemiological crisis anew, while knowledge about the biology of arthropods vectors is dwindling slowly but continuously, as is the number of field entomologists. The discrepancy between the rates of production of knowledge and its use and need for solving crises is widening, in particular due to the highly differing time spans of the two concurrent processes. A worldwide web based search using multiple key words and search engines of onsite and online courses in English, Spanish, Portuguese, French, Italian and German concerned with the biology of vectors identified over 140 courses. They are geographically and thematically scattered, the vast majority of them are on-site, with very few courses using the latest massive open online course (MOOC) powerfulness. Over two third of them is given in English and Western Africa is particularity poorly represented. The taxonomic groups covered are highly unbalanced towards mosquitoes. A worldwide unique portal to guide students of all grades and levels of expertise, in particular those in remote locations, is badly needed. This is the objective a new activity supported by the Special Programme for Research and Training in Tropical Diseases (TDR). PMID:27759770

Systematic technology transfer from biology to engineering.

PubMed

Vincent, Julian F V; Mann, Darrell L

2002-02-15

Solutions to problems move only very slowly between different disciplines. Transfer can be greatly speeded up with suitable abstraction and classification of problems. Russian researchers working on the TRIZ (Teoriya Resheniya Izobretatelskikh Zadatch) method for inventive problem solving have identified systematic means of transferring knowledge between different scientific and engineering disciplines. With over 1500 person years of effort behind it, TRIZ represents the biggest study of human creativity ever conducted, whose aim has been to establish a system into which all known solutions can be placed, classified in terms of function. At present, the functional classification structure covers nearly 3 000 000 of the world's successful patents and large proportions of the known physical, chemical and mathematical knowledge-base. Additional tools are the identification of factors which prevent the attainment of new technology, leading directly to a system of inventive principles which will resolve the impasse, a series of evolutionary trends of development, and to a system of methods for effecting change in a system (Su-fields). As yet, the database contains little biological knowledge despite early recognition by the instigator of TRIZ (Genrich Altshuller) that one day it should. This is illustrated by natural systems evolved for thermal stability and the maintenance of cleanliness.

Knowledge representation in metabolic pathway databases.

PubMed

Stobbe, Miranda D; Jansen, Gerbert A; Moerland, Perry D; van Kampen, Antoine H C

2014-05-01

The accurate representation of all aspects of a metabolic network in a structured format, such that it can be used for a wide variety of computational analyses, is a challenge faced by a growing number of researchers. Analysis of five major metabolic pathway databases reveals that each database has made widely different choices to address this challenge, including how to deal with knowledge that is uncertain or missing. In concise overviews, we show how concepts such as compartments, enzymatic complexes and the direction of reactions are represented in each database. Importantly, also concepts which a database does not represent are described. Which aspects of the metabolic network need to be available in a structured format and to what detail differs per application. For example, for in silico phenotype prediction, a detailed representation of gene-protein-reaction relations and the compartmentalization of the network is essential. Our analysis also shows that current databases are still limited in capturing all details of the biology of the metabolic network, further illustrated with a detailed analysis of three metabolic processes. Finally, we conclude that the conceptual differences between the databases, which make knowledge exchange and integration a challenge, have not been resolved, so far, by the exchange formats in which knowledge representation is standardized.

THE ADVERSE OUTCOME PATHWAY (AOP) FRAMEWORK ...

EPA Pesticide Factsheets

An Adverse Outcome Pathway (AOP) represents the organization of current and newly acquired knowledge of biological pathways. These pathways contain a series of nodes (Key Events, KEs) that when sufficiently altered influence the next node on the pathway, beginning from an Molecular Initiating Event (MIE), through intermediate KEs, ending in an Adverse Outcome (AO) which may be used as a basis for decision making. A KE is a measurable biological change, and is linked with other KEs via Key Event Relationships (KERs). A given KE may be involved in several AOPs, leading to a plausible network of biological changes that are involved in an organism’s response to an external stressor. When describing an AOP, five guiding principles have been proposed [1]: 1) an AOP is not specific to a single external stressor, 2) AOPs are modular, with KEs and KERs that can be used in several AOPs, 3) a single AOP is the unit of development, 4) most biological responses will be the result of networks of AOPs, and 5) AOPs will be modified as more biological knowledge becomes available. The collaborative development of AOPs is recommended to be performed using the AOP-Wiki (https://aopwiki.org), which is an effort between the European Commission – DG Joint Research Centre (JRC) and U.S. Environmental Protection Agency (EPA). The Wiki is one part of a larger OECD-sponsored AOP Knowledgebase effort, which is a repository for all AOPs developed as part of the Organization for Economic

Effects of Biology Teachers' Professional Knowledge and Cognitive Activation on Students' Achievement

ERIC Educational Resources Information Center

Förtsch, Christian; Werner, Sonja; von Kotzebue, Lena; Neuhaus, Birgit J.

2016-01-01

This study examined the effects of teachers' biology-specific dimensions of professional knowledge--pedagogical content knowledge (PCK) and content knowledge (CK)--and cognitively activating biology instruction, as a feature of instructional quality, on students' learning. The sample comprised 39 German secondary school teachers whose lessons on…

EvoluCode: Evolutionary Barcodes as a Unifying Framework for Multilevel Evolutionary Data.

PubMed

Linard, Benjamin; Nguyen, Ngoc Hoan; Prosdocimi, Francisco; Poch, Olivier; Thompson, Julie D

2012-01-01

Evolutionary systems biology aims to uncover the general trends and principles governing the evolution of biological networks. An essential part of this process is the reconstruction and analysis of the evolutionary histories of these complex, dynamic networks. Unfortunately, the methodologies for representing and exploiting such complex evolutionary histories in large scale studies are currently limited. Here, we propose a new formalism, called EvoluCode (Evolutionary barCode), which allows the integration of different evolutionary parameters (eg, sequence conservation, orthology, synteny …) in a unifying format and facilitates the multilevel analysis and visualization of complex evolutionary histories at the genome scale. The advantages of the approach are demonstrated by constructing barcodes representing the evolution of the complete human proteome. Two large-scale studies are then described: (i) the mapping and visualization of the barcodes on the human chromosomes and (ii) automatic clustering of the barcodes to highlight protein subsets sharing similar evolutionary histories and their functional analysis. The methodologies developed here open the way to the efficient application of other data mining and knowledge extraction techniques in evolutionary systems biology studies. A database containing all EvoluCode data is available at: http://lbgi.igbmc.fr/barcodes.

From Network Analysis to Functional Metabolic Modeling of the Human Gut Microbiota.

PubMed

Bauer, Eugen; Thiele, Ines

2018-01-01

An important hallmark of the human gut microbiota is its species diversity and complexity. Various diseases have been associated with a decreased diversity leading to reduced metabolic functionalities. Common approaches to investigate the human microbiota include high-throughput sequencing with subsequent correlative analyses. However, to understand the ecology of the human gut microbiota and consequently design novel treatments for diseases, it is important to represent the different interactions between microbes with their associated metabolites. Computational systems biology approaches can give further mechanistic insights by constructing data- or knowledge-driven networks that represent microbe interactions. In this minireview, we will discuss current approaches in systems biology to analyze the human gut microbiota, with a particular focus on constraint-based modeling. We will discuss various community modeling techniques with their advantages and differences, as well as their application to predict the metabolic mechanisms of intestinal microbial communities. Finally, we will discuss future perspectives and current challenges of simulating realistic and comprehensive models of the human gut microbiota.

Between Two Fern Genomes

PubMed Central

2014-01-01

Ferns are the only major lineage of vascular plants not represented by a sequenced nuclear genome. This lack of genome sequence information significantly impedes our ability to understand and reconstruct genome evolution not only in ferns, but across all land plants. Azolla and Ceratopteris are ideal and complementary candidates to be the first ferns to have their nuclear genomes sequenced. They differ dramatically in genome size, life history, and habit, and thus represent the immense diversity of extant ferns. Together, this pair of genomes will facilitate myriad large-scale comparative analyses across ferns and all land plants. Here we review the unique biological characteristics of ferns and describe a number of outstanding questions in plant biology that will benefit from the addition of ferns to the set of taxa with sequenced nuclear genomes. We explain why the fern clade is pivotal for understanding genome evolution across land plants, and we provide a rationale for how knowledge of fern genomes will enable progress in research beyond the ferns themselves. PMID:25324969

Formalizing Knowledge in Multi-Scale Agent-Based Simulations

PubMed Central

Somogyi, Endre; Sluka, James P.; Glazier, James A.

2017-01-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused. PMID:29338063

Formalizing Knowledge in Multi-Scale Agent-Based Simulations.

PubMed

Somogyi, Endre; Sluka, James P; Glazier, James A

2016-10-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.

Consensus and conflict cards for metabolic pathway databases

PubMed Central

2013-01-01

Background The metabolic network of H. sapiens and many other organisms is described in multiple pathway databases. The level of agreement between these descriptions, however, has proven to be low. We can use these different descriptions to our advantage by identifying conflicting information and combining their knowledge into a single, more accurate, and more complete description. This task is, however, far from trivial. Results We introduce the concept of Consensus and Conflict Cards (C2Cards) to provide concise overviews of what the databases do or do not agree on. Each card is centered at a single gene, EC number or reaction. These three complementary perspectives make it possible to distinguish disagreements on the underlying biology of a metabolic process from differences that can be explained by different decisions on how and in what detail to represent knowledge. As a proof-of-concept, we implemented C2CardsHuman, as a web application http://www.molgenis.org/c2cards, covering five human pathway databases. Conclusions C2Cards can contribute to ongoing reconciliation efforts by simplifying the identification of consensus and conflicts between pathway databases and lowering the threshold for experts to contribute. Several case studies illustrate the potential of the C2Cards in identifying disagreements on the underlying biology of a metabolic process. The overviews may also point out controversial biological knowledge that should be subject of further research. Finally, the examples provided emphasize the importance of manual curation and the need for a broad community involvement. PMID:23803311

Consensus and conflict cards for metabolic pathway databases.

PubMed

Stobbe, Miranda D; Swertz, Morris A; Thiele, Ines; Rengaw, Trebor; van Kampen, Antoine H C; Moerland, Perry D

2013-06-26

The metabolic network of H. sapiens and many other organisms is described in multiple pathway databases. The level of agreement between these descriptions, however, has proven to be low. We can use these different descriptions to our advantage by identifying conflicting information and combining their knowledge into a single, more accurate, and more complete description. This task is, however, far from trivial. We introduce the concept of Consensus and Conflict Cards (C₂Cards) to provide concise overviews of what the databases do or do not agree on. Each card is centered at a single gene, EC number or reaction. These three complementary perspectives make it possible to distinguish disagreements on the underlying biology of a metabolic process from differences that can be explained by different decisions on how and in what detail to represent knowledge. As a proof-of-concept, we implemented C₂Cards(Human), as a web application http://www.molgenis.org/c2cards, covering five human pathway databases. C₂Cards can contribute to ongoing reconciliation efforts by simplifying the identification of consensus and conflicts between pathway databases and lowering the threshold for experts to contribute. Several case studies illustrate the potential of the C₂Cards in identifying disagreements on the underlying biology of a metabolic process. The overviews may also point out controversial biological knowledge that should be subject of further research. Finally, the examples provided emphasize the importance of manual curation and the need for a broad community involvement.

Knowledge Transfer in Biology and Translation across External Representations: Experts' Views and Challenges for Learning

ERIC Educational Resources Information Center

Schonborn, Konrad J.; Bogeholz, Susanne

2009-01-01

Recent curriculum reform promotes core competencies such as desired "content knowledge" and "communication" for meaningful learning in biology. Understanding in biology is demonstrated when pupils can apply acquired knowledge to new tasks. This process requires the transfer of knowledge and the subordinate process of translation across external…

How well are you teaching one of the most important biological concepts for humankind? A call to action

USGS Publications Warehouse

Bonar, Scott A.; Fife, Deanna A.; Bonar, John S.

2016-01-01

We represent several generations of biology educators – with teaching experiences beginning in the 1940s and continuing to the present, from elementary school to graduate-level programs. We find the vast array of subjects that biology teachers can now cover both thrilling and mind-boggling. Depending on the grade level, units exist that focus on neurobiology, forensics, DNA analysis, biotechnology, marine biology, and a host of other topics.Although science teachers cover a potpourri of advanced topics, we must ask ourselves – no matter our biology-teaching responsibilities – how well we are teaching carrying capacity, one of the most fundamental biological concepts for our society, knowledge of which becomes more important every day. As biology teachers, most of you know that carrying capacity is defined as the maximum population an environment can sustain, given the amounts of food, habitat, and other resources available. Every environment – from your goldfish bowl to the local forest to planet Earth – can only sustain a set number (weight) of a particular species, based on available resources and space. Currently, most science classes teach …

Multi-level and hybrid modelling approaches for systems biology.

PubMed

Bardini, R; Politano, G; Benso, A; Di Carlo, S

2017-01-01

During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

The United States and biological warfare: secrets from the early cold war and Korea.

PubMed

Bruwer, A

2001-01-01

The United States and Biological Warfare is about accusations that the United States resorted to bacteriological warfare at a time of great military stress during the Korean War. In December 1951, the then US Secretary of Defense ordered early readiness for offensive use of biological weapons. Soon afterwards, the North Korean and Chinese armies accused the United States of starting a large-scale biological warfare experiment in Korea. The US State Department denied the accusation. Both parties to the dispute maintain their positions today. The authors spent 20 years researching the accusations in North America, Europe and Japan. They were the first foreigners to be given access to Chinese classified documents. The reader is also introduced to the concept of 'plausible denial', an official US policy which allowed responsible governmental representatives to deny knowledge of certain events. The authors hope that their work will contribute to the understanding of a time when modern war expanded into a new type of violence.

Cellular and Molecular Changes in Orthodontic Tooth Movement

PubMed Central

Zainal Ariffin, Shahrul Hisham; Yamamoto, Zulham; Zainol Abidin, lntan Zarina; Megat Abdul Wahab, Rohaya; Zainal Ariffin, Zaidah

2011-01-01

Tooth movement induced by orthodontic treatment can cause sequential reactions involving the periodontal tissue and alveolar bone, resulting in the release of numerous substances from the dental tissues and surrounding structures. To better understand the biological processes involved in orthodontic treatment, improve treatment, and reduce adverse side effects, several of these substances have been proposed as biomarkers. Potential biological markers can be collected from different tissue samples, and suitable sampling is important to accurately reflect biological processes. This paper covers the tissue changes that are involved during orthodontic tooth movement such as at compression region (involving osteoblasts), tension region (involving osteoclasts), dental root, and pulp tissues. Besides, the involvement of stem cells and their development towards osteoblasts and osteoclasts during orthodontic treatment have also been explained. Several possible biomarkers representing these biological changes during specific phenomenon, that is, bone remodelling (formation and resorption), inflammation, and root resorption have also been proposed. The knowledge of these biomarkers could be used in accelerating orthodontic treatment. PMID:22125437

Systems biology of stored blood cells: can it help to extend the expiration date?

PubMed

Paglia, Giuseppe; Palsson, Bernhard Ø; Sigurjonsson, Olafur E

2012-12-05

With increasingly stringent regulations regarding deferral and elimination of blood donors it will become increasingly important to extend the expiration date of blood components beyond the current allowed storage periods. One reason for the storage time limit for blood components is that platelets and red blood cells develop a condition called storage lesions during their storage in plastic blood containers. Systems biology provides comprehensive bio-chemical descriptions of organisms through quantitative measurements and data integration in mathematical models. The biological knowledge for a target organism can be translated in a mathematical format and used to compute physiological properties. The use of systems biology represents a concrete solution in the study of blood cell storage lesions, and it may open up new avenues towards developing better storage methods and better storage media, thereby extending the storage period of blood components. This article is part of a Special Issue entitled: Integrated omics. Copyright © 2012 Elsevier B.V. All rights reserved.

Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems

PubMed Central

Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K.; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C.; Hoeng, Julia

2015-01-01

With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com PMID:25887162

Effects of Subject-Matter Knowledge in the Teaching of Biology and Physics.

ERIC Educational Resources Information Center

Hashweh, Maher Z.

An analysis of science teacher's knowledge of specific biology and physics topics and the effects of this knowledge on their planning for instruction and on simulated teaching are discussed in this report. Six experienced secondary school teachers participated in the study. Each teacher's knowledge of a biology topic and a physics topic was…

XML-based data model and architecture for a knowledge-based grid-enabled problem-solving environment for high-throughput biological imaging.

PubMed

Ahmed, Wamiq M; Lenz, Dominik; Liu, Jia; Paul Robinson, J; Ghafoor, Arif

2008-03-01

High-throughput biological imaging uses automated imaging devices to collect a large number of microscopic images for analysis of biological systems and validation of scientific hypotheses. Efficient manipulation of these datasets for knowledge discovery requires high-performance computational resources, efficient storage, and automated tools for extracting and sharing such knowledge among different research sites. Newly emerging grid technologies provide powerful means for exploiting the full potential of these imaging techniques. Efficient utilization of grid resources requires the development of knowledge-based tools and services that combine domain knowledge with analysis algorithms. In this paper, we first investigate how grid infrastructure can facilitate high-throughput biological imaging research, and present an architecture for providing knowledge-based grid services for this field. We identify two levels of knowledge-based services. The first level provides tools for extracting spatiotemporal knowledge from image sets and the second level provides high-level knowledge management and reasoning services. We then present cellular imaging markup language, an extensible markup language-based language for modeling of biological images and representation of spatiotemporal knowledge. This scheme can be used for spatiotemporal event composition, matching, and automated knowledge extraction and representation for large biological imaging datasets. We demonstrate the expressive power of this formalism by means of different examples and extensive experimental results.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hartmann, Anja, E-mail: hartmann@ipk-gatersleben.de; Schreiber, Falk; Martin-Luther-University Halle-Wittenberg, Halle

The characterization of biological systems with respect to their behavior and functionality based on versatile biochemical interactions is a major challenge. To understand these complex mechanisms at systems level modeling approaches are investigated. Different modeling formalisms allow metabolic models to be analyzed depending on the question to be solved, the biochemical knowledge and the availability of experimental data. Here, we describe a method for an integrative analysis of the structure and dynamics represented by qualitative and quantitative metabolic models. Using various formalisms, the metabolic model is analyzed from different perspectives. Determined structural and dynamic properties are visualized in the contextmore » of the metabolic model. Interaction techniques allow the exploration and visual analysis thereby leading to a broader understanding of the behavior and functionality of the underlying biological system. The System Biology Metabolic Model Framework (SBM{sup 2} – Framework) implements the developed method and, as an example, is applied for the integrative analysis of the crop plant potato.« less

Programming languages for synthetic biology.

PubMed

Umesh, P; Naveen, F; Rao, Chanchala Uma Maheswara; Nair, Achuthsankar S

2010-12-01

In the backdrop of accelerated efforts for creating synthetic organisms, the nature and scope of an ideal programming language for scripting synthetic organism in-silico has been receiving increasing attention. A few programming languages for synthetic biology capable of defining, constructing, networking, editing and delivering genome scale models of cellular processes have been recently attempted. All these represent important points in a spectrum of possibilities. This paper introduces Kera, a state of the art programming language for synthetic biology which is arguably ahead of similar languages or tools such as GEC, Antimony and GenoCAD. Kera is a full-fledged object oriented programming language which is tempered by biopart rule library named Samhita which captures the knowledge regarding the interaction of genome components and catalytic molecules. Prominent feature of the language are demonstrated through a toy example and the road map for the future development of Kera is also presented.

Creative design inspired by biological knowledge: Technologies and methods

NASA Astrophysics Data System (ADS)

Tan, Runhua; Liu, Wei; Cao, Guozhong; Shi, Yuan

2018-05-01

Biological knowledge is becoming an important source of inspiration for developing creative solutions to engineering design problems and even has a huge potential in formulating ideas that can help firms compete successfully in a dynamic market. To identify the technologies and methods that can facilitate the development of biologically inspired creative designs, this research briefly reviews the existing biological-knowledge-based theories and methods and examines the application of biological-knowledge-inspired designs in various fields. Afterward, this research thoroughly examines the four dimensions of key technologies that underlie the biologically inspired design (BID) process. This research then discusses the future development trends of the BID process before presenting the conclusions.

Discovery and Enumeration of Organic-Chemical and Biomimetic Reaction Cycles within the Network of Chemistry.

PubMed

Bajczyk, Michał D; Dittwald, Piotr; Wołos, Agnieszka; Szymkuć, Sara; Grzybowski, Bartosz A

2018-02-23

Analysis of the chemical-organic knowledge represented as a giant network reveals that it contains millions of reaction sequences closing into cycles. Without realizing it, independent chemists working at different times have jointly created examples of cyclic sequences that allow for the recovery of useful reagents and for the autoamplification of synthetically important molecules, those that mimic biological cycles, and those that can be operated one-pot. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

The microbiology of malting and brewing.

PubMed

Bokulich, Nicholas A; Bamforth, Charles W

2013-06-01

Brewing beer involves microbial activity at every stage, from raw material production and malting to stability in the package. Most of these activities are desirable, as beer is the result of a traditional food fermentation, but others represent threats to the quality of the final product and must be controlled actively through careful management, the daily task of maltsters and brewers globally. This review collates current knowledge relevant to the biology of brewing yeast, fermentation management, and the microbial ecology of beer and brewing.

The Microbiology of Malting and Brewing

PubMed Central

Bokulich, Nicholas A.

2013-01-01

SUMMARY Brewing beer involves microbial activity at every stage, from raw material production and malting to stability in the package. Most of these activities are desirable, as beer is the result of a traditional food fermentation, but others represent threats to the quality of the final product and must be controlled actively through careful management, the daily task of maltsters and brewers globally. This review collates current knowledge relevant to the biology of brewing yeast, fermentation management, and the microbial ecology of beer and brewing. PMID:23699253

ADO: a disease ontology representing the domain knowledge specific to Alzheimer's disease.

PubMed

Malhotra, Ashutosh; Younesi, Erfan; Gündel, Michaela; Müller, Bernd; Heneka, Michael T; Hofmann-Apitius, Martin

2014-03-01

Biomedical ontologies offer the capability to structure and represent domain-specific knowledge semantically. Disease-specific ontologies can facilitate knowledge exchange across multiple disciplines, and ontology-driven mining approaches can generate great value for modeling disease mechanisms. However, in the case of neurodegenerative diseases such as Alzheimer's disease, there is a lack of formal representation of the relevant knowledge domain. Alzheimer's disease ontology (ADO) is constructed in accordance to the ontology building life cycle. The Protégé OWL editor was used as a tool for building ADO in Ontology Web Language format. ADO was developed with the purpose of containing information relevant to four main biological views-preclinical, clinical, etiological, and molecular/cellular mechanisms-and was enriched by adding synonyms and references. Validation of the lexicalized ontology by means of named entity recognition-based methods showed a satisfactory performance (F score = 72%). In addition to structural and functional evaluation, a clinical expert in the field performed a manual evaluation and curation of ADO. Through integration of ADO into an information retrieval environment, we show that the ontology supports semantic search in scientific text. The usefulness of ADO is authenticated by dedicated use case scenarios. Development of ADO as an open ADO is a first attempt to organize information related to Alzheimer's disease in a formalized, structured manner. We demonstrate that ADO is able to capture both established and scattered knowledge existing in scientific text. Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Molecular Biology In Young Women With Breast Cancer: From Tumor Gene Expression To DNA Mutations.

PubMed

Gómez-Flores-Ramos, Liliana; Castro-Sánchez, Andrea; Peña-Curiel, Omar; Mohar-Betancourt, Alejandro

2017-01-01

Young women with breast cancer (YWBC) represent roughly 15% of breast cancer (BC) cases in Latin America and other developing regions. Breast tumors occurring at an early age are more aggressive and have an overall worse prognosis compared to breast tumors in postmenopausal women. The expression of relevant proliferation biomarkers such as endocrine receptors and human epidermal growth factor receptor 2 appears to be unique in YWBC. Moreover, histopathological, molecular, genetic, and genomic studies have shown that YWBC exhibit a higher frequency of aggressive subtypes, differential tumor gene expression, increased genetic susceptibility, and specific genomic signatures, compared to older women with BC. This article reviews the current knowledge on tumor biology and genomic signatures in YWBC.

Supporting shared hypothesis testing in the biomedical domain.

PubMed

Agibetov, Asan; Jiménez-Ruiz, Ernesto; Ondrésik, Marta; Solimando, Alessandro; Banerjee, Imon; Guerrini, Giovanna; Catalano, Chiara E; Oliveira, Joaquim M; Patanè, Giuseppe; Reis, Rui L; Spagnuolo, Michela

2018-02-08

Pathogenesis of inflammatory diseases can be tracked by studying the causality relationships among the factors contributing to its development. We could, for instance, hypothesize on the connections of the pathogenesis outcomes to the observed conditions. And to prove such causal hypotheses we would need to have the full understanding of the causal relationships, and we would have to provide all the necessary evidences to support our claims. In practice, however, we might not possess all the background knowledge on the causality relationships, and we might be unable to collect all the evidence to prove our hypotheses. In this work we propose a methodology for the translation of biological knowledge on causality relationships of biological processes and their effects on conditions to a computational framework for hypothesis testing. The methodology consists of two main points: hypothesis graph construction from the formalization of the background knowledge on causality relationships, and confidence measurement in a causality hypothesis as a normalized weighted path computation in the hypothesis graph. In this framework, we can simulate collection of evidences and assess confidence in a causality hypothesis by measuring it proportionally to the amount of available knowledge and collected evidences. We evaluate our methodology on a hypothesis graph that represents both contributing factors which may cause cartilage degradation and the factors which might be caused by the cartilage degradation during osteoarthritis. Hypothesis graph construction has proven to be robust to the addition of potentially contradictory information on the simultaneously positive and negative effects. The obtained confidence measures for the specific causality hypotheses have been validated by our domain experts, and, correspond closely to their subjective assessments of confidences in investigated hypotheses. Overall, our methodology for a shared hypothesis testing framework exhibits important properties that researchers will find useful in literature review for their experimental studies, planning and prioritizing evidence collection acquisition procedures, and testing their hypotheses with different depths of knowledge on causal dependencies of biological processes and their effects on the observed conditions.

The Contribution of Ethnobiology to the Construction of a Dialogue Between Ways of Knowing: A Case Study in a Brazilian Public High School

NASA Astrophysics Data System (ADS)

Baptista, Geilsa Costa Santos; El-Hani, Charbel Niño

2009-04-01

This paper reports results obtained in pedagogical interventions in a Brazilian public high school which aimed at promoting a dialogue between scientific and traditional knowledge in the context of biology teaching. The interventions were based on the use of a didactic material and teaching sequence elaborated on the grounds of school knowledge about botany, as presented in biology textbooks, and interviews with students who were also farmers, so as to gather data about their ethnobiological knowledge. Our goal was to develop and test resources that can offer support for teachers who wish to build a dialogue between different ways of knowing in multicultural settings. Our results indicate that the use of the didactic material and teaching sequence indeed created possibilities for a dialogue between the students’ ethnobiological knowledge and biology school knowledge. We observed some shortcomings in classroom practice, partly reflecting our very choice of subject matter to develop the teaching sequence. But the interventions also revealed important limitations that we regard as representative of problems that may generally make multicultural science teaching a hard goal to achieve. It was clear that important shortcomings were related to teachers’ difficulties to conduct a dialogue between ways of knowing in a science classroom, and, thus, called attention to the importance of introducing a multicultural dimension into teacher education. We also observed that the fact that students did not show much sensitivity towards dealing with cultural diversity was a factor constraining the success of the interventions. These results highlight the importance of proposing and testing teacher education initiatives aiming at preparing them to teach science in a culturally sensitive manner, and also managing classroom tensions and conflicts so as to make it possible an effective dialogue between different ways of knowing in a multicultural setting.

SPARK: A Framework for Multi-Scale Agent-Based Biomedical Modeling.

PubMed

Solovyev, Alexey; Mikheev, Maxim; Zhou, Leming; Dutta-Moscato, Joyeeta; Ziraldo, Cordelia; An, Gary; Vodovotz, Yoram; Mi, Qi

2010-01-01

Multi-scale modeling of complex biological systems remains a central challenge in the systems biology community. A method of dynamic knowledge representation known as agent-based modeling enables the study of higher level behavior emerging from discrete events performed by individual components. With the advancement of computer technology, agent-based modeling has emerged as an innovative technique to model the complexities of systems biology. In this work, the authors describe SPARK (Simple Platform for Agent-based Representation of Knowledge), a framework for agent-based modeling specifically designed for systems-level biomedical model development. SPARK is a stand-alone application written in Java. It provides a user-friendly interface, and a simple programming language for developing Agent-Based Models (ABMs). SPARK has the following features specialized for modeling biomedical systems: 1) continuous space that can simulate real physical space; 2) flexible agent size and shape that can represent the relative proportions of various cell types; 3) multiple spaces that can concurrently simulate and visualize multiple scales in biomedical models; 4) a convenient graphical user interface. Existing ABMs of diabetic foot ulcers and acute inflammation were implemented in SPARK. Models of identical complexity were run in both NetLogo and SPARK; the SPARK-based models ran two to three times faster.

Prior knowledge-based approach for associating contaminants with biological effects: A case study in the St. Croix River basin, MN, WI, USA

USGS Publications Warehouse

Schroeder, Anthony L.; Martinovic-Weigelt, Dalma; Ankley, Gerald T.; Lee, Kathy E.; Garcia-Reyero, Natalia; Perkins, Edward J.; Schoenfuss, Heiko L.; Villeneuve, Daniel L.

2017-01-01

Evaluating potential adverse effects of complex chemical mixtures in the environment is challenging. One way to address that challenge is through more integrated analysis of chemical monitoring and biological effects data. In the present study, water samples from five locations near two municipal wastewater treatment plants in the St. Croix River basin, on the border of MN and WI, USA, were analyzed for 127 organic contaminants. Known chemical-gene interactions were used to develop site-specific knowledge assembly models (KAMs) and formulate hypotheses concerning possible biological effects associated with chemicals detected in water samples from each location. Additionally, hepatic gene expression data were collected for fathead minnows (Pimephales promelas) exposed in situ, for 12 d, at each location. Expression data from oligonucleotide microarrays were analyzed to identify functional annotation terms enriched among the differentially-expressed probes. The general nature of many of the terms made hypothesis formulation on the basis of the transcriptome-level response alone difficult. However, integrated analysis of the transcriptome data in the context of the site-specific KAMs allowed for evaluation of the likelihood of specific chemicals contributing to observed biological responses. Thirteen chemicals (atrazine, carbamazepine, metformin, thiabendazole, diazepam, cholesterol, p-cresol, phenytoin, omeprazole, ethyromycin, 17β-estradiol, cimetidine, and estrone), for which there was statistically significant concordance between occurrence at a site and expected biological response as represented in the KAM, were identified. While not definitive, the approach provides a line of evidence for evaluating potential cause-effect relationships between components of a complex mixture of contaminants and biological effects data, which can inform subsequent monitoring and investigation.

Prior knowledge-based approach for associating contaminants with biological effects: A case study in the St. Croix River basin, MN, WI, USA.

PubMed

Schroeder, Anthony L; Martinović-Weigelt, Dalma; Ankley, Gerald T; Lee, Kathy E; Garcia-Reyero, Natalia; Perkins, Edward J; Schoenfuss, Heiko L; Villeneuve, Daniel L

2017-02-01

Evaluating potential adverse effects of complex chemical mixtures in the environment is challenging. One way to address that challenge is through more integrated analysis of chemical monitoring and biological effects data. In the present study, water samples from five locations near two municipal wastewater treatment plants in the St. Croix River basin, on the border of MN and WI, USA, were analyzed for 127 organic contaminants. Known chemical-gene interactions were used to develop site-specific knowledge assembly models (KAMs) and formulate hypotheses concerning possible biological effects associated with chemicals detected in water samples from each location. Additionally, hepatic gene expression data were collected for fathead minnows (Pimephales promelas) exposed in situ, for 12 d, at each location. Expression data from oligonucleotide microarrays were analyzed to identify functional annotation terms enriched among the differentially-expressed probes. The general nature of many of the terms made hypothesis formulation on the basis of the transcriptome-level response alone difficult. However, integrated analysis of the transcriptome data in the context of the site-specific KAMs allowed for evaluation of the likelihood of specific chemicals contributing to observed biological responses. Thirteen chemicals (atrazine, carbamazepine, metformin, thiabendazole, diazepam, cholesterol, p-cresol, phenytoin, omeprazole, ethyromycin, 17β-estradiol, cimetidine, and estrone), for which there was statistically significant concordance between occurrence at a site and expected biological response as represented in the KAM, were identified. While not definitive, the approach provides a line of evidence for evaluating potential cause-effect relationships between components of a complex mixture of contaminants and biological effects data, which can inform subsequent monitoring and investigation. Published by Elsevier Ltd.

The Integration of Javanese Indigenous Knowledge in Biology Learning Resources Development

NASA Astrophysics Data System (ADS)

Anazifa, D.; Hadi, R. F.

2017-02-01

The student’s difficulties in learning and understanding Biology concepts are caused by the adoption of scientific phenomenon that not suitable with the environment they live in. Students who comes from the Javanese background sometimes find the Biology concepts hard to understand. Science content that comes from the West sometimes is not suitable with the student’s background, because the cultural and geographical background that underlining the science development are different. It can potentially cause the clash in constructing knowledge of students. The proportion of western knowledge and indigenous knowledge has to be balanced, in order to give the scientific rationale of the natural phenomenon that faced by students in everyday life. The ethnoscience experienced by student is still in the form of concrete experience as a result of the interaction with the nature. As one of the largest tribe in Indonesia, Javanese has many unique cultures that can be adopted in science classroom especially in Biology class. The role on ethnoscience in the context of developing Biology learning resources is to connect the science concept with the real world situation. By considering indigenous knowledge as one of learning resources, teachers can start to adjust the Javanese indigenous knowledge into the curriculum. This paper is literature review which will present the background, rationale, and procedure in integrating Javanese indigenous knowledge into Biology classroom as learning resources. The integration of Javanese indigenous knowledge in Biology learning resources development is necessary in order to connect the Biology concept into real situation.

Uncommon knowledge of a common phenomenon: intuitions and statistical thinking about gender birth ratio

NASA Astrophysics Data System (ADS)

Peled, Ofra N.; Peled, Irit; Peled, Jonathan U.

2013-01-01

The phenomenon of birth of a baby is a common and familiar one, and yet college students participating in a general biology class did not possess the expected common knowledge of the equal probability of gender births. We found that these students held strikingly skewed conceptions regarding gender birth ratio, estimating the number of female births to be more than twice the number of male births. Possible sources of these beliefs were analysed, showing flaws in statistical thinking such as viewing small unplanned samples as representing the whole population and making inferences from an inappropriate population. Some educational implications are discussed and a short teaching example (using data assembly) demonstrates an instructional direction that might facilitate conceptual change.

Addressing the translational dilemma: dynamic knowledge representation of inflammation using agent-based modeling.

PubMed

An, Gary; Christley, Scott

2012-01-01

Given the panoply of system-level diseases that result from disordered inflammation, such as sepsis, atherosclerosis, cancer, and autoimmune disorders, understanding and characterizing the inflammatory response is a key target of biomedical research. Untangling the complex behavioral configurations associated with a process as ubiquitous as inflammation represents a prototype of the translational dilemma: the ability to translate mechanistic knowledge into effective therapeutics. A critical failure point in the current research environment is a throughput bottleneck at the level of evaluating hypotheses of mechanistic causality; these hypotheses represent the key step toward the application of knowledge for therapy development and design. Addressing the translational dilemma will require utilizing the ever-increasing power of computers and computational modeling to increase the efficiency of the scientific method in the identification and evaluation of hypotheses of mechanistic causality. More specifically, development needs to focus on facilitating the ability of non-computer trained biomedical researchers to utilize and instantiate their knowledge in dynamic computational models. This is termed "dynamic knowledge representation." Agent-based modeling is an object-oriented, discrete-event, rule-based simulation method that is well suited for biomedical dynamic knowledge representation. Agent-based modeling has been used in the study of inflammation at multiple scales. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggest that this modeling framework is well suited for addressing the translational dilemma. This review describes agent-based modeling, gives examples of its applications in the study of inflammation, and introduces a proposed general expansion of the use of modeling and simulation to augment the generation and evaluation of knowledge by the biomedical research community at large.

Knowledge representation and management: transforming textual information into useful knowledge.

PubMed

Rassinoux, A-M

2010-01-01

To summarize current outstanding research in the field of knowledge representation and management. Synopsis of the articles selected for the IMIA Yearbook 2010. Four interesting papers, dealing with structured knowledge, have been selected for the section knowledge representation and management. Combining the newest techniques in computational linguistics and natural language processing with the latest methods in statistical data analysis, machine learning and text mining has proved to be efficient for turning unstructured textual information into meaningful knowledge. Three of the four selected papers for the section knowledge representation and management corroborate this approach and depict various experiments conducted to .extract meaningful knowledge from unstructured free texts such as extracting cancer disease characteristics from pathology reports, or extracting protein-protein interactions from biomedical papers, as well as extracting knowledge for the support of hypothesis generation in molecular biology from the Medline literature. Finally, the last paper addresses the level of formally representing and structuring information within clinical terminologies in order to render such information easily available and shareable among the health informatics community. Delivering common powerful tools able to automatically extract meaningful information from the huge amount of electronically unstructured free texts is an essential step towards promoting sharing and reusability across applications, domains, and institutions thus contributing to building capacities worldwide.

Functional Abstraction as a Method to Discover Knowledge in Gene Ontologies

PubMed Central

Ultsch, Alfred; Lötsch, Jörn

2014-01-01

Computational analyses of functions of gene sets obtained in microarray analyses or by topical database searches are increasingly important in biology. To understand their functions, the sets are usually mapped to Gene Ontology knowledge bases by means of over-representation analysis (ORA). Its result represents the specific knowledge of the functionality of the gene set. However, the specific ontology typically consists of many terms and relationships, hindering the understanding of the ‘main story’. We developed a methodology to identify a comprehensibly small number of GO terms as “headlines” of the specific ontology allowing to understand all central aspects of the roles of the involved genes. The Functional Abstraction method finds a set of headlines that is specific enough to cover all details of a specific ontology and is abstract enough for human comprehension. This method exceeds the classical approaches at ORA abstraction and by focusing on information rather than decorrelation of GO terms, it directly targets human comprehension. Functional abstraction provides, with a maximum of certainty, information value, coverage and conciseness, a representation of the biological functions in a gene set plays a role. This is the necessary means to interpret complex Gene Ontology results thus strengthening the role of functional genomics in biomarker and drug discovery. PMID:24587272

Academic Preparation in Biology and Advocacy for Teaching Evolution: Biology versus Non-Biology Teachers

ERIC Educational Resources Information Center

Nehm, Ross H.; Kim, Sun Young; Sheppard, Keith

2009-01-01

Despite considerable focus on evolution knowledge-belief relationships, little research has targeted populations with strong content backgrounds, such as undergraduate degrees in biology. This study (1) measured precertified biology and non-biology teachers' (n = 167) knowledge of evolution and the nature of science; (2) quantified teacher…

Exploring Biology Teachers' Pedagogical Content Knowledge in the Teaching of Genetics in Swaziland Science Classrooms

ERIC Educational Resources Information Center

Mthethwa-Kunene, Eunice; Onwu, Gilbert Oke; de Villiers, Rian

2015-01-01

This study explored the pedagogical content knowledge (PCK) and its development of four experienced biology teachers in the context of teaching school genetics. PCK was defined in terms of teacher content knowledge, pedagogical knowledge and knowledge of students' preconceptions and learning difficulties. Data sources of teacher knowledge base…

Kernel-PCA data integration with enhanced interpretability

PubMed Central

2014-01-01

Background Nowadays, combining the different sources of information to improve the biological knowledge available is a challenge in bioinformatics. One of the most powerful methods for integrating heterogeneous data types are kernel-based methods. Kernel-based data integration approaches consist of two basic steps: firstly the right kernel is chosen for each data set; secondly the kernels from the different data sources are combined to give a complete representation of the available data for a given statistical task. Results We analyze the integration of data from several sources of information using kernel PCA, from the point of view of reducing dimensionality. Moreover, we improve the interpretability of kernel PCA by adding to the plot the representation of the input variables that belong to any dataset. In particular, for each input variable or linear combination of input variables, we can represent the direction of maximum growth locally, which allows us to identify those samples with higher/lower values of the variables analyzed. Conclusions The integration of different datasets and the simultaneous representation of samples and variables together give us a better understanding of biological knowledge. PMID:25032747

Benefits of using a hybrid problem-based learning curriculum to improve long-term learning acquisition in undergraduate biology education.

PubMed

Carrió, Mar; Agell, Laia; Baños, Josep Eladi; Moyano, Elisabeth; Larramona, Pilar; Pérez, Jorge

2016-08-01

Although problem-based learning (PBL) has been used for over 40 years, with many studies comparing the benefits of PBL versus other educational approaches, little attention has been paid to the effectiveness of hybrid PBL (H-PBL) curricula. Here we aimed to compare the learning outcomes of two groups of undergraduate biology students working towards a bachelor's degree: one group used an H-PBL approach, while the second used a lecture-based learning (LBL) approach. Specifically, the H-PBL group used a PBL module with interdisciplinary problems, which represented 20% of the entire curriculum. The main outcomes of evaluation were the long-term acquisition of factual knowledge and the problem-solving skills at the end of the bachelor's degree. The sample included 85 students, 39 in the H-PBL group and 46 in the LBL group. We found that an H-PBL curriculum can improve the students' learning outcomes such as long-term knowledge acquisition, problem solving skills and generic competences. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Effects of student ontological position on cognition of human origins

NASA Astrophysics Data System (ADS)

Ervin, Jeremy Alan

In this study, the narratives from a hermeneutical dialectic cycle of three high school students were analyzed to understand the influences of ontological position on the learning of human origins. The interpretation of the narratives provides the reader an opportunity to consider the learning process from the perspective of worldview and conceptual change theories. Questions guiding this research include: Within a context of a worldview, what is the range of ontological positions among a high school AP biology class? To what extent does ontological position influence the learning of scientific concepts about human origins? If a student's ontological position is contradictory to scientific explanation of human origins, how will learning strategies and motivations change? All consenting students in an AP biology class were interviewed in order to select three students who represented three different ontological positions of a worldview: No Supernatural, Supernatural Without Impact, or Supernatural Impact. The issue of worldview is addressed at length in this work. Consenting students had completed the graduation requirements in biology, but were taking an additional biology course in preparation for college. Enrollment in an AP biology course was assumed to indicate that the selected students have an understanding of the concept of human origins at a comprehensive level, but not necessarily at an apprehension level, both being needed for conceptual change. Examination of the narratives reveals that students may alternate between two ontological positions in order to account for inconsistencies within a situation. This relativity enables the range of ontological positions to vary depending on concepts being considered. Not all Supernatural Impact positions conflict with biological understanding of human origins due to the ability of some to create a dichotomy between religion and school. Any comprehended concepts within this dichotomy lead to plagiaristic knowledge rather than conceptual change. When conflicts occur, students employ alternate learning strategies for comprehension, but not apprehension, which result in plagiaristic knowledge. These findings suggest that teachers consider the ontological positions of student worldviews because of the potential influence on knowledge construction and conceptual change, especially about topics involving the theory of evolution.

Integrating systems biology models and biomedical ontologies

PubMed Central

2011-01-01

Background Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. Results We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. Conclusions We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms. PMID:21835028

The diverse biological properties of the chemically inert noble gases.

PubMed

Winkler, David A; Thornton, Aaron; Farjot, Géraldine; Katz, Ira

2016-04-01

The noble gases represent an intriguing scientific paradox. They are extremely inert chemically but display a remarkable spectrum of clinically useful biological properties. Despite a relative paucity of knowledge of their mechanisms of action, some of the noble gases have been used successfully in the clinic. Studies with xenon have suggested that the noble gases as a class may exhibit valuable biological properties such as anaesthesia; amelioration of ischemic damage; tissue protection prior to transplantation; analgesic properties; and a potentially wide range of other clinically useful effects. Xenon has been shown to be safe in humans, and has useful pharmacokinetic properties such as rapid onset, fast wash out etc. The main limitations in wider use are that: many of the fundamental biochemical studies are still lacking; the lighter noble gases are likely to manifest their properties only under hyperbaric conditions, impractical in surgery; and administration of xenon using convectional gaseous anaesthesia equipment is inefficient, making its use very expensive. There is nonetheless a significant body of published literature on the biochemical, pharmacological, and clinical properties of noble gases but no comprehensive reviews exist that summarize their properties and the existing knowledge of their models of action at the molecular (atomic) level. This review provides such an up-to-date summary of the extensive, useful biological properties of noble gases as drugs and prospects for wider application of these atoms. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Bioinformatics core competencies for undergraduate life sciences education.

PubMed

Wilson Sayres, Melissa A; Hauser, Charles; Sierk, Michael; Robic, Srebrenka; Rosenwald, Anne G; Smith, Todd M; Triplett, Eric W; Williams, Jason J; Dinsdale, Elizabeth; Morgan, William R; Burnette, James M; Donovan, Samuel S; Drew, Jennifer C; Elgin, Sarah C R; Fowlks, Edison R; Galindo-Gonzalez, Sebastian; Goodman, Anya L; Grandgenett, Nealy F; Goller, Carlos C; Jungck, John R; Newman, Jeffrey D; Pearson, William; Ryder, Elizabeth F; Tosado-Acevedo, Rafael; Tapprich, William; Tobin, Tammy C; Toro-Martínez, Arlín; Welch, Lonnie R; Wright, Robin; Barone, Lindsay; Ebenbach, David; McWilliams, Mindy; Olney, Kimberly C; Pauley, Mark A

2018-01-01

Although bioinformatics is becoming increasingly central to research in the life sciences, bioinformatics skills and knowledge are not well integrated into undergraduate biology education. This curricular gap prevents biology students from harnessing the full potential of their education, limiting their career opportunities and slowing research innovation. To advance the integration of bioinformatics into life sciences education, a framework of core bioinformatics competencies is needed. To that end, we here report the results of a survey of biology faculty in the United States about teaching bioinformatics to undergraduate life scientists. Responses were received from 1,260 faculty representing institutions in all fifty states with a combined capacity to educate hundreds of thousands of students every year. Results indicate strong, widespread agreement that bioinformatics knowledge and skills are critical for undergraduate life scientists as well as considerable agreement about which skills are necessary. Perceptions of the importance of some skills varied with the respondent's degree of training, time since degree earned, and/or the Carnegie Classification of the respondent's institution. To assess which skills are currently being taught, we analyzed syllabi of courses with bioinformatics content submitted by survey respondents. Finally, we used the survey results, the analysis of the syllabi, and our collective research and teaching expertise to develop a set of bioinformatics core competencies for undergraduate biology students. These core competencies are intended to serve as a guide for institutions as they work to integrate bioinformatics into their life sciences curricula.

Bioinformatics core competencies for undergraduate life sciences education

PubMed Central

Wilson Sayres, Melissa A.; Hauser, Charles; Sierk, Michael; Robic, Srebrenka; Rosenwald, Anne G.; Smith, Todd M.; Triplett, Eric W.; Williams, Jason J.; Dinsdale, Elizabeth; Morgan, William R.; Burnette, James M.; Donovan, Samuel S.; Drew, Jennifer C.; Elgin, Sarah C. R.; Fowlks, Edison R.; Galindo-Gonzalez, Sebastian; Goodman, Anya L.; Grandgenett, Nealy F.; Goller, Carlos C.; Jungck, John R.; Newman, Jeffrey D.; Pearson, William; Ryder, Elizabeth F.; Tosado-Acevedo, Rafael; Tapprich, William; Tobin, Tammy C.; Toro-Martínez, Arlín; Welch, Lonnie R.; Wright, Robin; Ebenbach, David; McWilliams, Mindy; Olney, Kimberly C.

2018-01-01

Although bioinformatics is becoming increasingly central to research in the life sciences, bioinformatics skills and knowledge are not well integrated into undergraduate biology education. This curricular gap prevents biology students from harnessing the full potential of their education, limiting their career opportunities and slowing research innovation. To advance the integration of bioinformatics into life sciences education, a framework of core bioinformatics competencies is needed. To that end, we here report the results of a survey of biology faculty in the United States about teaching bioinformatics to undergraduate life scientists. Responses were received from 1,260 faculty representing institutions in all fifty states with a combined capacity to educate hundreds of thousands of students every year. Results indicate strong, widespread agreement that bioinformatics knowledge and skills are critical for undergraduate life scientists as well as considerable agreement about which skills are necessary. Perceptions of the importance of some skills varied with the respondent’s degree of training, time since degree earned, and/or the Carnegie Classification of the respondent’s institution. To assess which skills are currently being taught, we analyzed syllabi of courses with bioinformatics content submitted by survey respondents. Finally, we used the survey results, the analysis of the syllabi, and our collective research and teaching expertise to develop a set of bioinformatics core competencies for undergraduate biology students. These core competencies are intended to serve as a guide for institutions as they work to integrate bioinformatics into their life sciences curricula. PMID:29870542

OWL reasoning framework over big biological knowledge network.

PubMed

Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity.

OWL Reasoning Framework over Big Biological Knowledge Network

PubMed Central

Chen, Huajun; Chen, Xi; Gu, Peiqin; Wu, Zhaohui; Yu, Tong

2014-01-01

Recently, huge amounts of data are generated in the domain of biology. Embedded with domain knowledge from different disciplines, the isolated biological resources are implicitly connected. Thus it has shaped a big network of versatile biological knowledge. Faced with such massive, disparate, and interlinked biological data, providing an efficient way to model, integrate, and analyze the big biological network becomes a challenge. In this paper, we present a general OWL (web ontology language) reasoning framework to study the implicit relationships among biological entities. A comprehensive biological ontology across traditional Chinese medicine (TCM) and western medicine (WM) is used to create a conceptual model for the biological network. Then corresponding biological data is integrated into a biological knowledge network as the data model. Based on the conceptual model and data model, a scalable OWL reasoning method is utilized to infer the potential associations between biological entities from the biological network. In our experiment, we focus on the association discovery between TCM and WM. The derived associations are quite useful for biologists to promote the development of novel drugs and TCM modernization. The experimental results show that the system achieves high efficiency, accuracy, scalability, and effectivity. PMID:24877076

Extracellular vesicles: their role in cancer biology and epithelial-mesenchymal transition.

PubMed

Gopal, Shashi K; Greening, David W; Rai, Alin; Chen, Maoshan; Xu, Rong; Shafiq, Adnan; Mathias, Rommel A; Zhu, Hong-Jian; Simpson, Richard J

2017-01-01

Cell-cell communication is critical across an assortment of physiological and pathological processes. Extracellular vesicles (EVs) represent an integral facet of intercellular communication largely through the transfer of functional cargo such as proteins, messenger RNAs (mRNAs), microRNA (miRNAs), DNAs and lipids. EVs, especially exosomes and shed microvesicles, represent an important delivery medium in the tumour micro-environment through the reciprocal dissemination of signals between cancer and resident stromal cells to facilitate tumorigenesis and metastasis. An important step of the metastatic cascade is the reprogramming of cancer cells from an epithelial to mesenchymal phenotype (epithelial-mesenchymal transition, EMT), which is associated with increased aggressiveness, invasiveness and metastatic potential. There is now increasing evidence demonstrating that EVs released by cells undergoing EMT are reprogrammed (protein and RNA content) during this process. This review summarises current knowledge of EV-mediated functional transfer of proteins and RNA species (mRNA, miRNA, long non-coding RNA) between cells in cancer biology and the EMT process. An in-depth understanding of EVs associated with EMT, with emphasis on molecular composition (proteins and RNA species), will provide fundamental insights into cancer biology. © 2017 The Author(s); published by Portland Press Limited on behalf of the Biochemical Society.

Fostering Students' Conceptual Knowledge in Biology in the Context of German National Education Standards

NASA Astrophysics Data System (ADS)

Förtsch, Christian; Dorfner, Tobias; Baumgartner, Julia; Werner, Sonja; von Kotzebue, Lena; Neuhaus, Birgit J.

2018-04-01

The German National Education Standards (NES) for biology were introduced in 2005. The content part of the NES emphasizes fostering conceptual knowledge. However, there are hardly any indications of what such an instructional implementation could look like. We introduce a theoretical framework of an instructional approach to foster students' conceptual knowledge as demanded in the NES (Fostering Conceptual Knowledge) including instructional practices derived from research on single core ideas, general psychological theories, and biology-specific features of instructional quality. First, we aimed to develop a rating manual, which is based on this theoretical framework. Second, we wanted to describe current German biology instruction according to this approach and to quantitatively analyze its effectiveness. And third, we aimed to provide qualitative examples of this approach to triangulate our findings. In a first step, we developed a theoretically devised rating manual to measure Fostering Conceptual Knowledge in videotaped lessons. Data for quantitative analysis included 81 videotaped biology lessons of 28 biology teachers from different German secondary schools. Six hundred forty students completed a questionnaire on their situational interest after each lesson and an achievement test. Results from multilevel modeling showed significant positive effects of Fostering Conceptual Knowledge on students' achievement and situational interest. For qualitative analysis, we contrasted instruction of four teachers, two with high and two with low student achievement and situational interest using the qualitative method of thematic analysis. Qualitative analysis revealed five main characteristics describing Fostering Conceptual Knowledge. Therefore, implementing Fostering Conceptual Knowledge in biology instruction seems promising. Examples of how to implement Fostering Conceptual Knowledge in instruction are shown and discussed.

Teachers' Journal Club: Bridging between the Dynamics of Biological Discoveries and Biology Teachers

ERIC Educational Resources Information Center

Brill, Gilat; Falk, Hedda; Yarden, Anat

2003-01-01

Since biology is one of the most dynamic research fields within the natural sciences, the gap between the accumulated knowledge in biology and the knowledge that is taught in schools, increases rapidly with time. Our long-term objective is to develop means to bridge between the dynamics of biological discoveries and the biology teachers and…

Do Zoo Visitors Need Zoology Knowledge to Understand Conservation Messages? An Exploration of the Public Understanding of Animal Biology and of the Conservation of Biodiversity in a Zoo Setting

ERIC Educational Resources Information Center

Dove, Tracy; Byrne, Jenny

2014-01-01

This study explores the current knowledge and understanding about animal biology of zoo visitors and investigates whether knowledge of animal biology influences the ability of people to understand how human activity affects biodiversity. Zoos can play a role in the development of scientific literacy in the fields of animal biology and biodiversity…

Causal biological network database: a comprehensive platform of causal biological network models focused on the pulmonary and vascular systems.

PubMed

Boué, Stéphanie; Talikka, Marja; Westra, Jurjen Willem; Hayes, William; Di Fabio, Anselmo; Park, Jennifer; Schlage, Walter K; Sewer, Alain; Fields, Brett; Ansari, Sam; Martin, Florian; Veljkovic, Emilija; Kenney, Renee; Peitsch, Manuel C; Hoeng, Julia

2015-01-01

With the wealth of publications and data available, powerful and transparent computational approaches are required to represent measured data and scientific knowledge in a computable and searchable format. We developed a set of biological network models, scripted in the Biological Expression Language, that reflect causal signaling pathways across a wide range of biological processes, including cell fate, cell stress, cell proliferation, inflammation, tissue repair and angiogenesis in the pulmonary and cardiovascular context. This comprehensive collection of networks is now freely available to the scientific community in a centralized web-based repository, the Causal Biological Network database, which is composed of over 120 manually curated and well annotated biological network models and can be accessed at http://causalbionet.com. The website accesses a MongoDB, which stores all versions of the networks as JSON objects and allows users to search for genes, proteins, biological processes, small molecules and keywords in the network descriptions to retrieve biological networks of interest. The content of the networks can be visualized and browsed. Nodes and edges can be filtered and all supporting evidence for the edges can be browsed and is linked to the original articles in PubMed. Moreover, networks may be downloaded for further visualization and evaluation. Database URL: http://causalbionet.com © The Author(s) 2015. Published by Oxford University Press.

Synthetic biology and the ethics of knowledge

PubMed Central

Douglas, Thomas; Savulescu, Julian

2011-01-01

Synthetic biologists aim to generate biological organisms according to rational design principles. Their work may have many beneficial applications, but it also raises potentially serious ethical concerns. In this article, we consider what attention the discipline demands from bioethicists. We argue that the most important issue for ethicists to examine is the risk that knowledge from synthetic biology will be misused, for example, in biological terrorism or warfare. To adequately address this concern, bioethics will need to broaden its scope, contemplating not just the means by which scientific knowledge is produced, but also what kinds of knowledge should be sought and disseminated. PMID:20935316

Biological knowledge is more tentative than physics knowledge: Taiwan high school adolescents' views about the nature of biology and physics.

PubMed

Tsai, Chin-Chung

2006-01-01

Many educational psychologists believe that students' beliefs about the nature of knowledge, called epistemological beliefs, play an essential role in their learning process. Educators also stress the importance of helping students develop a better understanding of the nature of knowledge. The tentative and creative nature of science is often highlighted by contemporary science educators. However, few previous studies have investigated students' views of more specific knowledge domains, such as biology and physics. Consequently, this study developed a questionnaire to assess students' views specifically about the tentative and creative nature of biology and physics. From a survey of 428 Taiwanese high school adolescents, this study found that although students showed an understanding of the tentative and creative nature of biology and physics, they expressed stronger agreement as to the tentativeness of biology than that of physics. In addition, male students tended to agree more than did females that physics had tentative and creative features and that biology had tentative features. Also, students with more years of science education tended to show more agreement regarding the creative nature of physics and biology than those with fewer years.

The diversity and antibiotic properties of actinobacteria associated with endemic deepwater amphipods of Lake Baikal.

PubMed

Protasov, Eugenii S; Axenov-Gribanov, Denis V; Rebets, Yuriy V; Voytsekhovskaya, Irina V; Tokovenko, Bogdan T; Shatilina, Zhanna M; Luzhetskyy, Andriy N; Timofeyev, Maxim A

2017-12-01

The emergence of pathogenic bacteria resistant to antibiotics increases the need for discovery of new effective antimicrobials. Unique habitats such as marine deposits, wetlands and caves or unexplored biological communities are promising sources for the isolation of actinobacteria, which are among the major antibiotic producers. The present study aimed at examining cultivated actinobacteria strains associated with endemic Lake Baikal deepwater amphipods and estimating their antibiotic activity. We isolated 42 actinobacterial strains from crustaceans belonging to Ommatogammarus albinus and Ommatogammarus flavus. To our knowledge, this is the first report describing the isolation and initial characterization of representatives of Micromonospora and Pseudonocardia genera from Baikal deepwater invertebrates. Also, as expected, representatives of the genus Streptomyces were the dominant group among the isolated species. Some correlations could be observed between the number of actinobacterial isolates, the depth of sampling and the source of the strains. Nevertheless, >70% of isolated strains demonstrated antifungal activity. The dereplication analysis of extract of one of the isolated strains resulted in annotation of several known compounds that can help to explain the observed biological activities. The characteristics of ecological niche and lifestyle of deepwater amphipods suggests that the observed associations between crustaceans and isolated actinobacteria are not random and might represent long-term symbiotic interactions.

Student Perceived and Determined Knowledge of Biology Concepts in an Upper-Level Biology Course

ERIC Educational Resources Information Center

Ziegler, Brittany; Montplaisir, Lisa

2014-01-01

Students who lack metacognitive skills can struggle with the learning process. To be effective learners, students should recognize what they know and what they do not know. This study examines the relationship between students' perception of their knowledge and determined knowledge in an upper-level biology course utilizing a pre/posttest…

Using the Biology Card Sorting Task to Measure Changes in Conceptual Expertise during Postsecondary Biology Education

ERIC Educational Resources Information Center

Bissonnette, Sarah A.; Combs, Elijah D.; Nagami, Paul H.; Byers, Victor; Fernandez, Juliana; Le, Dinh; Realin, Jared; Woodham, Selina; Smith, Julia I.; Tanner, Kimberly D.

2017-01-01

While there have been concerted efforts to reform undergraduate biology toward teaching students to organize their conceptual knowledge like experts, there are few tools that attempt to measure this. We previously developed the Biology Card Sorting Task (BCST), designed to probe how individuals organize their conceptual biological knowledge.…

A Problem-Sorting Task Detects Changes in Undergraduate Biological Expertise over a Single Semester

PubMed Central

Hoskinson, Anne-Marie; Maher, Jessica Middlemis; Bekkering, Cody; Ebert-May, Diane

2017-01-01

Calls for undergraduate biology reform share similar goals: to produce people who can organize, use, connect, and communicate about biological knowledge. Achieving these goals requires students to gain disciplinary expertise. Experts organize, access, and apply disciplinary knowledge differently than novices, and expertise is measurable. By asking introductory biology students to sort biological problems, we investigated whether they changed how they organized and linked biological ideas over one semester of introductory biology. We administered the Biology Card Sorting Task to 751 students enrolled in their first or second introductory biology course focusing on either cellular–molecular or organismal–population topics, under structured or unstructured sorting conditions. Students used a combination of superficial, deep, and yet-uncharacterized ways of organizing and connecting biological knowledge. In some cases, this translated to more expert-like ways of organizing knowledge over a single semester, best predicted by whether students were enrolled in their first or second semester of biology and by the sorting condition completed. In addition to illuminating differences between novices and experts, our results show that card sorting is a robust way of detecting changes in novices’ biological expertise—even in heterogeneous populations of novice biology students over the time span of a single semester. PMID:28408406

Analysis of undergraduate students' conceptual models of a complex biological system across a diverse body of learners

NASA Astrophysics Data System (ADS)

Dirnbeck, Matthew R.

Biological systems pose a challenge both for learners and teachers because they are complex systems mediated by feedback loops; networks of cause-effect relationships; and non-linear, hierarchical, and emergent properties. Teachers and scientists routinely use models to communicate ideas about complex systems. Model-based pedagogies engage students in model construction as a means of practicing higher-order reasoning skills. One such modeling paradigm describes systems in terms of their structures, behaviors, and functions (SBF). The SBF framework is a simple modeling language that has been used to teach about complex biological systems. Here, we used student-generated SBF models to assess students' causal reasoning in the context of a novel biological problem on an exam. We compared students' performance on the modeling problem, their performance on a set of knowledge/comprehension questions, and their performance on a set of scientific reasoning questions. We found that students who performed well on knowledge and understanding questions also constructed more networked, higher quality models. Previous studies have shown that learners' mental maps increase in complexity with increased expertise. We wanted to investigate if biology students with varying levels of training in biology showed a similar pattern when constructing system models. In a pilot study, we administered the same modeling problem to two additional groups of students: 1) an animal physiology course for students pursuing a major in biology (n=37) and 2) an exercise physiology course for non-majors (n=27). We found that there was no significant difference in model organization across the three student populations, but there was a significant difference in the ability to represent function between the three populations. Between the three groups the non-majors had the lowest function scores, the introductory majors had the middle function scores, and the upper division majors had the highest function scores.

A consistent S-Adenosylmethionine force field improved by dynamic Hirshfeld-I atomic charges for biomolecular simulation

NASA Astrophysics Data System (ADS)

Saez, David Adrian; Vöhringer-Martinez, Esteban

2015-10-01

S-Adenosylmethionine (AdoMet) is involved in many biological processes as cofactor in enzymes transferring its sulfonium methyl group to various substrates. Additionally, it is used as drug and nutritional supplement to reduce the pain in osteoarthritis and against depression. Due to the biological relevance of AdoMet it has been part of various computational simulation studies and will also be in the future. However, to our knowledge no rigorous force field parameter development for its simulation in biological systems has been reported. Here, we use electronic structure calculations combined with molecular dynamics simulations in explicit solvent to develop force field parameters compatible with the AMBER99 force field. Additionally, we propose new dynamic Hirshfeld-I atomic charges which are derived from the polarized electron density of AdoMet in aqueous solution to describe its electrostatic interactions in biological systems. The validation of the force field parameters and the atomic charges is performed against experimental interproton NOE distances of AdoMet in aqueous solution and crystal structures of AdoMet in the cavity of three representative proteins.

Microbiological control of soil-borne phytopathogenic fungi with special emphasis on wilt-inducing Fusarium oxysporum.

PubMed

Alabouvette, Claude; Olivain, Chantal; Migheli, Quirico; Steinberg, Christian

2009-11-01

Plant diseases induced by soil-borne plant pathogens are among the most difficult to control. In the absence of effective chemical control methods, there is renewed interest in biological control based on application of populations of antagonistic micro-organisms. In addition to Pseudomonas spp. and Trichoderma spp., which are the two most widely studied groups of biological control agents, the protective strains of Fusarium oxysporum represent an original model. These protective strains of F. oxysporum can be used to control wilt induced by pathogenic strains of the same species. Exploring the mechanisms involved in the protective capability of these strains is not only necessary for their development as commercial biocontrol agents but raises many basic questions related to the determinism of pathogenicity versus biocontrol capacity in the F. oxysporum species complex. In this paper, current knowledge regarding the interaction between the plant and the protective strains is reviewed in comparison with interactions between the plant and pathogenic strains. The success of biological control depends not only on plant-microbial interactions but also on the ecological fitness of the biological control agents.

Parasites, proteomes and systems: has Descartes' clock run out of time?

PubMed

Wastling, J M; Armstrong, S D; Krishna, R; Xia, D

2012-08-01

Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types.

Generation and Biological Activities of Oxidized Phospholipids

PubMed Central

Oskolkova, Olga V.; Birukov, Konstantin G.; Levonen, Anna-Liisa; Binder, Christoph J.; Stöckl, Johannes

2010-01-01

Abstract Glycerophospholipids represent a common class of lipids critically important for integrity of cellular membranes. Oxidation of esterified unsaturated fatty acids dramatically changes biological activities of phospholipids. Apart from impairment of their structural function, oxidation makes oxidized phospholipids (OxPLs) markers of “modified-self” type that are recognized by soluble and cell-associated receptors of innate immunity, including scavenger receptors, natural (germ line-encoded) antibodies, and C-reactive protein, thus directing removal of senescent and apoptotic cells or oxidized lipoproteins. In addition, OxPLs acquire novel biological activities not characteristic of their unoxidized precursors, including the ability to regulate innate and adaptive immune responses. Effects of OxPLs described in vitro and in vivo suggest their potential relevance in different pathologies, including atherosclerosis, acute inflammation, lung injury, and many other conditions. This review summarizes current knowledge on the mechanisms of formation, structures, and biological activities of OxPLs. Furthermore, potential applications of OxPLs as disease biomarkers, as well as experimental therapies targeting OxPLs, are described, providing a broad overview of an emerging class of lipid mediators. Antioxid. Redox Signal. 12, 1009–1059. PMID:19686040

Parasites, proteomes and systems: has Descartes’ clock run out of time?

PubMed Central

WASTLING, J. M.; ARMSTRONG, S. D.; KRISHNA, R.; XIA, D.

2012-01-01

SUMMARY Systems biology aims to integrate multiple biological data types such as genomics, transcriptomics and proteomics across different levels of structure and scale; it represents an emerging paradigm in the scientific process which challenges the reductionism that has dominated biomedical research for hundreds of years. Systems biology will nevertheless only be successful if the technologies on which it is based are able to deliver the required type and quality of data. In this review we discuss how well positioned is proteomics to deliver the data necessary to support meaningful systems modelling in parasite biology. We summarise the current state of identification proteomics in parasites, but argue that a new generation of quantitative proteomics data is now needed to underpin effective systems modelling. We discuss the challenges faced to acquire more complete knowledge of protein post-translational modifications, protein turnover and protein-protein interactions in parasites. Finally we highlight the central role of proteome-informatics in ensuring that proteomics data is readily accessible to the user-community and can be translated and integrated with other relevant data types. PMID:22828391

Transformation of Follicular Lymphoma

PubMed Central

Lossos, Izidore S.; Gascoyne, Randy D.

2011-01-01

Histological transformation of follicular lymphoma (FL) to a more aggressive non-Hodgkin's lymphomas is a pivotal event in the natural history of FL and is associated with poor outcome. While commonly observed in clinical practice and despite multiple studies designed to address its pathogenesis, the biology of this process represents an enigma. In this chapter we present a state of the art review summarizing the definition of histologic transformation, its incidence, pathogenesis, clinical manifestations, treatment and outcome. Furthermore, we specifically emphasize gaps in our knowledge that should be addressed in future studies. PMID:21658615

What language is the language-ready brain ready for?. Comment on "Towards a Computational Comparative Neuroprimatology: Framing the language-ready brain" by Michael A. Arbib

NASA Astrophysics Data System (ADS)

Croft, William

2016-03-01

Arbib's computational comparative neuroprimatology [1] is a welcome model for cognitive linguists, that is, linguists who ground their models of language in human cognition and language use in social interaction. Arbib argues that language emerged via biological and cultural coevolution [1]; linguistic knowledge is represented by constructions, and semantic representations of linguistic constructions are grounded in embodied perceptual-motor schemas (the mirror system hypothesis). My comments offer some refinements from a linguistic point of view.

[Metastasis tumors of the central nervous system: molecular biology].

PubMed

Bello, M Josefa; González-Gómez, P; Rey, J A

2004-12-01

Metastases in the nervous system represent an important and growing problem in the clinical practice, being the cause of a great mortality in the developed countries. This article reviews the few data available on the molecular mechanisms involved in the pathogenesis of these tumours, leading to oncogene activation, inactivation of tumour suppressor genes, not only by the classical mechanisms, but also by the tumour cell epigenetic balance alteration. We conclude that all this knowledge will lead in the future to a better diagnosis, treatment and clinic evolution of these patients.

Can we manage for biological diversity in the absence of science?

USGS Publications Warehouse

Trauger, D.L.; Hall, R.J.

1995-01-01

Conservation of biological diversity is dependent on sound scientific information about underlying ecological processes. Current knowledge of the composition, distribution, abundance and life cycles of most species of plants and animals is incomplete, insufficient, unreliable, or nonexistent. Contemporary managers are also confronted with additional levels of complexity related to varying degrees of knowledge and understanding about interactions of species and ecosystems. Consequently, traditional species-oriented management schemes may have unintended consequences and ecosystem-oriented management initiatives may fail in the face of inadequate or fragmentary information on the structure, function, and dynamics of biotic communities and ecological systems. Nevertheless, resource managers must make decisions and manage based on the best biological information currently available. Adaptive resource management may represent a management paradigm that allows managers to learn something about the species or systems that they are managing while they are managing, but potential pitfalls lurk for such approaches. In addition to lack of control over the primary physical, chemical, and ecological processes, managers also lack control over social, economic, and political parameters affecting resource management options. Moreover, appropriate goals may be difficult to identify and criteria for determining success may be elusive. Some management responsibilities do not lend themselves to adaptive strategies. Finally, the lessons learned from adaptive management are usually obtained from a highly situational context that may limit applicability in a wider range of situations or undermine confidence that problems and solutions were properly diagnosed and addressed. Several scenarios are critically examined where adaptive management approaches may be inappropriate or ineffective and where management for biological diversity may be infeasible or inefficient without a sound scientific basis. Whereas some level of management must exist to meet agency responsibilities, more research is needed to conserve biological diversity.

Using Student Self-Assessment of Biological Concepts in an Introductory Biology Course.

ERIC Educational Resources Information Center

Heinze-Fry, Jane Ann

1992-01-01

Describes the author's methods to establish what students enrolled in an introductory biology course for nonmajors know about biology prior to instruction. The project also compared preinstructional knowledge to postinstructional knowledge. Beginning students knew the least about plant transport/chemical control and cellular metabolism. Students…

An introduction to microbiome analysis for human biology applications.

PubMed

Amato, Katherine R

2017-01-01

Research examining the gut microbiota is currently exploding, and results are providing new perspectives on human biology. Factors such as host diet and physiology influence the composition and function of the gut microbiota, which in turn affects human nutrition, health, and behavior via interactions with metabolism, the immune system, and the brain. These findings represent an exciting new twist on familiar topics, and as a result, gut microbiome research is likely to provide insight into unresolved biological mechanisms driving human health. However, much remains to be learned about the broader ecological and evolutionary contexts within which gut microbes and humans are affecting each other. Here, I outline the procedures for generating data describing the gut microbiota with the goal of facilitating the wider integration of microbiome analyses into studies of human biology. I describe the steps involved in sample collection, DNA extraction, PCR amplification, high-throughput sequencing, and bioinformatics. While this review serves only as an introduction to these topics, it provides sufficient resources for researchers interested in launching new microbiome initiatives. As knowledge of these methods spreads, microbiome analysis should become a standard tool in the arsenal of human biology research. © 2016 Wiley Periodicals, Inc.

Using novel descriptor accounting for ligand-receptor interactions to define and visually explore biologically relevant chemical space.

PubMed

Rabal, Obdulia; Oyarzabal, Julen

2012-05-25

The definition and pragmatic implementation of biologically relevant chemical space is critical in addressing navigation strategies in the overlapping regions where chemistry and therapeutically relevant targets reside and, therefore, also key to performing an efficient drug discovery project. Here, we describe the development and implementation of a simple and robust method for representing biologically relevant chemical space as a general reference according to current knowledge, independently of any reference space, and analyzing chemical structures accordingly. Underlying our method is the generation of a novel descriptor (LiRIf) that converts structural information into a one-dimensional string accounting for the plausible ligand-receptor interactions as well as for topological information. Capitalizing on ligand-receptor interactions as a descriptor enables the clustering, profiling, and comparison of libraries of compounds from a chemical biology and medicinal chemistry perspective. In addition, as a case study, R-groups analysis is performed to identify the most populated ligand-receptor interactions according to different target families (GPCR, kinases, etc.), as well as to evaluate the coverage of biologically relevant chemical space by structures annotated in different databases (ChEMBL, Glida, etc.).

The EvoDevoCI: A Concept Inventory for Gauging Students’ Understanding of Evolutionary Developmental Biology

PubMed Central

Perez, Kathryn E.; Hiatt, Anna; Davis, Gregory K.; Trujillo, Caleb; French, Donald P.; Terry, Mark; Price, Rebecca M.

2013-01-01

The American Association for the Advancement of Science 2011 report Vision and Change in Undergraduate Biology Education encourages the teaching of developmental biology as an important part of teaching evolution. Recently, however, we found that biology majors often lack the developmental knowledge needed to understand evolutionary developmental biology, or “evo-devo.” To assist in efforts to improve evo-devo instruction among undergraduate biology majors, we designed a concept inventory (CI) for evolutionary developmental biology, the EvoDevoCI. The CI measures student understanding of six core evo-devo concepts using four scenarios and 11 multiple-choice items, all inspired by authentic scientific examples. Distracters were designed to represent the common conceptual difficulties students have with each evo-devo concept. The tool was validated by experts and administered at four institutions to 1191 students during preliminary (n = 652) and final (n = 539) field trials. We used student responses to evaluate the readability, difficulty, discriminability, validity, and reliability of the EvoDevoCI, which included items ranging in difficulty from 0.22–0.55 and in discriminability from 0.19–0.38. Such measures suggest the EvoDevoCI is an effective tool for assessing student understanding of evo-devo concepts and the prevalence of associated common conceptual difficulties among both novice and advanced undergraduate biology majors. PMID:24297293

Student Perceived and Determined Knowledge of Biology Concepts in an Upper-Level Biology Course.

PubMed

Ziegler, Brittany; Montplaisir, Lisa

2014-01-01

Students who lack metacognitive skills can struggle with the learning process. To be effective learners, students should recognize what they know and what they do not know. This study examines the relationship between students' perception of their knowledge and determined knowledge in an upper-level biology course utilizing a pre/posttest approach. Significant differences in students' perception of their knowledge and their determined knowledge exist at the beginning (pretest) and end (posttest) of the course. Alignment between student perception and determined knowledge was significantly more accurate on the posttest compared with the pretest. Students whose determined knowledge was in the upper quartile had significantly better alignment between their perception and determined knowledge on the pre- and posttest than students in the lower quartile. No difference exists between how students perceived their knowledge between upper- and lower-quartile students. There was a significant difference in alignment of perception and determined knowledge between males and females on the posttest, with females being more accurate in their perception of knowledge. This study provides evidence of discrepancies that exist between what students perceive they know and what they actually know. © 2014 B. Ziegler and L. Montplaisir. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Creativity, brain, and art: biological and neurological considerations.

PubMed

Zaidel, Dahlia W

2014-01-01

Creativity is commonly thought of as a positive advance for society that transcends the status quo knowledge. Humans display an inordinate capacity for it in a broad range of activities, with art being only one. Most work on creativity's neural substrates measures general creativity, and that is done with laboratory tasks, whereas specific creativity in art is gleaned from acquired brain damage, largely in observing established visual artists, and some in visual de novo artists (became artists after the damage). The verb "to create" has been erroneously equated with creativity; creativity, in the classic sense, does not appear to be enhanced following brain damage, regardless of etiology. The turning to communication through art in lieu of language deficits reflects a biological survival strategy. Creativity in art, and in other domains, is most likely dependent on intact and healthy knowledge and semantic conceptual systems, which are represented in several pathways in the cortex. It is adversely affected when these systems are dysfunctional, for congenital reasons (savant autism) or because of acquired brain damage (stroke, dementia, Parkinson's), whereas inherent artistic talent and skill appear less affected. Clues to the neural substrates of general creativity and specific art creativity can be gleaned from considering that art is produced spontaneously mainly by humans, that there are unique neuroanatomical and neurofunctional organizations in the human brain, and that there are biological antecedents of innovation in animals.

Creativity, brain, and art: biological and neurological considerations

PubMed Central

Zaidel, Dahlia W.

2014-01-01

Creativity is commonly thought of as a positive advance for society that transcends the status quo knowledge. Humans display an inordinate capacity for it in a broad range of activities, with art being only one. Most work on creativity’s neural substrates measures general creativity, and that is done with laboratory tasks, whereas specific creativity in art is gleaned from acquired brain damage, largely in observing established visual artists, and some in visual de novo artists (became artists after the damage). The verb “to create” has been erroneously equated with creativity; creativity, in the classic sense, does not appear to be enhanced following brain damage, regardless of etiology. The turning to communication through art in lieu of language deficits reflects a biological survival strategy. Creativity in art, and in other domains, is most likely dependent on intact and healthy knowledge and semantic conceptual systems, which are represented in several pathways in the cortex. It is adversely affected when these systems are dysfunctional, for congenital reasons (savant autism) or because of acquired brain damage (stroke, dementia, Parkinson’s), whereas inherent artistic talent and skill appear less affected. Clues to the neural substrates of general creativity and specific art creativity can be gleaned from considering that art is produced spontaneously mainly by humans, that there are unique neuroanatomical and neurofunctional organizations in the human brain, and that there are biological antecedents of innovation in animals. PMID:24917807

Using semantics for representing experimental protocols.

PubMed

Giraldo, Olga; García, Alexander; López, Federico; Corcho, Oscar

2017-11-13

An experimental protocol is a sequence of tasks and operations executed to perform experimental research in biological and biomedical areas, e.g. biology, genetics, immunology, neurosciences, virology. Protocols often include references to equipment, reagents, descriptions of critical steps, troubleshooting and tips, as well as any other information that researchers deem important for facilitating the reusability of the protocol. Although experimental protocols are central to reproducibility, the descriptions are often cursory. There is the need for a unified framework with respect to the syntactic structure and the semantics for representing experimental protocols. In this paper we present "SMART Protocols ontology", an ontology for representing experimental protocols. Our ontology represents the protocol as a workflow with domain specific knowledge embedded within a document. We also present the S ample I nstrument R eagent O bjective (SIRO) model, which represents the minimal common information shared across experimental protocols. SIRO was conceived in the same realm as the Patient Intervention Comparison Outcome (PICO) model that supports search, retrieval and classification purposes in evidence based medicine. We evaluate our approach against a set of competency questions modeled as SPARQL queries and processed against a set of published and unpublished protocols modeled with the SP Ontology and the SIRO model. Our approach makes it possible to answer queries such as Which protocols use tumor tissue as a sample. Improving reporting structures for experimental protocols requires collective efforts from authors, peer reviewers, editors and funding bodies. The SP Ontology is a contribution towards this goal. We build upon previous experiences and bringing together the view of researchers managing protocols in their laboratory work. Website: https://smartprotocols.github.io/ .

Basic-education mexican teachers' knowledge of biotechnology and attitudes about the consumption of genetically modified foods.

PubMed

Jiménez-Salas, Zacarías; Campos-Góngora, Eduardo; González-Martínez, Blanca E; Tijerina-Sáenz, Alexandra; Escamilla-Méndez, Angélica D; Ramírez-López, Erik

2017-09-01

Over the past few years, a new research field has emerged, focusing on the social-scientific criteria for the study of opinions toward genetically modified foods (GMFs), since these may be limiting factors for the success or failure of these products. Basic education is the first step in the Mexican education system, and teachers may wield an outsized influence on the attitudes and preferences of children, prospective future consumers of these products. To better understand the current state of knowledge of biotechnology issues and opinions toward the consumption of GMF of Mexican teachers, a questionnaire was distributed, and 362 Mexican teachers of basic education responded. The survey included questions about the benefits and risks of consuming GMF. The mean percentage of teachers expressing knowledge of a given topic in biotechnology was 50%. More than 60% of teachers believed that GMFs would be useful in preventing world hunger, while 39.2% considered GMF to be hazards for future generations. Although 47.0% reported not having enough knowledge about these topics, almost all (90.3%) respondents expressed an interest and willingness to learn about biotechnology. In light of the fact that teachers of basic education represent the first and potentially most lasting stage in the education of young children, this survey establishes the urgent need to develop strategies to improve the scientific knowledge of teachers and to facilitate decision making and the promotion of scientific and technological advances for their students. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(5):396-402, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

The Ontology for Biomedical Investigations.

PubMed

Bandrowski, Anita; Brinkman, Ryan; Brochhausen, Mathias; Brush, Matthew H; Bug, Bill; Chibucos, Marcus C; Clancy, Kevin; Courtot, Mélanie; Derom, Dirk; Dumontier, Michel; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Gibson, Frank; Gonzalez-Beltran, Alejandra; Haendel, Melissa A; He, Yongqun; Heiskanen, Mervi; Hernandez-Boussard, Tina; Jensen, Mark; Lin, Yu; Lister, Allyson L; Lord, Phillip; Malone, James; Manduchi, Elisabetta; McGee, Monnie; Morrison, Norman; Overton, James A; Parkinson, Helen; Peters, Bjoern; Rocca-Serra, Philippe; Ruttenberg, Alan; Sansone, Susanna-Assunta; Scheuermann, Richard H; Schober, Daniel; Smith, Barry; Soldatova, Larisa N; Stoeckert, Christian J; Taylor, Chris F; Torniai, Carlo; Turner, Jessica A; Vita, Randi; Whetzel, Patricia L; Zheng, Jie

2016-01-01

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl.

The Ontology for Biomedical Investigations

PubMed Central

Bandrowski, Anita; Brinkman, Ryan; Brochhausen, Mathias; Brush, Matthew H.; Chibucos, Marcus C.; Clancy, Kevin; Courtot, Mélanie; Derom, Dirk; Dumontier, Michel; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Gibson, Frank; Gonzalez-Beltran, Alejandra; Haendel, Melissa A.; He, Yongqun; Heiskanen, Mervi; Hernandez-Boussard, Tina; Jensen, Mark; Lin, Yu; Lister, Allyson L.; Lord, Phillip; Malone, James; Manduchi, Elisabetta; McGee, Monnie; Morrison, Norman; Overton, James A.; Parkinson, Helen; Peters, Bjoern; Rocca-Serra, Philippe; Ruttenberg, Alan; Sansone, Susanna-Assunta; Scheuermann, Richard H.; Schober, Daniel; Smith, Barry; Soldatova, Larisa N.; Stoeckert, Christian J.; Taylor, Chris F.; Torniai, Carlo; Turner, Jessica A.; Vita, Randi; Whetzel, Patricia L.; Zheng, Jie

2016-01-01

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl. PMID:27128319

Linking sensory biology and fisheries bycatch reduction in elasmobranch fishes: a review with new directions for research

PubMed Central

Jordan, Laura K.; Mandelman, John W.; McComb, D. Michelle; Fordham, Sonja V.; Carlson, John K.; Werner, Timothy B.

2013-01-01

Incidental capture, or bycatch, in fisheries represents a substantial threat to the sustainability of elasmobranch populations worldwide. Consequently, researchers are increasingly investigating elasmobranch bycatch reduction methods, including some focused on these species' sensory capabilities, particularly their electrosensory systems. To guide this research, we review current knowledge of elasmobranch sensory biology and feeding ecology with respect to fishing gear interactions and include examples of bycatch reduction methods used for elasmobranchs as well as other taxonomic groups. We discuss potential elasmobranch bycatch reduction strategies for various fishing gear types based on the morphological, physiological, and behavioural characteristics of species within this diverse group. In select examples, we indicate how an understanding of the physiology and sensory biology of vulnerable, bycatch-prone, non-target elasmobranch species can help in the identification of promising options for bycatch reduction. We encourage collaboration among researchers studying bycatch reduction across taxa to provide better understanding of the broad effects of bycatch reduction methods. PMID:27293586

BioCreative V track 4: a shared task for the extraction of causal network information using the Biological Expression Language.

PubMed

Rinaldi, Fabio; Ellendorff, Tilia Renate; Madan, Sumit; Clematide, Simon; van der Lek, Adrian; Mevissen, Theo; Fluck, Juliane

2016-01-01

Automatic extraction of biological network information is one of the most desired and most complex tasks in biological and medical text mining. Track 4 at BioCreative V attempts to approach this complexity using fragments of large-scale manually curated biological networks, represented in Biological Expression Language (BEL), as training and test data. BEL is an advanced knowledge representation format which has been designed to be both human readable and machine processable. The specific goal of track 4 was to evaluate text mining systems capable of automatically constructing BEL statements from given evidence text, and of retrieving evidence text for given BEL statements. Given the complexity of the task, we designed an evaluation methodology which gives credit to partially correct statements. We identified various levels of information expressed by BEL statements, such as entities, functions, relations, and introduced an evaluation framework which rewards systems capable of delivering useful BEL fragments at each of these levels. The aim of this evaluation method is to help identify the characteristics of the systems which, if combined, would be most useful for achieving the overall goal of automatically constructing causal biological networks from text. © The Author(s) 2016. Published by Oxford University Press.

[Attitudes of adults towards homosexuality and knowledge of sexually transmitted diseases: part one].

PubMed

Tritt, Remigiusz Jarosław

2011-01-01

This doctoral dissertation is the first scientific article in Poland with an in-depth analysis of subjective attitudes of members of various social groups towards persons with a homosexual orientation. The dissertation includes definitions of terms related to homosexuality, as well as changing opinions on gays and lesbians over the centuries from antiquity till modern times. Special attention is devoted to the biological background of human and animal homosexuality. Opinions of various experts are presented and the fate of homosexuals throughout history is discussed together with examples of persecution on one side and growing tolerance on the other. The aim of this study was to (a) investigate the attitudes of adults representing various social groups towards homosexuality; (b) evaluate the knowledge of respondents concerning biological and social aspects of homosexuality; (c) determine the degree of tolerance and acceptance of gays and lesbians. The study was done in 2255 respondents - students of various university faculties, as well as in teachers, servicemen, and cadets of the Military Academy. The study tool was a 24-item anonymous questionnaire. 1. Knowledge of problems relating to homosexuality differed among various social groups. Knowledge was highest among students of cultural studies and teachers. 2. The level of tolerance and acceptance towards homosexuals continues to rise, particularly among students of the humanities. 3. The type and field of studies has an impact on the shaping of attitudes of students towards the homosexually-oriented population. The highest level of acceptance was found among students of cultural studies and philosophy. Students of the military academy and physical education revealed animosity and negative attitudes. 4. Biological factors - gender and environmental factors - parents' social class - have an impact on the shaping of attitudes towards homosexuality. Males and respondents of peasant descent do not accept homosexuality. More positive attitudes are evolving among respondents of worker descent, possibly because of their migration to cities.

Assessment of knowledge of participants on basic molecular biology techniques after 5-day intensive molecular biology training workshops in Nigeria.

PubMed

Yisau, J I; Adagbada, A O; Bamidele, T; Fowora, M; Brai, B I C; Adebesin, O; Bamidele, M; Fesobi, T; Nwaokorie, F O; Ajayi, A; Smith, S I

2017-07-08

The deployment of molecular biology techniques for diagnosis and research in Nigeria is faced with a number of challenges, including the cost of equipment and reagents coupled with the dearth of personnel skilled in the procedures and handling of equipment. Short molecular biology training workshops were conducted at the Nigerian Institute of Medical Research (NIMR), to improve the knowledge and skills of laboratory personnel and academics in health, research, and educational facilities. Five-day molecular biology workshops were conducted annually between 2011 and 2014, with participants drawn from health, research facilities, and the academia. The courses consisted of theoretical and practical sessions. The impact of the workshops on knowledge and skill acquisition was evaluated by pre- and post-tests which consisted of 25 multiple choice and other questions. Sixty-five participants took part in the workshops. The mean knowledge of molecular biology as evaluated by the pre- and post-test assessments were 8.4 (95% CI 7.6-9.1) and 13.0 (95 CI 11.9-14.1), respectively. The mean post-test score was significantly greater than the mean pre-test score (p < 0.0001). The five-day molecular biology workshop significantly increased the knowledge and skills of participants in molecular biology techniques. © 2017 by The International Union of Biochemistry and Molecular Biology, 45(4):313-317, 2017. © 2017 The International Union of Biochemistry and Molecular Biology.

Knowledge base and functionality of concepts of some Filipino biology teachers in five biology topics

NASA Astrophysics Data System (ADS)

Barquilla, Manuel B.

2018-01-01

This mixed research, is a snapshot of some Filipino Biology teachers' knowledge structure and how their concepts of the five topics in Biology (Photosynthesis, Cellular Respiration, human reproductive system, Mendelian genetics and NonMendelian genetics) functions and develops inside a biology classroom. The study focuses on the six biology teachers and a total of 222 students in their respective classes. Of the Six (6) teachers, three (3) are under the Science curriculum and the other three (3) are under regular curriculum in both public and private schools in Iligan city and Lanao del Norte, Philippines. The study utilized classroom discourses, concept maps, interpretative case-study method, bracketing method, and concept analysis for qualitative part; the quantitative part uses a nonparametric statistical tool, Kendall's tau Coefficient for determining relationship and congruency while measures of central tendencies and dispersion (mean, and standard deviation) for concept maps scores interpretation. Knowledge Base of Biology teachers were evaluated by experts in field of specialization having a doctorate program (e.g. PhD in Genetics) and PhD Biology candidates. The data collection entailed seven (7) months immersion: one (1) month for preliminary phase for the researcher to gain teachers' and students' confidence and the succeeding six (6) months for main observation and data collection. The evaluation of teachers' knowledge base by experts indicated that teachers' knowledge of (65%) is lower than the minimum (75%) recommended by ABD-el-Khalick and Boujaoude (1997). Thus, the experts believe that content knowledge of the teachers is hardly adequate for their teaching assignment. Moreover, the teachers in this study do not systematically use reallife situation to apply the concepts they teach. They can identify concepts too abstract for their student; however, they seldom use innovative ways to bring the discussion to their students' level of readiness and capacity to learn. Kendall's Tau Coefficient of agreement indicated that there is an agreement of the rating by experts and PhD (Biology) candidates. As for recommended level for teaching based on the respondent content knowledge structure, the experts and the PhD (Biology) candidates agree that the content knowledge of the teachers is at the borderline (rating of 6) between elementary and high school. These results imply that biology teachers need in-service training to upgrade their content knowledge in the subject. At the same time, the pre-service curriculum for biology teachers needs upgrading.

Introduction of a Framework for Dynamic Knowledge Representation of the Control Structure of Transplant Immunology: Employing the Power of Abstraction with a Solid Organ Transplant Agent-Based Model

PubMed Central

An, Gary

2015-01-01

Agent-based modeling has been used to characterize the nested control loops and non-linear dynamics associated with inflammatory and immune responses, particularly as a means of visualizing putative mechanistic hypotheses. This process is termed dynamic knowledge representation and serves a critical role in facilitating the ability to test and potentially falsify hypotheses in the current data- and hypothesis-rich biomedical research environment. Importantly, dynamic computational modeling aids in identifying useful abstractions, a fundamental scientific principle that pervades the physical sciences. Recognizing the critical scientific role of abstraction provides an intellectual and methodological counterweight to the tendency in biology to emphasize comprehensive description as the primary manifestation of biological knowledge. Transplant immunology represents yet another example of the challenge of identifying sufficient understanding of the inflammatory/immune response in order to develop and refine clinically effective interventions. Advances in immunosuppressive therapies have greatly improved solid organ transplant (SOT) outcomes, most notably by reducing and treating acute rejection. The end goal of these transplant immune strategies is to facilitate effective control of the balance between regulatory T cells and the effector/cytotoxic T-cell populations in order to generate, and ideally maintain, a tolerant phenotype. Characterizing the dynamics of immune cell populations and the interactive feedback loops that lead to graft rejection or tolerance is extremely challenging, but is necessary if rational modulation to induce transplant tolerance is to be accomplished. Herein is presented the solid organ agent-based model (SOTABM) as an initial example of an agent-based model (ABM) that abstractly reproduces the cellular and molecular components of the immune response to SOT. Despite its abstract nature, the SOTABM is able to qualitatively reproduce acute rejection and the suppression of acute rejection by immunosuppression to generate transplant tolerance. The SOTABM is intended as an initial example of how ABMs can be used to dynamically represent mechanistic knowledge concerning transplant immunology in a scalable and expandable form and can thus potentially serve as useful adjuncts to the investigation and development of control strategies to induce transplant tolerance. PMID:26594211

Introduction of a Framework for Dynamic Knowledge Representation of the Control Structure of Transplant Immunology: Employing the Power of Abstraction with a Solid Organ Transplant Agent-Based Model.

PubMed

An, Gary

2015-01-01

Agent-based modeling has been used to characterize the nested control loops and non-linear dynamics associated with inflammatory and immune responses, particularly as a means of visualizing putative mechanistic hypotheses. This process is termed dynamic knowledge representation and serves a critical role in facilitating the ability to test and potentially falsify hypotheses in the current data- and hypothesis-rich biomedical research environment. Importantly, dynamic computational modeling aids in identifying useful abstractions, a fundamental scientific principle that pervades the physical sciences. Recognizing the critical scientific role of abstraction provides an intellectual and methodological counterweight to the tendency in biology to emphasize comprehensive description as the primary manifestation of biological knowledge. Transplant immunology represents yet another example of the challenge of identifying sufficient understanding of the inflammatory/immune response in order to develop and refine clinically effective interventions. Advances in immunosuppressive therapies have greatly improved solid organ transplant (SOT) outcomes, most notably by reducing and treating acute rejection. The end goal of these transplant immune strategies is to facilitate effective control of the balance between regulatory T cells and the effector/cytotoxic T-cell populations in order to generate, and ideally maintain, a tolerant phenotype. Characterizing the dynamics of immune cell populations and the interactive feedback loops that lead to graft rejection or tolerance is extremely challenging, but is necessary if rational modulation to induce transplant tolerance is to be accomplished. Herein is presented the solid organ agent-based model (SOTABM) as an initial example of an agent-based model (ABM) that abstractly reproduces the cellular and molecular components of the immune response to SOT. Despite its abstract nature, the SOTABM is able to qualitatively reproduce acute rejection and the suppression of acute rejection by immunosuppression to generate transplant tolerance. The SOTABM is intended as an initial example of how ABMs can be used to dynamically represent mechanistic knowledge concerning transplant immunology in a scalable and expandable form and can thus potentially serve as useful adjuncts to the investigation and development of control strategies to induce transplant tolerance.

An ontology-driven semantic mash-up of gene and biological pathway information: Application to the domain of nicotine dependence

PubMed Central

Sahoo, Satya S.; Bodenreider, Olivier; Rutter, Joni L.; Skinner, Karen J.; Sheth, Amit P.

2008-01-01

Objectives This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. Methods We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Results Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Conclusion Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. Resource page http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/ PMID:18395495

An ontology-driven semantic mashup of gene and biological pathway information: application to the domain of nicotine dependence.

PubMed

Sahoo, Satya S; Bodenreider, Olivier; Rutter, Joni L; Skinner, Karen J; Sheth, Amit P

2008-10-01

This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. RESOURCE PAGE: http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/

BioTextQuest(+): a knowledge integration platform for literature mining and concept discovery.

PubMed

Papanikolaou, Nikolas; Pavlopoulos, Georgios A; Pafilis, Evangelos; Theodosiou, Theodosios; Schneider, Reinhard; Satagopam, Venkata P; Ouzounis, Christos A; Eliopoulos, Aristides G; Promponas, Vasilis J; Iliopoulos, Ioannis

2014-11-15

The iterative process of finding relevant information in biomedical literature and performing bioinformatics analyses might result in an endless loop for an inexperienced user, considering the exponential growth of scientific corpora and the plethora of tools designed to mine PubMed(®) and related biological databases. Herein, we describe BioTextQuest(+), a web-based interactive knowledge exploration platform with significant advances to its predecessor (BioTextQuest), aiming to bridge processes such as bioentity recognition, functional annotation, document clustering and data integration towards literature mining and concept discovery. BioTextQuest(+) enables PubMed and OMIM querying, retrieval of abstracts related to a targeted request and optimal detection of genes, proteins, molecular functions, pathways and biological processes within the retrieved documents. The front-end interface facilitates the browsing of document clustering per subject, the analysis of term co-occurrence, the generation of tag clouds containing highly represented terms per cluster and at-a-glance popup windows with information about relevant genes and proteins. Moreover, to support experimental research, BioTextQuest(+) addresses integration of its primary functionality with biological repositories and software tools able to deliver further bioinformatics services. The Google-like interface extends beyond simple use by offering a range of advanced parameterization for expert users. We demonstrate the functionality of BioTextQuest(+) through several exemplary research scenarios including author disambiguation, functional term enrichment, knowledge acquisition and concept discovery linking major human diseases, such as obesity and ageing. The service is accessible at http://bioinformatics.med.uoc.gr/biotextquest. g.pavlopoulos@gmail.com or georgios.pavlopoulos@esat.kuleuven.be Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Investigating Undergraduate Students' Use of Intuitive Reasoning and Evolutionary Knowledge in Explanations of Antibiotic Resistance.

PubMed

Richard, Melissa; Coley, John D; Tanner, Kimberly D

2017-01-01

Natural selection is a central concept throughout biology; however, it is a process frequently misunderstood. Bacterial resistance to antibiotic medications provides a contextual example of the relevance of evolutionary theory and is also commonly misunderstood. While research has shed light on student misconceptions of natural selection, minimal study has focused on misconceptions of antibiotic resistance. Additionally, research has focused on the degree to which misconceptions may be based in the complexity of biological information or in pedagogical choices, rather than in deep-seated cognitive patterns. Cognitive psychology research has established that humans develop early intuitive assumptions to make sense of the world. In this study, we used a written assessment tool to investigate undergraduate students' misconceptions of antibiotic resistance, use of intuitive reasoning, and application of evolutionary knowledge to antibiotic resistance. We found a majority of students produced and agreed with misconceptions, and intuitive reasoning was present in nearly all students' written explanations. Acceptance of a misconception was significantly associated with production of a hypothesized form of intuitive thinking (all p ≤ 0.05). Intuitive reasoning may represent a subtle but innately appealing linguistic shorthand, and instructor awareness of intuitive reasoning's relation to student misunderstandings has potential for addressing persistent misconceptions. © 2017 M. Richard et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Preservice Biology Teachers' Professional Knowledge: Structure and Learning Opportunities

ERIC Educational Resources Information Center

Großschedl, Jörg; Harms, Ute; Kleickmann, Thilo; Glowinski, Ingrid

2015-01-01

What learning opportunities in higher education promote the development of content knowledge (CK), pedagogical content knowledge (PCK), and pedagogical knowledge (PK)? In order to investigate this question, a cross-sectional study with a total of 274 German preservice biology teachers (21.5% male, average age 22.8 years) was conducted in German…

Primary School Student Teachers' Perceived and Actual Knowledge in Biology

ERIC Educational Resources Information Center

Eija, Yli-Panula; Eila, Jeronen; Pongsakdi, Nonmanut

2017-01-01

Individuals' perceptions of their knowledge can have an important role in shaping their cognition and influencing their behaviour. However, there has been a scarcity of studies in biology on how perceived knowledge relates to actual knowledge. The focus of this article is on quantitative results analysing and interpreting student teachers'…

High School Biology Students' Knowledge and Certainty about Diffusion and Osmosis Concepts

ERIC Educational Resources Information Center

Odom, Arthur L.; Barrow, Lloyd H.

2007-01-01

The purpose of this study was to investigate students' understanding about scientifically acceptable content knowledge by exploring the relationship between knowledge of diffusion and osmosis and the students' certainty in their content knowledge. Data was collected from a high school biology class with the Diffusion and Osmosis Diagnostic Test…

The acquisition of biological knowledge during childhood: Cognitive conflict or tabula rasa?

NASA Astrophysics Data System (ADS)

Lawson, Anton E.

Clinical interviews were conducted with three elementary school children, who varied in age but not in family or school environment, to determine the extent to which they held naive misconceptions about important biological topics and to determine agewise trends in the development of biological knowledge. Does early biological knowledge acquisition follow a pattern of spontaneous naive theory construction and cognitive conflict or does it follow a pattern of gradual accretion to an initially blank slate? Contrary to findings in the physical sciences, little evidence was found for biological misconceptions as knowledge acquisition appeared to more directly follow the gradual accretion hypothesis with the primary source of that knowledge adult authority rather than personal experience. However, conceptual change teaching is still advocated due to its ability to provoke students to consider and test alternative conceptions (even if they are not their own) as a means of encouraging the development of important general reasoning patterns utilized in the testing of causal hypotheses.

Correlation set analysis: detecting active regulators in disease populations using prior causal knowledge

PubMed Central

2012-01-01

Background Identification of active causal regulators is a crucial problem in understanding mechanism of diseases or finding drug targets. Methods that infer causal regulators directly from primary data have been proposed and successfully validated in some cases. These methods necessarily require very large sample sizes or a mix of different data types. Recent studies have shown that prior biological knowledge can successfully boost a method's ability to find regulators. Results We present a simple data-driven method, Correlation Set Analysis (CSA), for comprehensively detecting active regulators in disease populations by integrating co-expression analysis and a specific type of literature-derived causal relationships. Instead of investigating the co-expression level between regulators and their regulatees, we focus on coherence of regulatees of a regulator. Using simulated datasets we show that our method performs very well at recovering even weak regulatory relationships with a low false discovery rate. Using three separate real biological datasets we were able to recover well known and as yet undescribed, active regulators for each disease population. The results are represented as a rank-ordered list of regulators, and reveals both single and higher-order regulatory relationships. Conclusions CSA is an intuitive data-driven way of selecting directed perturbation experiments that are relevant to a disease population of interest and represent a starting point for further investigation. Our findings demonstrate that combining co-expression analysis on regulatee sets with a literature-derived network can successfully identify causal regulators and help develop possible hypothesis to explain disease progression. PMID:22443377

Representing Ontogeny Through Ontology: A Developmental Biologist’s Guide to The Gene Ontology

PubMed Central

Hill, David P.; Berardini, Tanya Z.; Howe, Douglas G.; Van Auken, Kimberly M.

2010-01-01

Developmental biology, like many other areas of biology, has undergone a dramatic shift in the perspective from which developmental processes are viewed. Instead of focusing on the actions of a handful of genes or functional RNAs, we now consider the interactions of large functional gene networks and study how these complex systems orchestrate the unfolding of an organism, from gametes to adult. Developmental biologists are beginning to realize that understanding ontogeny on this scale requires the utilization of computational methods to capture, store and represent the knowledge we have about the underlying processes. Here we review the use of the Gene Ontology (GO) to study developmental biology. We describe the organization and structure of the GO and illustrate some of the ways we use it to capture the current understanding of many common developmental processes. We also discuss ways in which gene product annotations using the GO have been used to ask and answer developmental questions in a variety of model developmental systems. We provide suggestions as to how the GO might be used in more powerful ways to address questions about development. Our goal is to provide developmental biologists with enough background about the GO that they can begin to think about how they might use the ontology efficiently and in the most powerful ways possible. PMID:19921742

Adaptable data management for systems biology investigations.

PubMed

Boyle, John; Rovira, Hector; Cavnor, Chris; Burdick, David; Killcoyne, Sarah; Shmulevich, Ilya

2009-03-06

Within research each experiment is different, the focus changes and the data is generated from a continually evolving barrage of technologies. There is a continual introduction of new techniques whose usage ranges from in-house protocols through to high-throughput instrumentation. To support these requirements data management systems are needed that can be rapidly built and readily adapted for new usage. The adaptable data management system discussed is designed to support the seamless mining and analysis of biological experiment data that is commonly used in systems biology (e.g. ChIP-chip, gene expression, proteomics, imaging, flow cytometry). We use different content graphs to represent different views upon the data. These views are designed for different roles: equipment specific views are used to gather instrumentation information; data processing oriented views are provided to enable the rapid development of analysis applications; and research project specific views are used to organize information for individual research experiments. This management system allows for both the rapid introduction of new types of information and the evolution of the knowledge it represents. Data management is an important aspect of any research enterprise. It is the foundation on which most applications are built, and must be easily extended to serve new functionality for new scientific areas. We have found that adopting a three-tier architecture for data management, built around distributed standardized content repositories, allows us to rapidly develop new applications to support a diverse user community.

Integrative Systems Biology for Data Driven Knowledge Discovery

PubMed Central

Greene, Casey S.; Troyanskaya, Olga G.

2015-01-01

Integrative systems biology is an approach that brings together diverse high throughput experiments and databases to gain new insights into biological processes or systems at molecular through physiological levels. These approaches rely on diverse high-throughput experimental techniques that generate heterogeneous data by assaying varying aspects of complex biological processes. Computational approaches are necessary to provide an integrative view of these experimental results and enable data-driven knowledge discovery. Hypotheses generated from these approaches can direct definitive molecular experiments in a cost effective manner. Using integrative systems biology approaches, we can leverage existing biological knowledge and large-scale data to improve our understanding of yet unknown components of a system of interest and how its malfunction leads to disease. PMID:21044756

At the biological modeling and simulation frontier.

PubMed

Hunt, C Anthony; Ropella, Glen E P; Lam, Tai Ning; Tang, Jonathan; Kim, Sean H J; Engelberg, Jesse A; Sheikh-Bahaei, Shahab

2009-11-01

We provide a rationale for and describe examples of synthetic modeling and simulation (M&S) of biological systems. We explain how synthetic methods are distinct from familiar inductive methods. Synthetic M&S is a means to better understand the mechanisms that generate normal and disease-related phenomena observed in research, and how compounds of interest interact with them to alter phenomena. An objective is to build better, working hypotheses of plausible mechanisms. A synthetic model is an extant hypothesis: execution produces an observable mechanism and phenomena. Mobile objects representing compounds carry information enabling components to distinguish between them and react accordingly when different compounds are studied simultaneously. We argue that the familiar inductive approaches contribute to the general inefficiencies being experienced by pharmaceutical R&D, and that use of synthetic approaches accelerates and improves R&D decision-making and thus the drug development process. A reason is that synthetic models encourage and facilitate abductive scientific reasoning, a primary means of knowledge creation and creative cognition. When synthetic models are executed, we observe different aspects of knowledge in action from different perspectives. These models can be tuned to reflect differences in experimental conditions and individuals, making translational research more concrete while moving us closer to personalized medicine.

STARLIFE - An International Campaign to Study the Role of Galactic Cosmic Radiation in Astrobiological Model Systems

NASA Astrophysics Data System (ADS)

Moeller, Ralf; Raguse, Marina; Leuko, Stefan; Berger, Thomas; Hellweg, Christine Elisabeth; Fujimori, Akira; Okayasu, Ryuichi; Horneck, Gerda

2017-02-01

In-depth knowledge regarding the biological effects of the radiation field in space is required for assessing the radiation risks in space. To obtain this knowledge, a set of different astrobiological model systems has been studied within the STARLIFE radiation campaign during six irradiation campaigns (2013-2015). The STARLIFE group is an international consortium with the aim to investigate the responses of different astrobiological model systems to the different types of ionizing radiation (X-rays, γ rays, heavy ions) representing major parts of the galactic cosmic radiation spectrum. Low- and high-energy charged particle radiation experiments have been conducted at the Heavy Ion Medical Accelerator in Chiba (HIMAC) facility at the National Institute of Radiological Sciences (NIRS) in Chiba, Japan. X-rays or γ rays were used as reference radiation at the German Aerospace Center (DLR, Cologne, Germany) or Beta-Gamma-Service GmbH (BGS, Wiehl, Germany) to derive the biological efficiency of different radiation qualities. All samples were exposed under identical conditions to the same dose and qualities of ionizing radiation (i) allowing a direct comparison between the tested specimens and (ii) providing information on the impact of the space radiation environment on currently used astrobiological model organisms.

The human genome: Some assembly required. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1994-12-31

The Human Genome Project promises to be one of the most rewarding endeavors in modern biology. The cost and the ethical and social implications, however, have made this project the source of considerable debate both in the scientific community and in the public at large. The 1994 Graduate Student Symposium addresses the scientific merits of the project, the technical issues involved in accomplishing the task, as well as the medical and social issues which stem from the wealth of knowledge which the Human Genome Project will help create. To this end, speakers were brought together who represent the diverse areasmore » of expertise characteristic of this multidisciplinary project. The keynote speaker addresses the project`s motivations and goals in the larger context of biological and medical sciences. The first two sessions address relevant technical issues, data collection with a focus on high-throughput sequencing methods and data analysis with an emphasis on identification of coding sequences. The third session explores recent advances in the understanding of genetic diseases and possible routes to treatment. Finally, the last session addresses some of the ethical, social and legal issues which will undoubtedly arise from having a detailed knowledge of the human genome.« less

Contribution to the knowledge of Saprinus Erichson, 1834 of forensic relevance from Lebanon (Coleoptera, Histeridae).

PubMed

Shayya, Salman; Dégallier, Nicolas; Nel, André; Azar, Dany; Lackner, Tomáš

2018-01-01

Many histerid beetles are necrophilous on carrion during both active and advanced stages of decomposition. In this study, 13 species of Saprinus were recorded on carrion from Lebanon, containing eight that are new for the Lebanese fauna. The following Saprinus species are newly recorded from Lebanon: 1) Saprinus (S.) caerulescens caerulescens (Hoffmann, 1803); 2) S. (S.) calatravensis Fuente, 1899; 3) S. (S.) chalcites (Illiger, 1807); 4) S. (S.) godet (Brullé, 1832); 5) S. (S.) maculatus (P. Rossi, 1792); 6) S. (S.) strigil Marseul, 1855; 7) S. (S.) submarginatus J. Sahlberg, 1913; and 8) S. (S.) tenuistrius sparsutus Solsky, 1876. The peak activity was recorded, key for the species is provided, and habitus images and male genitalia are illustrated in order to facilitate their taxonomic identifications. Saprinus species are diverse and common on animal carcass; they were likewise collected from a human cadaver in Lebanon. Preliminary comments on biology and distribution of the studied species are given. Our paper represents the first faunistic study on Histeridae from Lebanon. A rigorous research program regarding the biology of Saprinus in Lebanon and the neighbouring countries would greatly improve the knowledge of the diversity, activity, and possible forensic value of Saprinus .

Ontology Sparse Vector Learning Algorithm for Ontology Similarity Measuring and Ontology Mapping via ADAL Technology

NASA Astrophysics Data System (ADS)

Gao, Wei; Zhu, Linli; Wang, Kaiyun

2015-12-01

Ontology, a model of knowledge representation and storage, has had extensive applications in pharmaceutics, social science, chemistry and biology. In the age of “big data”, the constructed concepts are often represented as higher-dimensional data by scholars, and thus the sparse learning techniques are introduced into ontology algorithms. In this paper, based on the alternating direction augmented Lagrangian method, we present an ontology optimization algorithm for ontological sparse vector learning, and a fast version of such ontology technologies. The optimal sparse vector is obtained by an iterative procedure, and the ontology function is then obtained from the sparse vector. Four simulation experiments show that our ontological sparse vector learning model has a higher precision ratio on plant ontology, humanoid robotics ontology, biology ontology and physics education ontology data for similarity measuring and ontology mapping applications.

Southern Ocean biological iron cycling in the pre-whaling and present ecosystems

NASA Astrophysics Data System (ADS)

Maldonado, Maria T.; Surma, Szymon; Pakhomov, Evgeny A.

2016-11-01

This study aimed to create the first model of biological iron (Fe) cycling in the Southern Ocean food web. Two biomass mass-balanced Ecopath models were built to represent pre- and post-whaling ecosystem states (1900 and 2008). Functional group biomasses (tonnes wet weight km-2) were converted to biogenic Fe pools (kg Fe km-2) using published Fe content ranges. In both models, biogenic Fe pools and consumption in the pelagic Southern Ocean were highest for plankton and small nektonic groups. The production of plankton biomass, particularly unicellular groups, accounted for the highest annual Fe demand. Microzooplankton contributed most to biological Fe recycling, followed by carnivorous zooplankton and krill. Biological Fe recycling matched previous estimates, and, under most conditions, could entirely meet the Fe demand of bacterioplankton and phytoplankton. Iron recycling by large baleen whales was reduced 10-fold by whaling between 1900 and 2008. However, even under the 1900 scenario, the contribution of whales to biological Fe recycling was negligible compared with that of planktonic consumers. These models are a first step in examining oceanic-scale biological Fe cycling, highlighting gaps in our present knowledge and key questions for future research on the role of marine food webs in the cycling of trace elements in the sea. This article is part of the themed issue 'Biological and climatic impacts of ocean trace element chemistry'.

Southern Ocean biological iron cycling in the pre-whaling and present ecosystems.

PubMed

Maldonado, Maria T; Surma, Szymon; Pakhomov, Evgeny A

2016-11-28

This study aimed to create the first model of biological iron (Fe) cycling in the Southern Ocean food web. Two biomass mass-balanced Ecopath models were built to represent pre- and post-whaling ecosystem states (1900 and 2008). Functional group biomasses (tonnes wet weight km -2 ) were converted to biogenic Fe pools (kg Fe km -2 ) using published Fe content ranges. In both models, biogenic Fe pools and consumption in the pelagic Southern Ocean were highest for plankton and small nektonic groups. The production of plankton biomass, particularly unicellular groups, accounted for the highest annual Fe demand. Microzooplankton contributed most to biological Fe recycling, followed by carnivorous zooplankton and krill. Biological Fe recycling matched previous estimates, and, under most conditions, could entirely meet the Fe demand of bacterioplankton and phytoplankton. Iron recycling by large baleen whales was reduced 10-fold by whaling between 1900 and 2008. However, even under the 1900 scenario, the contribution of whales to biological Fe recycling was negligible compared with that of planktonic consumers. These models are a first step in examining oceanic-scale biological Fe cycling, highlighting gaps in our present knowledge and key questions for future research on the role of marine food webs in the cycling of trace elements in the sea.This article is part of the themed issue 'Biological and climatic impacts of ocean trace element chemistry'. © 2016 The Author(s).

Does the transition to an active-learning environment for the introductory course reduce students' overall knowledge of the various disciplines in biology?

PubMed

Simurda, Maryanne C

2012-01-01

As biology education is being redesigned toward an interdisciplinary focus and as pedagogical trends move toward active-learning strategies and investigative experiences, a restructuring of the course content for the Introductory Biology course is necessary. The introductory course in biology has typically been a survey of all the biosciences. If the total number of topics covered is reduced, is the students' overall knowledge of biology also reduced? Our introductory course has been substantially modified away from surveying the biological sciences and toward providing a deep understanding of a particular biological topic, as well as focusing on developing students' analytical and communication skills. Because of this shift to a topic-driven approach for the introductory course, we were interested in assessing our graduating students' overall knowledge of the various biological disciplines. Using the Major Field Test - Biology (Educational Testing Service (ETS), Princeton, NJ), we compared the test performance of graduating students who had a traditional lecture-based introductory course to those who had a topic-driven active-learning introductory course. Our results suggest that eliminating the traditional survey of biology and, instead, focusing on quantitative and writing skills at the introductory level do not affect our graduating students' overall breadth of knowledge of the various biosciences.

Characterization of the cork oak transcriptome dynamics during acorn development.

PubMed

Miguel, Andreia; de Vega-Bartol, José; Marum, Liliana; Chaves, Inês; Santo, Tatiana; Leitão, José; Varela, Maria Carolina; Miguel, Célia M

2015-06-25

Cork oak (Quercus suber L.) has a natural distribution across western Mediterranean regions and is a keystone forest tree species in these ecosystems. The fruiting phase is especially critical for its regeneration but the molecular mechanisms underlying the biochemical and physiological changes during cork oak acorn development are poorly understood. In this study, the transcriptome of the cork oak acorn, including the seed, was characterized in five stages of development, from early development to acorn maturation, to identify the dominant processes in each stage and reveal transcripts with important functions in gene expression regulation and response to water. A total of 80,357 expressed sequence tags (ESTs) were de novo assembled from RNA-Seq libraries representative of the several acorn developmental stages. Approximately 7.6 % of the total number of transcripts present in Q. suber transcriptome was identified as acorn specific. The analysis of expression profiles during development returned 2,285 differentially expressed (DE) transcripts, which were clustered into six groups. The stage of development corresponding to the mature acorn exhibited an expression profile markedly different from other stages. Approximately 22 % of the DE transcripts putatively code for transcription factors (TF) or transcriptional regulators, and were found almost equally distributed among the several expression profile clusters, highlighting their major roles in controlling the whole developmental process. On the other hand, carbohydrate metabolism, the biological pathway most represented during acorn development, was especially prevalent in mid to late stages as evidenced by enrichment analysis. We further show that genes related to response to water, water deprivation and transport were mostly represented during the early (S2) and the last stage (S8) of acorn development, when tolerance to water desiccation is possibly critical for acorn viability. To our knowledge this work represents the first report of acorn development transcriptomics in oaks. The obtained results provide novel insights into the developmental biology of cork oak acorns, highlighting transcripts putatively involved in the regulation of the gene expression program and in specific processes likely essential for adaptation. It is expected that this knowledge can be transferred to other oak species of great ecological value.

Summary report of a workshop on research opportunities in plant biochemistry, December 11--13, 1992, Kona, Hawaii

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1992-12-31

A DOE-sponsored workshop was held December 11--13, 1992 in Kona, Hawaii to discuss those aspects of fundamental research in plant biochemistry deemed essential to provide the basic information base necessary for exploiting plant biotechnology to meet future societal needs. Twenty nine scientists, with interests representing many of the various areas of plant biochemistry, participated. The workshop was intended to define in both broad and specific terms the current state of knowledge in the general area of metabolic biochemistry, and to identify those areas that afford unusual opportunity or that are relatively underdeveloped in comparison with other areas of plant biology.more » Participants provided critiques of the state of knowledge of the major areas of metabolic biochemistry in relation to a series of questions that are presented herein.« less

Phylogenics & Tree-Thinking

ERIC Educational Resources Information Center

Baum, David A.; Offner, Susan

2008-01-01

Phylogenetic trees, which are depictions of the inferred evolutionary relationships among a set of species, now permeate almost all branches of biology and are appearing in increasing numbers in biology textbooks. While few state standards explicitly require knowledge of phylogenetics, most require some knowledge of evolutionary biology, and many…

Traces of embryogenesis are the same in monozygotic and dizygotic twins: not compatible with double ovulation.

PubMed

Boklage, Charles E

2009-06-01

Common knowledge of over a century has it that monozygotic and dizygotic twinning events occur by unrelated mechanisms: monozygotic twinning 'splits' embryos, producing anomalously re-arranged embryogenic asymmetries; dizygotic twinning begins with independent ovulations yielding undisturbed parallel embryogeneses with no expectation of departures from singleton outcomes. The anomalies statistically associated with twin births are due to the re-arranged embryos of the monozygotics. Common knowledge further requires that dizygotic pairs are dichorionic; monochorionicity is exclusive to monozygotic pairs. These are fundamental certainties in the literature of twin biology. Multiple observations contradict those common knowledge understandings. The double ovulation hypothesis of dizygotic twinning is untenable. Girl-boy twins differ subtly from all other humans of either sex, absolutely not representative of all dizygotics. Embryogenesis of dizygotic twins differs from singleton development at least as much as monozygotic embryogenesis does, and in the same ways, and the differences between singletons and twins of both zygosities represent a coherent system of re-arranged embryogenic asymmetries. Dizygotic twinning and monozygotic twinning have the same list of consequences of anomalous embryogenesis. Those include an unignorable fraction of dizygotic pairs that are in fact monochorionic, plus many more sharing co-twins' cells in tissues other than a common chorion. The idea that monozygotic and dizygotic twinning events arise from the same embryogenic mechanism is the only plausible hypothesis that might explain all of the observations.

AIDS Knowledge: The Media and the Biology Teacher.

ERIC Educational Resources Information Center

Vener, Arthur M.; Krupka, Lawrence R.

1988-01-01

Reports on a study to determine the level of knowledge college students possessed about Acquired Immune Deficiency Syndrome. Concluded that overall enhancement of knowledge occurred among young adults and that mass media was partially responsible. Lists biological terms necessary for understanding the disease. (RT)

On the debate about teleology in biology: the notion of "teleological obstacle".

PubMed

Ribeiro, Manuel Gustavo Leitão; Larentis, Ariane Leites; Caldas, Lúcio Ayres; Garcia, Tomás Coelho; Terra, Letícia Labati; Herbst, Marcelo Hawrylak; Almeida, Rodrigo Volcan

2015-12-01

Among the epistemological obstacles described by Gaston Bachelard, we contend that unitary and pragmatic knowledge is correlated to the teleological categories of Ernst Mayr and is the basis for prevailing debate on the notion of "function" in biology. Given the proximity of the aspects highlighted by these authors, we propose to associate the role of teleological thinking in biology and the notion of unitary and pragmatic knowledge as an obstacle to scientific knowledge. Thus, teleological thinking persists acting as an epistemological obstacle in biology, according to Bachelardian terminology. Our investigation led us to formulate the "teleological obstacle," which we consider important for the future of biology and possibly other sciences.

Building confidence: an exploration of nurses undertaking a postgraduate biological science course.

PubMed

Van Wissen, Kim; McBride-Henry, Karen

2010-01-01

This study aimed to explore the impact of studying biological science at a postgraduate level and how this impacted on nursing practice. The term biological sciences in this research encompasses elements of physiology, genetics, biochemistry and pathophysiology. A qualitative research study was designed, that involved the dissemination of a pre- and post-course semi-structured questionnaire for a biological science course, as part of a Master of Nursing programme at a New Zealand University, thus exploring the impact of undertaking a postgraduate biological sciences course. The responses were analysed into themes, based on interpretive concepts. The primary themes revealed improvement in confidence as: confidence in communication, confidence in linking nursing theoretical knowledge to practice and confidence in clinical nursing knowledge. This study highlights the need to privilege clinically-derived nursing knowledge, and that confidence in this nursing knowledge and clinical practice can be instilled through employing the model of theory-guided practice.

[Physicians' knowledge in Israel on the biology and control of head lice].

PubMed

Mumcuoglu, Kosta Y; Mumcuoglu, Michael; Danilevich, Maria; Gilead, Leon

2008-10-01

Health providers such as physicians, nurses and pharmacists should be knowledgeable about the biology of head lice and the ways to control them effectively, in order to reduce the proportion of children infested with head lice. To evaluate the knowledge of physicians in Israel on the biology and epidemiology of lice, as well as their experience with infested individuals and their preferences for diagnosis, prophylaxis and control. An anonymous questionnaire with 37 questions was used. The first 20 questions addressed the general knowledge of physicians on lice biology and control, while the remaining 17 questions were related to their personal experience with lice and louse treatment. Out of 273 physicians interviewed 66.8% had good knowledge of lice, while the remaining 33.2% had some knowledge on lice. The difference between the groups of physicians with medium and good knowledge on lice was borderline significant (P=0.0722), with the dermatologists borderline significantly less knowledgeable than the rest (P=0.0765). Significant differences were found between those physicians with 4-6 or 11-20 years of professional experience and the remaining groups (twice P<0.001). Although the percentage of female physicians who had a good knowledge on louse biology and control was higher than male physicians (39.4% and 29.4%, respectively), the differences were borderline significant (P=0.09). Pediatricians and dermatologists examined significantly more children than family physicians and general practitioners (P <0.001). The results of this study suggest that healthcare professionals' knowledge is of paramount importance for the correct diagnosis and control of head louse infestations.

[Knowledge and power at a molecular level; biological psychiatry in a social context].

PubMed

Verhoeff, B

2009-01-01

How do we acquire our knowledge about psychiatric disorders and how did the current biologically way of thinking in psychiatry originate? With the help of the philosophy of Michel Foucault and Nikolas Rose this essay describes the conditions that made possible today's biological approach in psychiatry. It will become clear that research in the life sciences and the psychiatric knowledge arising from this research are shaped and formed in a complex network of social, economic, political and scientific forces. The biological approach to psychiatric disorders is the product of present-day relationships between scientific developments and commercial corporations.

Influence of Content Knowledge on Pedagogical Content Knowledge: The Case of Teaching Photosynthesis and Plant Growth

ERIC Educational Resources Information Center

Kapyla, Markku; Heikkinen, Jussi-Pekka; Asunta, Tuula

2009-01-01

The aim of the research was to investigate the effect of the amount and quality of content knowledge on pedagogical content knowledge (PCK). The biological content photosynthesis and plant growth was used as an example. The research sample consisted of 10 primary and 10 secondary (biology) teacher students. Questionnaires, lesson preparation task…

iAB-RBC-283: A proteomically derived knowledge-base of erythrocyte metabolism that can be used to simulate its physiological and patho-physiological states.

PubMed

Bordbar, Aarash; Jamshidi, Neema; Palsson, Bernhard O

2011-07-12

The development of high-throughput technologies capable of whole cell measurements of genes, proteins, and metabolites has led to the emergence of systems biology. Integrated analysis of the resulting omic data sets has proved to be hard to achieve. Metabolic network reconstructions enable complex relationships amongst molecular components to be represented formally in a biologically relevant manner while respecting physical constraints. In silico models derived from such reconstructions can then be queried or interrogated through mathematical simulations. Proteomic profiling studies of the mature human erythrocyte have shown more proteins present related to metabolic function than previously thought; however the significance and the causal consequences of these findings have not been explored. Erythrocyte proteomic data was used to reconstruct the most expansive description of erythrocyte metabolism to date, following extensive manual curation, assessment of the literature, and functional testing. The reconstruction contains 281 enzymes representing functions from glycolysis to cofactor and amino acid metabolism. Such a comprehensive view of erythrocyte metabolism implicates the erythrocyte as a potential biomarker for different diseases as well as a 'cell-based' drug-screening tool. The analysis shows that 94 erythrocyte enzymes are implicated in morbid single nucleotide polymorphisms, representing 142 pathologies. In addition, over 230 FDA-approved and experimental pharmaceuticals have enzymatic targets in the erythrocyte. The advancement of proteomic technologies and increased generation of high-throughput proteomic data have created the need for a means to analyze these data in a coherent manner. Network reconstructions provide a systematic means to integrate and analyze proteomic data in a biologically meaning manner. Analysis of the red cell proteome has revealed an unexpected level of complexity in the functional capabilities of human erythrocyte metabolism.

What do unicellular organisms teach us about DNA methylation?

PubMed

Harony, Hala; Ankri, Serge

2008-05-01

DNA methylation is an epigenetic hallmark that has been studied intensively in mammals and plants. However, knowledge of this phenomenon in unicellular organisms is scanty. Examining epigenetic regulation, and more specifically DNA methylation, in these organisms represents a unique opportunity to better understand their biology. The determination of their methylation status is often complicated by the presence of several differentiation stages in their life cycle. This article focuses on some recent advances that have revealed the unexpected nature of the epigenetic determinants present in protozoa. The role of the enigmatic DNA methyltransferase Dnmt2 in unicellular organisms is discussed.

Biology. Student Investigations and Readings. Investigations in Natural Science.

ERIC Educational Resources Information Center

Renner, John W.; And Others

Investigations in Natural Science is a program in secondary school biology, chemistry, and physics based upon the description of science as a quest for knowledge, not the knowledge itself. This student manual contains the 18 biology investigations. These investigations focus on concepts related to: organisms; classification; populations;…

Preservice Biology Teachers' Conceptions about the Tentative Nature of Theories and Models in Biology

ERIC Educational Resources Information Center

Reinisch, Bianca; Krüger, Dirk

2018-01-01

In research on the nature of science, there is a need to investigate the role and status of different scientific knowledge forms. Theories and models are two of the most important knowledge forms within biology and are the focus of this study. During interviews, preservice biology teachers (N = 10) were asked about their understanding of theories…

A System-Level Pathway-Phenotype Association Analysis Using Synthetic Feature Random Forest

PubMed Central

Pan, Qinxin; Hu, Ting; Malley, James D.; Andrew, Angeline S.; Karagas, Margaret R.; Moore, Jason H.

2015-01-01

As the cost of genome-wide genotyping decreases, the number of genome-wide association studies (GWAS) has increased considerably. However, the transition from GWAS findings to the underlying biology of various phenotypes remains challenging. As a result, due to its system-level interpretability, pathway analysis has become a popular tool for gaining insights on the underlying biology from high-throughput genetic association data. In pathway analyses, gene sets representing particular biological processes are tested for significant associations with a given phenotype. Most existing pathway analysis approaches rely on single-marker statistics and assume that pathways are independent of each other. As biological systems are driven by complex biomolecular interactions, embracing the complex relationships between single-nucleotide polymorphisms (SNPs) and pathways needs to be addressed. To incorporate the complexity of gene-gene interactions and pathway-pathway relationships, we propose a system-level pathway analysis approach, synthetic feature random forest (SF-RF), which is designed to detect pathway-phenotype associations without making assumptions about the relationships among SNPs or pathways. In our approach, the genotypes of SNPs in a particular pathway are aggregated into a synthetic feature representing that pathway via Random Forest (RF). Multiple synthetic features are analyzed using RF simultaneously and the significance of a synthetic feature indicates the significance of the corresponding pathway. We further complement SF-RF with pathway-based Statistical Epistasis Network (SEN) analysis that evaluates interactions among pathways. By investigating the pathway SEN, we hope to gain additional insights into the genetic mechanisms contributing to the pathway-phenotype association. We apply SF-RF to a population-based genetic study of bladder cancer and further investigate the mechanisms that help explain the pathway-phenotype associations using SEN. The bladder cancer associated pathways we found are both consistent with existing biological knowledge and reveal novel and plausible hypotheses for future biological validations. PMID:24535726

The database of the PREDICTS (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems) project.

PubMed

Hudson, Lawrence N; Newbold, Tim; Contu, Sara; Hill, Samantha L L; Lysenko, Igor; De Palma, Adriana; Phillips, Helen R P; Alhusseini, Tamera I; Bedford, Felicity E; Bennett, Dominic J; Booth, Hollie; Burton, Victoria J; Chng, Charlotte W T; Choimes, Argyrios; Correia, David L P; Day, Julie; Echeverría-Londoño, Susy; Emerson, Susan R; Gao, Di; Garon, Morgan; Harrison, Michelle L K; Ingram, Daniel J; Jung, Martin; Kemp, Victoria; Kirkpatrick, Lucinda; Martin, Callum D; Pan, Yuan; Pask-Hale, Gwilym D; Pynegar, Edwin L; Robinson, Alexandra N; Sanchez-Ortiz, Katia; Senior, Rebecca A; Simmons, Benno I; White, Hannah J; Zhang, Hanbin; Aben, Job; Abrahamczyk, Stefan; Adum, Gilbert B; Aguilar-Barquero, Virginia; Aizen, Marcelo A; Albertos, Belén; Alcala, E L; Del Mar Alguacil, Maria; Alignier, Audrey; Ancrenaz, Marc; Andersen, Alan N; Arbeláez-Cortés, Enrique; Armbrecht, Inge; Arroyo-Rodríguez, Víctor; Aumann, Tom; Axmacher, Jan C; Azhar, Badrul; Azpiroz, Adrián B; Baeten, Lander; Bakayoko, Adama; Báldi, András; Banks, John E; Baral, Sharad K; Barlow, Jos; Barratt, Barbara I P; Barrico, Lurdes; Bartolommei, Paola; Barton, Diane M; Basset, Yves; Batáry, Péter; Bates, Adam J; Baur, Bruno; Bayne, Erin M; Beja, Pedro; Benedick, Suzan; Berg, Åke; Bernard, Henry; Berry, Nicholas J; Bhatt, Dinesh; Bicknell, Jake E; Bihn, Jochen H; Blake, Robin J; Bobo, Kadiri S; Bóçon, Roberto; Boekhout, Teun; Böhning-Gaese, Katrin; Bonham, Kevin J; Borges, Paulo A V; Borges, Sérgio H; Boutin, Céline; Bouyer, Jérémy; Bragagnolo, Cibele; Brandt, Jodi S; Brearley, Francis Q; Brito, Isabel; Bros, Vicenç; Brunet, Jörg; Buczkowski, Grzegorz; Buddle, Christopher M; Bugter, Rob; Buscardo, Erika; Buse, Jörn; Cabra-García, Jimmy; Cáceres, Nilton C; Cagle, Nicolette L; Calviño-Cancela, María; Cameron, Sydney A; Cancello, Eliana M; Caparrós, Rut; Cardoso, Pedro; Carpenter, Dan; Carrijo, Tiago F; Carvalho, Anelena L; Cassano, Camila R; Castro, Helena; Castro-Luna, Alejandro A; Rolando, Cerda B; Cerezo, Alexis; Chapman, Kim Alan; Chauvat, Matthieu; Christensen, Morten; Clarke, Francis M; Cleary, Daniel F R; Colombo, Giorgio; Connop, Stuart P; Craig, Michael D; Cruz-López, Leopoldo; Cunningham, Saul A; D'Aniello, Biagio; D'Cruze, Neil; da Silva, Pedro Giovâni; Dallimer, Martin; Danquah, Emmanuel; Darvill, Ben; Dauber, Jens; Davis, Adrian L V; Dawson, Jeff; de Sassi, Claudio; de Thoisy, Benoit; Deheuvels, Olivier; Dejean, Alain; Devineau, Jean-Louis; Diekötter, Tim; Dolia, Jignasu V; Domínguez, Erwin; Dominguez-Haydar, Yamileth; Dorn, Silvia; Draper, Isabel; Dreber, Niels; Dumont, Bertrand; Dures, Simon G; Dynesius, Mats; Edenius, Lars; Eggleton, Paul; Eigenbrod, Felix; Elek, Zoltán; Entling, Martin H; Esler, Karen J; de Lima, Ricardo F; Faruk, Aisyah; Farwig, Nina; Fayle, Tom M; Felicioli, Antonio; Felton, Annika M; Fensham, Roderick J; Fernandez, Ignacio C; Ferreira, Catarina C; Ficetola, Gentile F; Fiera, Cristina; Filgueiras, Bruno K C; Fırıncıoğlu, Hüseyin K; Flaspohler, David; Floren, Andreas; Fonte, Steven J; Fournier, Anne; Fowler, Robert E; Franzén, Markus; Fraser, Lauchlan H; Fredriksson, Gabriella M; Freire, Geraldo B; Frizzo, Tiago L M; Fukuda, Daisuke; Furlani, Dario; Gaigher, René; Ganzhorn, Jörg U; García, Karla P; Garcia-R, Juan C; Garden, Jenni G; Garilleti, Ricardo; Ge, Bao-Ming; Gendreau-Berthiaume, Benoit; Gerard, Philippa J; Gheler-Costa, Carla; Gilbert, Benjamin; Giordani, Paolo; Giordano, Simonetta; Golodets, Carly; Gomes, Laurens G L; Gould, Rachelle K; Goulson, Dave; Gove, Aaron D; Granjon, Laurent; Grass, Ingo; Gray, Claudia L; Grogan, James; Gu, Weibin; Guardiola, Moisès; Gunawardene, Nihara R; Gutierrez, Alvaro G; Gutiérrez-Lamus, Doris L; Haarmeyer, Daniela H; Hanley, Mick E; Hanson, Thor; Hashim, Nor R; Hassan, Shombe N; Hatfield, Richard G; Hawes, Joseph E; Hayward, Matt W; Hébert, Christian; Helden, Alvin J; Henden, John-André; Henschel, Philipp; Hernández, Lionel; Herrera, James P; Herrmann, Farina; Herzog, Felix; Higuera-Diaz, Diego; Hilje, Branko; Höfer, Hubert; Hoffmann, Anke; Horgan, Finbarr G; Hornung, Elisabeth; Horváth, Roland; Hylander, Kristoffer; Isaacs-Cubides, Paola; Ishida, Hiroaki; Ishitani, Masahiro; Jacobs, Carmen T; Jaramillo, Víctor J; Jauker, Birgit; Hernández, F Jiménez; Johnson, McKenzie F; Jolli, Virat; Jonsell, Mats; Juliani, S Nur; Jung, Thomas S; Kapoor, Vena; Kappes, Heike; Kati, Vassiliki; Katovai, Eric; Kellner, Klaus; Kessler, Michael; Kirby, Kathryn R; Kittle, Andrew M; Knight, Mairi E; Knop, Eva; Kohler, Florian; Koivula, Matti; Kolb, Annette; Kone, Mouhamadou; Kőrösi, Ádám; Krauss, Jochen; Kumar, Ajith; Kumar, Raman; Kurz, David J; Kutt, Alex S; Lachat, Thibault; Lantschner, Victoria; Lara, Francisco; Lasky, Jesse R; Latta, Steven C; Laurance, William F; Lavelle, Patrick; Le Féon, Violette; LeBuhn, Gretchen; Légaré, Jean-Philippe; Lehouck, Valérie; Lencinas, María V; Lentini, Pia E; Letcher, Susan G; Li, Qi; Litchwark, Simon A; Littlewood, Nick A; Liu, Yunhui; Lo-Man-Hung, Nancy; López-Quintero, Carlos A; Louhaichi, Mounir; Lövei, Gabor L; Lucas-Borja, Manuel Esteban; Luja, Victor H; Luskin, Matthew S; MacSwiney G, M Cristina; Maeto, Kaoru; Magura, Tibor; Mallari, Neil Aldrin; Malone, Louise A; Malonza, Patrick K; Malumbres-Olarte, Jagoba; Mandujano, Salvador; Måren, Inger E; Marin-Spiotta, Erika; Marsh, Charles J; Marshall, E J P; Martínez, Eliana; Martínez Pastur, Guillermo; Moreno Mateos, David; Mayfield, Margaret M; Mazimpaka, Vicente; McCarthy, Jennifer L; McCarthy, Kyle P; McFrederick, Quinn S; McNamara, Sean; Medina, Nagore G; Medina, Rafael; Mena, Jose L; Mico, Estefania; Mikusinski, Grzegorz; Milder, Jeffrey C; Miller, James R; Miranda-Esquivel, Daniel R; Moir, Melinda L; Morales, Carolina L; Muchane, Mary N; Muchane, Muchai; Mudri-Stojnic, Sonja; Munira, A Nur; Muoñz-Alonso, Antonio; Munyekenye, B F; Naidoo, Robin; Naithani, A; Nakagawa, Michiko; Nakamura, Akihiro; Nakashima, Yoshihiro; Naoe, Shoji; Nates-Parra, Guiomar; Navarrete Gutierrez, Dario A; Navarro-Iriarte, Luis; Ndang'ang'a, Paul K; Neuschulz, Eike L; Ngai, Jacqueline T; Nicolas, Violaine; Nilsson, Sven G; Noreika, Norbertas; Norfolk, Olivia; Noriega, Jorge Ari; Norton, David A; Nöske, Nicole M; Nowakowski, A Justin; Numa, Catherine; O'Dea, Niall; O'Farrell, Patrick J; Oduro, William; Oertli, Sabine; Ofori-Boateng, Caleb; Oke, Christopher Omamoke; Oostra, Vicencio; Osgathorpe, Lynne M; Otavo, Samuel Eduardo; Page, Navendu V; Paritsis, Juan; Parra-H, Alejandro; Parry, Luke; Pe'er, Guy; Pearman, Peter B; Pelegrin, Nicolás; Pélissier, Raphaël; Peres, Carlos A; Peri, Pablo L; Persson, Anna S; Petanidou, Theodora; Peters, Marcell K; Pethiyagoda, Rohan S; Phalan, Ben; Philips, T Keith; Pillsbury, Finn C; Pincheira-Ulbrich, Jimmy; Pineda, Eduardo; Pino, Joan; Pizarro-Araya, Jaime; Plumptre, A J; Poggio, Santiago L; Politi, Natalia; Pons, Pere; Poveda, Katja; Power, Eileen F; Presley, Steven J; Proença, Vânia; Quaranta, Marino; Quintero, Carolina; Rader, Romina; Ramesh, B R; Ramirez-Pinilla, Martha P; Ranganathan, Jai; Rasmussen, Claus; Redpath-Downing, Nicola A; Reid, J Leighton; Reis, Yana T; Rey Benayas, José M; Rey-Velasco, Juan Carlos; Reynolds, Chevonne; Ribeiro, Danilo Bandini; Richards, Miriam H; Richardson, Barbara A; Richardson, Michael J; Ríos, Rodrigo Macip; Robinson, Richard; Robles, Carolina A; Römbke, Jörg; Romero-Duque, Luz Piedad; Rös, Matthias; Rosselli, Loreta; Rossiter, Stephen J; Roth, Dana S; Roulston, T'ai H; Rousseau, Laurent; Rubio, André V; Ruel, Jean-Claude; Sadler, Jonathan P; Sáfián, Szabolcs; Saldaña-Vázquez, Romeo A; Sam, Katerina; Samnegård, Ulrika; Santana, Joana; Santos, Xavier; Savage, Jade; Schellhorn, Nancy A; Schilthuizen, Menno; Schmiedel, Ute; Schmitt, Christine B; Schon, Nicole L; Schüepp, Christof; Schumann, Katharina; Schweiger, Oliver; Scott, Dawn M; Scott, Kenneth A; Sedlock, Jodi L; Seefeldt, Steven S; Shahabuddin, Ghazala; Shannon, Graeme; Sheil, Douglas; Sheldon, Frederick H; Shochat, Eyal; Siebert, Stefan J; Silva, Fernando A B; Simonetti, Javier A; Slade, Eleanor M; Smith, Jo; Smith-Pardo, Allan H; Sodhi, Navjot S; Somarriba, Eduardo J; Sosa, Ramón A; Soto Quiroga, Grimaldo; St-Laurent, Martin-Hugues; Starzomski, Brian M; Stefanescu, Constanti; Steffan-Dewenter, Ingolf; Stouffer, Philip C; Stout, Jane C; Strauch, Ayron M; Struebig, Matthew J; Su, Zhimin; Suarez-Rubio, Marcela; Sugiura, Shinji; Summerville, Keith S; Sung, Yik-Hei; Sutrisno, Hari; Svenning, Jens-Christian; Teder, Tiit; Threlfall, Caragh G; Tiitsaar, Anu; Todd, Jacqui H; Tonietto, Rebecca K; Torre, Ignasi; Tóthmérész, Béla; Tscharntke, Teja; Turner, Edgar C; Tylianakis, Jason M; Uehara-Prado, Marcio; Urbina-Cardona, Nicolas; Vallan, Denis; Vanbergen, Adam J; Vasconcelos, Heraldo L; Vassilev, Kiril; Verboven, Hans A F; Verdasca, Maria João; Verdú, José R; Vergara, Carlos H; Vergara, Pablo M; Verhulst, Jort; Virgilio, Massimiliano; Vu, Lien Van; Waite, Edward M; Walker, Tony R; Wang, Hua-Feng; Wang, Yanping; Watling, James I; Weller, Britta; Wells, Konstans; Westphal, Catrin; Wiafe, Edward D; Williams, Christopher D; Willig, Michael R; Woinarski, John C Z; Wolf, Jan H D; Wolters, Volkmar; Woodcock, Ben A; Wu, Jihua; Wunderle, Joseph M; Yamaura, Yuichi; Yoshikura, Satoko; Yu, Douglas W; Zaitsev, Andrey S; Zeidler, Juliane; Zou, Fasheng; Collen, Ben; Ewers, Rob M; Mace, Georgina M; Purves, Drew W; Scharlemann, Jörn P W; Purvis, Andy

2017-01-01

The PREDICTS project-Projecting Responses of Ecological Diversity In Changing Terrestrial Systems (www.predicts.org.uk)-has collated from published studies a large, reasonably representative database of comparable samples of biodiversity from multiple sites that differ in the nature or intensity of human impacts relating to land use. We have used this evidence base to develop global and regional statistical models of how local biodiversity responds to these measures. We describe and make freely available this 2016 release of the database, containing more than 3.2 million records sampled at over 26,000 locations and representing over 47,000 species. We outline how the database can help in answering a range of questions in ecology and conservation biology. To our knowledge, this is the largest and most geographically and taxonomically representative database of spatial comparisons of biodiversity that has been collated to date; it will be useful to researchers and international efforts wishing to model and understand the global status of biodiversity.

A novel paradigm for cell and molecule interaction ontology: from the CMM model to IMGT-ONTOLOGY

PubMed Central

2010-01-01

Background Biology is moving fast toward the virtuous circle of other disciplines: from data to quantitative modeling and back to data. Models are usually developed by mathematicians, physicists, and computer scientists to translate qualitative or semi-quantitative biological knowledge into a quantitative approach. To eliminate semantic confusion between biology and other disciplines, it is necessary to have a list of the most important and frequently used concepts coherently defined. Results We propose a novel paradigm for generating new concepts for an ontology, starting from model rather than developing a database. We apply that approach to generate concepts for cell and molecule interaction starting from an agent based model. This effort provides a solid infrastructure that is useful to overcome the semantic ambiguities that arise between biologists and mathematicians, physicists, and computer scientists, when they interact in a multidisciplinary field. Conclusions This effort represents the first attempt at linking molecule ontology with cell ontology, in IMGT-ONTOLOGY, the well established ontology in immunogenetics and immunoinformatics, and a paradigm for life science biology. With the increasing use of models in biology and medicine, the need to link different levels, from molecules to cells to tissues and organs, is increasingly important. PMID:20167082

Pathophysiology and biology of peritoneal carcinomatosis.

PubMed

Kusamura, Shigeki; Baratti, Dario; Zaffaroni, Nadia; Villa, Raffaella; Laterza, Barbara; Balestra, Maria Rosaria; Deraco, Marcello

2010-01-15

Peritoneal carcinomatosis represents a devastating form of cancer progression with a very poor prognosis. Its complex pathogenesis is represented by a dynamic process comprising several steps. To the best of our knowledge pathogenesis can be partly explained by 3 major molecular pathways: (1) dissemination from the primary tumor; (2) primary tumor of peritoneum; and (3) independent origins of the primary tumor and peritoneal implants. These are not mutually exclusive and combinations of different mechanisms could occur inside a single case. There are still several aspects which need explanation by future studies. A comprehensive understanding of molecular events involved in peritoneal carcinomatosis is of paramount importance and should be systematically pursued not only to identify novel strategies for the prevention of the condition, but also to obtain therapeutic advances, through the identification of surrogate markers of prognosis and development of future molecular targeted therapies.

Pathophysiology and biology of peritoneal carcinomatosis

PubMed Central

Kusamura, Shigeki; Baratti, Dario; Zaffaroni, Nadia; Villa, Raffaella; Laterza, Barbara; Balestra, Maria Rosaria; Deraco, Marcello

2010-01-01

Peritoneal carcinomatosis represents a devastating form of cancer progression with a very poor prognosis. Its complex pathogenesis is represented by a dynamic process comprising several steps. To the best of our knowledge pathogenesis can be partly explained by 3 major molecular pathways: (1) dissemination from the primary tumor; (2) primary tumor of peritoneum; and (3) independent origins of the primary tumor and peritoneal implants. These are not mutually exclusive and combinations of different mechanisms could occur inside a single case. There are still several aspects which need explanation by future studies. A comprehensive understanding of molecular events involved in peritoneal carcinomatosis is of paramount importance and should be systematically pursued not only to identify novel strategies for the prevention of the condition, but also to obtain therapeutic advances, through the identification of surrogate markers of prognosis and development of future molecular targeted therapies. PMID:21160812

Bone Quest - A Space-Based Science and Health Education Unit

NASA Technical Reports Server (NTRS)

Smith, Scott M.; David-Street, Janis E.; Abrams, Steve A.

2000-01-01

This proposal addresses the need for effective and innovative science and health education materials that focus on space bone biology and its implications for bone health on Earth. The focus of these materials, bone biology and health, will increase science knowledge as well as health awareness. Current investigations of the bone loss observed after long-duration space missions provide a link between studies of bone health in space, and studies of osteoporosis, a disease characterized by bone loss and progressive skeletal weakness. The overall goal of this project is to design and develop web-based and print-based materials for high school science students, that will address the following: a) knowledge of normal bone biology and bone biology in a microgravity environment; b) knowledge of osteoporosis; c) knowledge of treatment modalities for space- and Earth-based bone loss; and d} bone-related nutrition knowledge and behavior. To this end, we propose to design and develop a Bone Biology Tutorial which will instruct students about normal bone biology, bone biology in a microgravity environment, osteoporosis - its definition, detection, risk factors, and prevention, treatment modalities for space- and Earth-based bone loss, and the importance of nutrition in bone health. Particular emphasis will be placed on current trends in . adolescent nutrition, and their relationships to bone health. Additionally, we propose to design and develop two interactive nutrition/health ' education activities that will allow students to apply the information provided in the Bone Biology Tutorial. In the first, students will apply constructs provided in the Bone Biology Tutorial to design "Bone Health Plans" for space travelers.

Mining Rare Associations between Biological Ontologies

PubMed Central

Benites, Fernando; Simon, Svenja; Sapozhnikova, Elena

2014-01-01

The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations. PMID:24404165

Mining rare associations between biological ontologies.

PubMed

Benites, Fernando; Simon, Svenja; Sapozhnikova, Elena

2014-01-01

The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations.

Identification of differentially expressed genes in Monochamus alternatus digested with azadirachtin.

PubMed

Lin, Tong; Liu, Qisi; Chen, Jingxiang

2016-09-15

The pine sawyer beetle Monochamus alternatus Hope, a major forest insect pest, is the primary vector of the destructive forest pest pine wood nematode, Bursaphelenchus xylophilus. Azadirachtin, an active compound of neem, is biologically interesting because it represents a group of important, successful botanical pesticides. We provide insight into the molecular effects of azadirachtin on M. alternatus at the transcriptional level to provide clues about possible molecular-level targets and to establish a link between azadirachtin and insect global responses. We found that 920 and 9894 unique genes were significantly up- and down-regulated, respectively. We obtained expression patterns of the differentially expressed genes (DEGs), identifying 4247, 3488 and 7613 sequences that involved cellular components, molecular functions and biological processes, respectively, and showed that the DEGs were distributed among 50 Gene Ontology categories. The Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that the DEGs were enriched in 50 pathways. Detailed gene profile knowledge of the interaction of azadirachtin with M. alternatus should facilitate the development of more effective azadirachtin-based products against M. alternatus and other target Coleoptera. These results further enhance the value of azadirachtin as a potential insecticide of biological origin, as well as for other biological applications.

Identification of differentially expressed genes in Monochamus alternatus digested with azadirachtin

PubMed Central

Lin, Tong; Liu, Qisi; Chen, Jingxiang

2016-01-01

The pine sawyer beetle Monochamus alternatus Hope, a major forest insect pest, is the primary vector of the destructive forest pest pine wood nematode, Bursaphelenchus xylophilus. Azadirachtin, an active compound of neem, is biologically interesting because it represents a group of important, successful botanical pesticides. We provide insight into the molecular effects of azadirachtin on M. alternatus at the transcriptional level to provide clues about possible molecular-level targets and to establish a link between azadirachtin and insect global responses. We found that 920 and 9894 unique genes were significantly up- and down-regulated, respectively. We obtained expression patterns of the differentially expressed genes (DEGs), identifying 4247, 3488 and 7613 sequences that involved cellular components, molecular functions and biological processes, respectively, and showed that the DEGs were distributed among 50 Gene Ontology categories. The Encyclopedia of Genes and Genomes pathway enrichment analysis indicated that the DEGs were enriched in 50 pathways. Detailed gene profile knowledge of the interaction of azadirachtin with M. alternatus should facilitate the development of more effective azadirachtin-based products against M. alternatus and other target Coleoptera. These results further enhance the value of azadirachtin as a potential insecticide of biological origin, as well as for other biological applications. PMID:27629396

A Problem-Sorting Task Detects Changes in Undergraduate Biological Expertise over a Single Semester.

PubMed

Hoskinson, Anne-Marie; Maher, Jessica Middlemis; Bekkering, Cody; Ebert-May, Diane

2017-01-01

Calls for undergraduate biology reform share similar goals: to produce people who can organize, use, connect, and communicate about biological knowledge. Achieving these goals requires students to gain disciplinary expertise. Experts organize, access, and apply disciplinary knowledge differently than novices, and expertise is measurable. By asking introductory biology students to sort biological problems, we investigated whether they changed how they organized and linked biological ideas over one semester of introductory biology. We administered the Biology Card Sorting Task to 751 students enrolled in their first or second introductory biology course focusing on either cellular-molecular or organismal-population topics, under structured or unstructured sorting conditions. Students used a combination of superficial, deep, and yet-uncharacterized ways of organizing and connecting biological knowledge. In some cases, this translated to more expert-like ways of organizing knowledge over a single semester, best predicted by whether students were enrolled in their first or second semester of biology and by the sorting condition completed. In addition to illuminating differences between novices and experts, our results show that card sorting is a robust way of detecting changes in novices' biological expertise-even in heterogeneous populations of novice biology students over the time span of a single semester. © 2017 A.-M. Hoskinson et al. CBE—Life Sciences Education © 2017 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License(http://creativecommons.org/licenses/by-nc-sa/3.0).

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge

PubMed Central

Wagner, Florian

2015-01-01

Method Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. Results I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets. PMID:26575370

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge.

PubMed

Wagner, Florian

2015-01-01

Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets.

The Domains of Human Nutrition: The Importance of Nutrition Education in Academia and Medical Schools

PubMed Central

Donini, Lorenzo M.; Leonardi, Francesco; Rondanelli, Mariangela; Banderali, Giuseppe; Battino, Maurizio; Bertoli, Enrico; Bordoni, Alessandra; Brighenti, Furio; Caccialanza, Riccardo; Cairella, Giulia; Caretto, Antonio; Cena, Hellas; Gambarara, Manuela; Gentile, Maria Gabriella; Giovannini, Marcello; Lucchin, Lucio; Migliaccio, Pietro; Nicastro, Francesco; Pasanisi, Fabrizio; Piretta, Luca; Radrizzani, Danilo; Roggi, Carla; Rotilio, Giuseppe; Scalfi, Luca; Vettor, Roberto; Vignati, Federico; Battistini, Nino C.; Muscaritoli, Maurizio

2017-01-01

Human nutrition encompasses an extremely broad range of medical, social, commercial, and ethical domains and thus represents a wide, interdisciplinary scientific and cultural discipline. The high prevalence of both disease-related malnutrition and overweight/obesity represents an important risk factor for disease burden and mortality worldwide. It is the opinion of Federation of the Italian Nutrition Societies (FeSIN) that these two sides of the same coin, with their sociocultural background, are related to a low “nutritional culture” secondary, at least in part, to an insufficient academic training for health-care professionals (HCPs). Therefore, FeSIN created a study group, composed of delegates of all the federated societies and representing the different HCPs involved in human nutrition, with the aim of identifying and defining the domains of human nutrition in the attempt to more clearly define the cultural identity of human nutrition in an academically and professionally oriented perspective and to report the conclusions in a position paper. Three main domains of human nutrition, namely, basic nutrition, applied nutrition, and clinical nutrition, were identified. FeSIN has examined the areas of knowledge pertinent to human nutrition. Thirty-two items were identified, attributed to one or more of the three domains and ranked considering their diverse importance for academic training in the different domains of human nutrition. Finally, the study group proposed the attribution of the different areas of knowledge to the degree courses where training in human nutrition is deemed necessary (e.g., schools of medicine, biology, nursing, etc.). It is conceivable that, in the near future, a better integration of the professionals involved in the field of human nutrition will eventually occur based on the progressive consolidation of knowledge, competence, and skills in the different areas and domains of this discipline. PMID:28275609

NASA Biological Specimen Repository

NASA Technical Reports Server (NTRS)

McMonigal, K. A.; Pietrzyk, R. A.; Sams, C. F.; Johnson, M. A.

2010-01-01

The NASA Biological Specimen Repository (NBSR) was established in 2006 to collect, process, preserve and distribute spaceflight-related biological specimens from long duration ISS astronauts. This repository provides unique opportunities to study longitudinal changes in human physiology spanning may missions. The NBSR collects blood and urine samples from all participating ISS crewmembers who have provided informed consent. These biological samples are collected once before flight, during flight scheduled on flight days 15, 30, 60, 120 and within 2 weeks of landing. Postflight sessions are conducted 3 and 30 days after landing. The number of in-flight sessions is dependent on the duration of the mission. Specimens are maintained under optimal storage conditions in a manner that will maximize their integrity and viability for future research The repository operates under the authority of the NASA/JSC Committee for the Protection of Human Subjects to support scientific discovery that contributes to our fundamental knowledge in the area of human physiological changes and adaptation to a microgravity environment. The NBSR will institute guidelines for the solicitation, review and sample distribution process through establishment of the NBSR Advisory Board. The Advisory Board will be composed of representatives of all participating space agencies to evaluate each request from investigators for use of the samples. This process will be consistent with ethical principles, protection of crewmember confidentiality, prevailing laws and regulations, intellectual property policies, and consent form language. Operations supporting the NBSR are scheduled to continue until the end of U.S. presence on the ISS. Sample distribution is proposed to begin with selections on investigations beginning in 2017. The availability of the NBSR will contribute to the body of knowledge about the diverse factors of spaceflight on human physiology.

Direct Experience with Nature and the Development of Biological Knowledge

ERIC Educational Resources Information Center

Longbottom, Sarah E.; Slaughter, Virginia

2016-01-01

Research Findings: An emerging consensus is that casual, direct contact with nature influences the development of children's biological knowledge. Here we review the existing literature on this topic, focusing on the effects of (a) rural versus urban rearing environments and (b) pet ownership and care on children's biological concepts and…

Teacher Education and the New Biology

ERIC Educational Resources Information Center

Reiss, Michael J.

2006-01-01

Recent years have seen a growth not only in biological knowledge but also, and more significantly for teacher education, in the types of knowledge manifested in biology. No longer, therefore, is it adequate for teachers to retain a Mertonian or a Popperian conception of science. Today's teachers of science need also to be able to help their…

A Problem-Sorting Task Detects Changes in Undergraduate Biological Expertise over a Single Semester

ERIC Educational Resources Information Center

Hoskinson, Anne-Marie; Maher, Jessica Middlemis; Bekkering, Cody; Ebert-May, Diane

2017-01-01

Calls for undergraduate biology reform share similar goals: to produce people who can organize, use, connect, and communicate about biological knowledge. Achieving these goals requires students to gain disciplinary expertise. Experts organize, access, and apply disciplinary knowledge differently than novices, and expertise is measurable. By asking…

Investigating Lebanese Grade Seven Biology Teachers Mathematical Knowledge and Skills: A Case Study

ERIC Educational Resources Information Center

Raad, Nawal Abou; Chatila, Hanadi

2016-01-01

This paper investigates Lebanese grade 7 biology teachers' mathematical knowledge and skills, by exploring how they explain a visual representation in an activity depending on the mathematical concept "Function". Twenty Lebanese in-service biology teachers participated in the study, and were interviewed about their explanation for the…

Biology. Teacher's Guide. Investigations in Natural Science.

ERIC Educational Resources Information Center

Renner, John W.; And Others

Investigations in Natural Science is a program in secondary school biology, chemistry, and physics based upon the description of science as a quest for knowledge, not the knowledge itself. This teaching guide is designed for use with the 18 biology investigations found in the student manual. These investigations focus on concepts related to:…

Current knowledge and attitudes: Russian olive biology, ecology and management

Treesearch

Sharlene E. Sing; Kevin J. Delaney

2016-01-01

The primary goals of a two-day Russian olive symposium held in February 2014 were to disseminate current knowledge and identify data gaps regarding Russian olive biology and ecology, distributions, integrated management, and to ascertain the feasibility and acceptance of a proposed program for classical biological control of Russian olive. The symposium was...

Towards the engineering of in vitro systems.

PubMed

Hold, Christoph; Panke, Sven

2009-08-06

Synthetic biology aims at rationally implementing biological systems from scratch. Given the complexity of living systems and our current lack of understanding of many aspects of living cells, this is a major undertaking. The design of in vitro systems can be considerably easier, because they can consist of fewer constituents, are quasi time invariant, their parameter space can be better accessed and they can be much more easily perturbed and then analysed chemically and mathematically. However, even for simplified in vitro systems, following a comprehensively rational design procedure is still difficult. When looking at a comparatively simple system, such as a medium-sized enzymatic reaction network as it is represented by glycolysis, major issues such as a lack of comprehensive enzyme kinetics and of suitable knowledge on crucial design parameters remain. Nevertheless, in vitro systems are very suitable to overcome these obstacles and therefore well placed to act as a stepping stone to engineering living systems.

Active machine learning-driven experimentation to determine compound effects on protein patterns.

PubMed

Naik, Armaghan W; Kangas, Joshua D; Sullivan, Devin P; Murphy, Robert F

2016-02-03

High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experimentation could be used to learn accurate models for many conditions and targets without doing all possible experiments. We have previously described an active machine learning algorithm that can iteratively choose small sets of experiments to learn models of multiple effects. We now show that, with no prior knowledge and with liquid handling robotics and automated microscopy under its control, this learner accurately learned the effects of 48 chemical compounds on the subcellular localization of 48 proteins while performing only 29% of all possible experiments. The results represent the first practical demonstration of the utility of active learning-driven biological experimentation in which the set of possible phenotypes is unknown in advance.

Discover mouse gene coexpression landscapes using dictionary learning and sparse coding.

PubMed

Li, Yujie; Chen, Hanbo; Jiang, Xi; Li, Xiang; Lv, Jinglei; Peng, Hanchuan; Tsien, Joe Z; Liu, Tianming

2017-12-01

Gene coexpression patterns carry rich information regarding enormously complex brain structures and functions. Characterization of these patterns in an unbiased, integrated, and anatomically comprehensive manner will illuminate the higher-order transcriptome organization and offer genetic foundations of functional circuitry. Here using dictionary learning and sparse coding, we derived coexpression networks from the space-resolved anatomical comprehensive in situ hybridization data from Allen Mouse Brain Atlas dataset. The key idea is that if two genes use the same dictionary to represent their original signals, then their gene expressions must share similar patterns, thereby considering them as "coexpressed." For each network, we have simultaneous knowledge of spatial distributions, the genes in the network and the extent a particular gene conforms to the coexpression pattern. Gene ontologies and the comparisons with published gene lists reveal biologically identified coexpression networks, some of which correspond to major cell types, biological pathways, and/or anatomical regions.

Life is physics and chemistry and communication.

PubMed

Witzany, Guenther

2015-04-01

Manfred Eigen extended Erwin Schroedinger's concept of "life is physics and chemistry" through the introduction of information theory and cybernetic systems theory into "life is physics and chemistry and information." Based on this assumption, Eigen developed the concepts of quasispecies and hypercycles, which have been dominant in molecular biology and virology ever since. He insisted that the genetic code is not just used metaphorically: it represents a real natural language. However, the basics of scientific knowledge changed dramatically within the second half of the 20th century. Unfortunately, Eigen ignored the results of the philosophy of science discourse on essential features of natural languages and codes: a natural language or code emerges from populations of living agents that communicate. This contribution will look at some of the highlights of this historical development and the results relevant for biological theories about life. © 2014 New York Academy of Sciences.

Features of Knowledge Building in Biology: Understanding Undergraduate Students' Ideas about Molecular Mechanisms

ERIC Educational Resources Information Center

Southard, Katelyn; Wince, Tyler; Meddleton, Shanice; Bolger, Molly S.

2016-01-01

Research has suggested that teaching and learning in molecular and cellular biology (MCB) is difficult. We used a new lens to understand undergraduate reasoning about molecular mechanisms: the knowledge-integration approach to conceptual change. Knowledge integration is the dynamic process by which learners acquire new ideas, develop connections…

Ultra-Structure database design methodology for managing systems biology data and analyses

PubMed Central

Maier, Christopher W; Long, Jeffrey G; Hemminger, Bradley M; Giddings, Morgan C

2009-01-01

Background Modern, high-throughput biological experiments generate copious, heterogeneous, interconnected data sets. Research is dynamic, with frequently changing protocols, techniques, instruments, and file formats. Because of these factors, systems designed to manage and integrate modern biological data sets often end up as large, unwieldy databases that become difficult to maintain or evolve. The novel rule-based approach of the Ultra-Structure design methodology presents a potential solution to this problem. By representing both data and processes as formal rules within a database, an Ultra-Structure system constitutes a flexible framework that enables users to explicitly store domain knowledge in both a machine- and human-readable form. End users themselves can change the system's capabilities without programmer intervention, simply by altering database contents; no computer code or schemas need be modified. This provides flexibility in adapting to change, and allows integration of disparate, heterogenous data sets within a small core set of database tables, facilitating joint analysis and visualization without becoming unwieldy. Here, we examine the application of Ultra-Structure to our ongoing research program for the integration of large proteomic and genomic data sets (proteogenomic mapping). Results We transitioned our proteogenomic mapping information system from a traditional entity-relationship design to one based on Ultra-Structure. Our system integrates tandem mass spectrum data, genomic annotation sets, and spectrum/peptide mappings, all within a small, general framework implemented within a standard relational database system. General software procedures driven by user-modifiable rules can perform tasks such as logical deduction and location-based computations. The system is not tied specifically to proteogenomic research, but is rather designed to accommodate virtually any kind of biological research. Conclusion We find Ultra-Structure offers substantial benefits for biological information systems, the largest being the integration of diverse information sources into a common framework. This facilitates systems biology research by integrating data from disparate high-throughput techniques. It also enables us to readily incorporate new data types, sources, and domain knowledge with no change to the database structure or associated computer code. Ultra-Structure may be a significant step towards solving the hard problem of data management and integration in the systems biology era. PMID:19691849

Investigating Novice and Expert Conceptions of Genetically Modified Organisms

PubMed Central

Potter, Lisa M.; Bissonnette, Sarah A.; Knight, Jonathan D.; Tanner, Kimberly D.

2017-01-01

The aspiration of biology education is to give students tools to apply knowledge learned in the classroom to everyday life. Genetic modification is a real-world biological concept that relies on an in-depth understanding of the molecular behavior of DNA and proteins. This study investigated undergraduate biology students’ conceptions of genetically modified organisms (GMOs) when probed with real-world, molecular and cellular, and essentialist cues, and how those conceptions compared across biology expertise. We developed a novel written assessment tool and administered it to 120 non–biology majors, 154 entering biology majors, 120 advanced biology majors (ABM), and nine biology faculty. Results indicated that undergraduate biology majors rarely included molecular and cellular rationales in their initial explanations of GMOs. Despite ABM demonstrating that they have much of the biology knowledge necessary to understand genetic modification, they did not appear to apply this knowledge to explaining GMOs. Further, this study showed that all undergraduate student populations exhibited evidence of essentialist thinking while explaining GMOs, regardless of their level of biology training. Finally, our results suggest an association between scientifically accurate ideas and the application of molecular and cellular rationales, as well as an association between misconceptions and essentialist rationales. PMID:28821537

“Cancer – Educate to Prevent” – High-School Teachers, the New Promoters of Cancer Prevention Education Campaigns

PubMed Central

Barros, Ana; Moreira, Luís; Santos, Helena; Ribeiro, Nuno; Carvalho, Luís; Santos-Silva, Filipe

2014-01-01

Cancer is one of the leading causes of death worldwide, and thus represents a priority for national public health programs. Prevention has been assumed as the best strategy to reduce cancer burden, however most cancer prevention programs are implemented by healthcare professionals, which constrain range and educational impacts. We developed an innovative approach for cancer prevention education focused on high-school biology teachers, considered privileged mediators in the socialization processes. A training program, “Cancer, Educate to Prevent” was applied, so that the teachers were able to independently develop and implement prevention campaigns focused on students and school-related communities. The program encompassed different educational modules, ranging from cancer biology to prevention campaigns design. Fifty-four teachers were empowered to develop and implement their own cancer prevention campaigns in a population up to five thousands students. The success of the training program was assessed through quantitative evaluation – questionnaires focused on teachers' cancer knowledge and perceptions, before the intervention (pre-test) and immediately after (post-test). The projects developed and implemented by teachers were also evaluated regarding the intervention design, educational contents and impact on the students' knowledge about cancer. This study presents and discusses the results concerning the training program “Cancer, Educate to Prevent” and clearly shows a significant increase in teacher's cancer literacy (knowledge and perceptions) and teachers' acquired proficiency to develop and deliver cancer prevention campaigns with direct impact on students' knowledge about cancer. This pilot study reinforces the potential of high-school teachers and schools as cancer prevention promoters and opens a new perspective for the development and validation of cancer prevention education strategies, based upon focused interventions in restricted targets (students) through non-health professionals (teachers). PMID:24817168

Disaster preparedness in an Australian urban trauma center: staff knowledge and perceptions.

PubMed

Corrigan, Ellen; Samrasinghe, Iromi

2012-10-01

A substantial barrier to improving disaster preparedness in Australia is a lack of prescriptive national guidelines based on individual hospital capabilities. A recent literature review revealed that only one Australian hospital has published data regarding its current preparedness level. To establish baseline levels of disaster knowledge, preparedness, and willingness to respond to a disaster among one hospital's staff, and thus enable the implementation of national disaster preparedness guidelines based on realistic capabilities of individual hospitals. An anonymous questionnaire was distributed to individuals and departments that play key roles in the hospital's external disaster response. Questions concerned prior education and experience specific to disasters, general preparedness knowledge, perceived preparedness of themselves and their department, and willingness to respond to a disaster from a conventional and/or chemical, biological, or radiological incident. Responses were received from 140 individuals representing nine hospital departments. Eighty-three participants (59.3%) had previously received disaster education; 53 (37.9%) had attended a disaster simulation drill, and 18 (12.9%) had responded to an actual disaster. The average disaster preparedness knowledge score was 3.57 out of 10. The majority of respondents rated themselves as "not really" prepared and were "unsure" of their respective departments' level of preparedness. Most respondents indicated a willingness to participate in both a conventional incident involving burns and/or physical trauma, and an incident involving chemical, biological or radiological (CBR) weapons. Australian hospital staff are under-prepared to respond to a disaster because of a lack of education, insufficient simulation exercises, and limited disaster experience. The absence of specific national standards and guidelines through which individual hospitals can develop their capabilities further compounds the poverty in preparedness.

"Cancer--Educate to Prevent"--high-school teachers, the new promoters of cancer prevention education campaigns.

PubMed

Barros, Ana; Moreira, Luís; Santos, Helena; Ribeiro, Nuno; Carvalho, Luís; Santos-Silva, Filipe

2014-01-01

Cancer is one of the leading causes of death worldwide, and thus represents a priority for national public health programs. Prevention has been assumed as the best strategy to reduce cancer burden, however most cancer prevention programs are implemented by healthcare professionals, which constrain range and educational impacts. We developed an innovative approach for cancer prevention education focused on high-school biology teachers, considered privileged mediators in the socialization processes. A training program, "Cancer, Educate to Prevent" was applied, so that the teachers were able to independently develop and implement prevention campaigns focused on students and school-related communities. The program encompassed different educational modules, ranging from cancer biology to prevention campaigns design. Fifty-four teachers were empowered to develop and implement their own cancer prevention campaigns in a population up to five thousands students. The success of the training program was assessed through quantitative evaluation--questionnaires focused on teachers' cancer knowledge and perceptions, before the intervention (pre-test) and immediately after (post-test). The projects developed and implemented by teachers were also evaluated regarding the intervention design, educational contents and impact on the students' knowledge about cancer. This study presents and discusses the results concerning the training program "Cancer, Educate to Prevent" and clearly shows a significant increase in teacher's cancer literacy (knowledge and perceptions) and teachers' acquired proficiency to develop and deliver cancer prevention campaigns with direct impact on students' knowledge about cancer. This pilot study reinforces the potential of high-school teachers and schools as cancer prevention promoters and opens a new perspective for the development and validation of cancer prevention education strategies, based upon focused interventions in restricted targets (students) through non-health professionals (teachers).

Integrating Crop Growth Models with Whole Genome Prediction through Approximate Bayesian Computation.

PubMed

Technow, Frank; Messina, Carlos D; Totir, L Radu; Cooper, Mark

2015-01-01

Genomic selection, enabled by whole genome prediction (WGP) methods, is revolutionizing plant breeding. Existing WGP methods have been shown to deliver accurate predictions in the most common settings, such as prediction of across environment performance for traits with additive gene effects. However, prediction of traits with non-additive gene effects and prediction of genotype by environment interaction (G×E), continues to be challenging. Previous attempts to increase prediction accuracy for these particularly difficult tasks employed prediction methods that are purely statistical in nature. Augmenting the statistical methods with biological knowledge has been largely overlooked thus far. Crop growth models (CGMs) attempt to represent the impact of functional relationships between plant physiology and the environment in the formation of yield and similar output traits of interest. Thus, they can explain the impact of G×E and certain types of non-additive gene effects on the expressed phenotype. Approximate Bayesian computation (ABC), a novel and powerful computational procedure, allows the incorporation of CGMs directly into the estimation of whole genome marker effects in WGP. Here we provide a proof of concept study for this novel approach and demonstrate its use with synthetic data sets. We show that this novel approach can be considerably more accurate than the benchmark WGP method GBLUP in predicting performance in environments represented in the estimation set as well as in previously unobserved environments for traits determined by non-additive gene effects. We conclude that this proof of concept demonstrates that using ABC for incorporating biological knowledge in the form of CGMs into WGP is a very promising and novel approach to improving prediction accuracy for some of the most challenging scenarios in plant breeding and applied genetics.

Integrating Crop Growth Models with Whole Genome Prediction through Approximate Bayesian Computation

PubMed Central

Technow, Frank; Messina, Carlos D.; Totir, L. Radu; Cooper, Mark

2015-01-01

Genomic selection, enabled by whole genome prediction (WGP) methods, is revolutionizing plant breeding. Existing WGP methods have been shown to deliver accurate predictions in the most common settings, such as prediction of across environment performance for traits with additive gene effects. However, prediction of traits with non-additive gene effects and prediction of genotype by environment interaction (G×E), continues to be challenging. Previous attempts to increase prediction accuracy for these particularly difficult tasks employed prediction methods that are purely statistical in nature. Augmenting the statistical methods with biological knowledge has been largely overlooked thus far. Crop growth models (CGMs) attempt to represent the impact of functional relationships between plant physiology and the environment in the formation of yield and similar output traits of interest. Thus, they can explain the impact of G×E and certain types of non-additive gene effects on the expressed phenotype. Approximate Bayesian computation (ABC), a novel and powerful computational procedure, allows the incorporation of CGMs directly into the estimation of whole genome marker effects in WGP. Here we provide a proof of concept study for this novel approach and demonstrate its use with synthetic data sets. We show that this novel approach can be considerably more accurate than the benchmark WGP method GBLUP in predicting performance in environments represented in the estimation set as well as in previously unobserved environments for traits determined by non-additive gene effects. We conclude that this proof of concept demonstrates that using ABC for incorporating biological knowledge in the form of CGMs into WGP is a very promising and novel approach to improving prediction accuracy for some of the most challenging scenarios in plant breeding and applied genetics. PMID:26121133

Effects of biology teachers' professional knowledge and cognitive activation on students' achievement

NASA Astrophysics Data System (ADS)

Förtsch, Christian; Werner, Sonja; von Kotzebue, Lena; Neuhaus, Birgit J.

2016-11-01

This study examined the effects of teachers' biology-specific dimensions of professional knowledge - pedagogical content knowledge (PCK) and content knowledge (CK) - and cognitively activating biology instruction, as a feature of instructional quality, on students' learning. The sample comprised 39 German secondary school teachers whose lessons on the topic neurobiology were videotaped twice. Teachers' instruction was coded with regard to cognitive activation using a rating manual. Multilevel path analysis results showed a positive significant effect of cognitive activation on students' learning and an indirect effect of teachers' PCK on students' learning mediated through cognitive activation. These findings highlight the importance of PCK in preservice biology teachers' education. Items of the rating manual may be used to provide exemplars of concrete teaching situations during university seminars for preservice teacher education or professional development initiatives for in-service teachers.

The multiscale backbone of the human phenotype network based on biological pathways.

PubMed

Darabos, Christian; White, Marquitta J; Graham, Britney E; Leung, Derek N; Williams, Scott M; Moore, Jason H

2014-01-25

Networks are commonly used to represent and analyze large and complex systems of interacting elements. In systems biology, human disease networks show interactions between disorders sharing common genetic background. We built pathway-based human phenotype network (PHPN) of over 800 physical attributes, diseases, and behavioral traits; based on about 2,300 genes and 1,200 biological pathways. Using GWAS phenotype-to-genes associations, and pathway data from Reactome, we connect human traits based on the common patterns of human biological pathways, detecting more pleiotropic effects, and expanding previous studies from a gene-centric approach to that of shared cell-processes. The resulting network has a heavily right-skewed degree distribution, placing it in the scale-free region of the network topologies spectrum. We extract the multi-scale information backbone of the PHPN based on the local densities of the network and discarding weak connection. Using a standard community detection algorithm, we construct phenotype modules of similar traits without applying expert biological knowledge. These modules can be assimilated to the disease classes. However, we are able to classify phenotypes according to shared biology, and not arbitrary disease classes. We present examples of expected clinical connections identified by PHPN as proof of principle. We unveil a previously uncharacterized connection between phenotype modules and discuss potential mechanistic connections that are obvious only in retrospect. The PHPN shows tremendous potential to become a useful tool both in the unveiling of the diseases' common biology, and in the elaboration of diagnosis and treatments.

An engineering paradigm in the biomedical sciences: Knowledge as epistemic tool.

PubMed

Boon, Mieke

2017-10-01

In order to deal with the complexity of biological systems and attempts to generate applicable results, current biomedical sciences are adopting concepts and methods from the engineering sciences. Philosophers of science have interpreted this as the emergence of an engineering paradigm, in particular in systems biology and synthetic biology. This article aims at the articulation of the supposed engineering paradigm by contrast with the physics paradigm that supported the rise of biochemistry and molecular biology. This articulation starts from Kuhn's notion of a disciplinary matrix, which indicates what constitutes a paradigm. It is argued that the core of the physics paradigm is its metaphysical and ontological presuppositions, whereas the core of the engineering paradigm is the epistemic aim of producing useful knowledge for solving problems external to the scientific practice. Therefore, the two paradigms involve distinct notions of knowledge. Whereas the physics paradigm entails a representational notion of knowledge, the engineering paradigm involves the notion of 'knowledge as epistemic tool'. Copyright © 2017 Elsevier Ltd. All rights reserved.

Approximate geodesic distances reveal biologically relevant structures in microarray data.

PubMed

Nilsson, Jens; Fioretos, Thoas; Höglund, Mattias; Fontes, Magnus

2004-04-12

Genome-wide gene expression measurements, as currently determined by the microarray technology, can be represented mathematically as points in a high-dimensional gene expression space. Genes interact with each other in regulatory networks, restricting the cellular gene expression profiles to a certain manifold, or surface, in gene expression space. To obtain knowledge about this manifold, various dimensionality reduction methods and distance metrics are used. For data points distributed on curved manifolds, a sensible distance measure would be the geodesic distance along the manifold. In this work, we examine whether an approximate geodesic distance measure captures biological similarities better than the traditionally used Euclidean distance. We computed approximate geodesic distances, determined by the Isomap algorithm, for one set of lymphoma and one set of lung cancer microarray samples. Compared with the ordinary Euclidean distance metric, this distance measure produced more instructive, biologically relevant, visualizations when applying multidimensional scaling. This suggests the Isomap algorithm as a promising tool for the interpretation of microarray data. Furthermore, the results demonstrate the benefit and importance of taking nonlinearities in gene expression data into account.

Adrenocortical carcinoma: the dawn of a new era of genomic and molecular biology analysis.

PubMed

Armignacco, R; Cantini, G; Canu, L; Poli, G; Ercolino, T; Mannelli, M; Luconi, M

2018-05-01

Over the last decade, the development of novel and high penetrance genomic approaches to analyze biological samples has provided very new insights in the comprehension of the molecular biology and genetics of tumors. The use of these techniques, consisting of exome sequencing, transcriptome, miRNome, chromosome alteration, genome, and epigenome analysis, has also been successfully applied to adrenocortical carcinoma (ACC). In fact, the analysis of large cohorts of patients allowed the stratification of ACC with different patterns of molecular alterations, associated with different outcomes, thus providing a novel molecular classification of the malignancy to be associated with the classical pathological analysis. Improving our knowledge about ACC molecular features will result not only in a better diagnostic and prognostic accuracy, but also in the identification of more specific therapeutic targets for the development of more effective pharmacological anti-cancer approaches. In particular, the specific molecular alteration profiles identified in ACC may represent targetable events by the use of already developed or newly designed drugs enabling a better and more efficacious management of the ACC patient in the context of new frontiers of personalized precision medicine.

Calcium Orthophosphates in Nature, Biology and Medicine

PubMed Central

Dorozhkin, Sergey V.

2009-01-01

The present overview is intended to point the readers’ attention to the important subject of calcium orthophosphates. These materials are of the special significance because they represent the inorganic part of major normal (bones, teeth and dear antlers) and pathological (i.e. those appearing due to various diseases) calcified tissues of mammals. Due to a great chemical similarity with the biological calcified tissues, many calcium orthophosphates possess remarkable biocompatibility and bioactivity. Materials scientists use this property extensively to construct artificial bone grafts that are either entirely made of or only surface-coated with the biologically relevant calcium ortho-phosphates. For example, self-setting hydraulic cements made of calcium orthophosphates are helpful in bone repair, while titanium substitutes covered by a surface layer of calcium orthophosphates are used for hip joint endoprostheses and as tooth substitutes. Porous scaffolds made of calcium orthophosphates are very promising tools for tissue engineering applications. In addition, technical grade calcium orthophosphates are very popular mineral fertilizers. Thus ere calcium orthophosphates are of great significance for humankind and, in this paper, an overview on the current knowledge on this subject is provided.

Adaptable data management for systems biology investigations

PubMed Central

Boyle, John; Rovira, Hector; Cavnor, Chris; Burdick, David; Killcoyne, Sarah; Shmulevich, Ilya

2009-01-01

Background Within research each experiment is different, the focus changes and the data is generated from a continually evolving barrage of technologies. There is a continual introduction of new techniques whose usage ranges from in-house protocols through to high-throughput instrumentation. To support these requirements data management systems are needed that can be rapidly built and readily adapted for new usage. Results The adaptable data management system discussed is designed to support the seamless mining and analysis of biological experiment data that is commonly used in systems biology (e.g. ChIP-chip, gene expression, proteomics, imaging, flow cytometry). We use different content graphs to represent different views upon the data. These views are designed for different roles: equipment specific views are used to gather instrumentation information; data processing oriented views are provided to enable the rapid development of analysis applications; and research project specific views are used to organize information for individual research experiments. This management system allows for both the rapid introduction of new types of information and the evolution of the knowledge it represents. Conclusion Data management is an important aspect of any research enterprise. It is the foundation on which most applications are built, and must be easily extended to serve new functionality for new scientific areas. We have found that adopting a three-tier architecture for data management, built around distributed standardized content repositories, allows us to rapidly develop new applications to support a diverse user community. PMID:19265554

A convenient dichotomy: critical eyes on the limits to biological knowledge

NASA Astrophysics Data System (ADS)

Milne, Catherine

2011-06-01

In The Secret Identity of a Biology Textbook: straight and naturally sexed, Jesse Bazzul and Heather Sykes conduct a case study of a biology textbook as an oppressive instructional material. Using queer theory they explore how the text of the biology textbook produces "truths" about sex, gender, and sexuality. Their analysis is complemented by the Forum papers by Jay Lemke and Francis Broadway who broaden the analysis examining the way that what counts as knowledge in science is a political decision while also encouraging authors, including Bazzul and Sykes, to also look critically at their own theoretical lenses. In this paper I pull together their ideas while exploring cultural contexts for a more nuanced representation of biological knowledge and the politics of what it means to know science.

Using a "Primer Unit" in an Introductory Biology Course: "A Soft Landing"

ERIC Educational Resources Information Center

Marbach-Ad, Gili; Ribke, Melina; Gershoni, Jonathan M.

2006-01-01

This study aimed to facilitate students' entrance to an introductory cell biology course for biology majors. The most prominent difficulty in this introductory course, is students' poor background-knowledge, such as a lack of understanding of very basic concepts and terms, and the huge differences in students' background knowledge. In order to…

Public Understanding of Plant Biology: Voices from the Bottom of the Garden

ERIC Educational Resources Information Center

Watts, Mike

2015-01-01

Many household gardeners accumulate considerable knowledge of plant biology through a range of informal learning sources. This knowledge seldom relates to school biology and is driven by interest, keen motivation and what is termed here "vital relevance." A small opportunity sample of 12 gardeners (6 M, 6 F) is interviewed in terms of…

A Knowledge Base for Teaching Biology Situated in the Context of Genetic Testing

ERIC Educational Resources Information Center

van der Zande, Paul; Waarlo, Arend Jan; Brekelmans, Mieke; Akkerman, Sanne F.; Vermunt, Jan D.

2011-01-01

Recent developments in the field of genomics will impact the daily practice of biology teachers who teach genetics in secondary education. This study reports on the first results of a research project aimed at enhancing biology teacher knowledge for teaching genetics in the context of genetic testing. The increasing body of scientific knowledge…

Verbal Final Exam in Introductory Biology Yields Gains in Student Content Knowledge and Longitudinal Performance

ERIC Educational Resources Information Center

Luckie, Douglas B.; Rivkin, Aaron M.; Aubry, Jacob R.; Marengo, Benjamin J.; Creech, Leah R.; Sweeder, Ryan D.

2013-01-01

We studied gains in student learning over eight semesters in which an introductory biology course curriculum was changed to include optional verbal final exams (VFs). Students could opt to demonstrate their mastery of course material via structured oral exams with the professor. In a quantitative assessment of cell biology content knowledge,…

Thinking about Digestive System in Early Childhood: A Comparative Study about Biological Knowledge

ERIC Educational Resources Information Center

AHI, Berat

2017-01-01

The current study aims to explore how children explain the concepts of biology and how biological knowledge develops across ages by focusing on the structure and functions of the digestive system. The study was conducted with 60 children. The data were collected through the interviews conducted within a think-aloud protocol. The interview data…

Representations of the Nature of Scientific Knowledge in Turkish Biology Textbooks

ERIC Educational Resources Information Center

Irez, Serhat

2016-01-01

Considering the impact of textbooks on learning, this study set out to assess representations of the nature of scientific knowledge in Turkish 9th grade biology textbooks. To this end, the ten most commonly used 9th grade biology textbooks were analyzed. A qualitative research approach was utilized and the textbooks were analyzed using…

Student Perceived and Determined Knowledge of Biology Concepts in an Upper-Level Biology Course

PubMed Central

Montplaisir, Lisa

2014-01-01

Students who lack metacognitive skills can struggle with the learning process. To be effective learners, students should recognize what they know and what they do not know. This study examines the relationship between students’ perception of their knowledge and determined knowledge in an upper-level biology course utilizing a pre/posttest approach. Significant differences in students’ perception of their knowledge and their determined knowledge exist at the beginning (pretest) and end (posttest) of the course. Alignment between student perception and determined knowledge was significantly more accurate on the posttest compared with the pretest. Students whose determined knowledge was in the upper quartile had significantly better alignment between their perception and determined knowledge on the pre- and posttest than students in the lower quartile. No difference exists between how students perceived their knowledge between upper- and lower-quartile students. There was a significant difference in alignment of perception and determined knowledge between males and females on the posttest, with females being more accurate in their perception of knowledge. This study provides evidence of discrepancies that exist between what students perceive they know and what they actually know. PMID:26086662

Reputation-based collaborative network biology.

PubMed

Binder, Jean; Boue, Stephanie; Di Fabio, Anselmo; Fields, R Brett; Hayes, William; Hoeng, Julia; Park, Jennifer S; Peitsch, Manuel C

2015-01-01

A pilot reputation-based collaborative network biology platform, Bionet, was developed for use in the sbv IMPROVER Network Verification Challenge to verify and enhance previously developed networks describing key aspects of lung biology. Bionet was successful in capturing a more comprehensive view of the biology associated with each network using the collective intelligence and knowledge of the crowd. One key learning point from the pilot was that using a standardized biological knowledge representation language such as BEL is critical to the success of a collaborative network biology platform. Overall, Bionet demonstrated that this approach to collaborative network biology is highly viable. Improving this platform for de novo creation of biological networks and network curation with the suggested enhancements for scalability will serve both academic and industry systems biology communities.

"The evil virus cell": Students‘ knowledge and beliefs about viruses

PubMed Central

Enzinger, Sonja M.; Fink, Andreas

2017-01-01

Education about virus biology at school is of pivotal interest to raise public awareness concerning means of disease transmission and, thus, methods to prevent infection, and to reduce unnecessary antibiotic treatment due to patient pressure on physicians in case of viral diseases such as influenza. This study aimed at making visible the knowledge of Austrian high school and university students with respect to virus biology, virus structure and health-education issues. The data presented here stem from comprehensive questionnaire analyses, including the task to draw a virus, from a cross-sectional study with 133 grade 7 and 199 grade 10 high school students, and 133 first-year biology and 181 first-year non-biology university students. Analyses were performed both quantitatively and qualitatively. ANOVA revealed a highly significant group effect for total knowledge relating to virus biology and health issues (F(3, 642) = 44.17, p < 0.01, η2p = 0.17). Specific post-hoc tests by means of the Tukey test showed significant differences between all groups (p < .01) with the exception of 1st year non-biology students and grade 10 high school students. Students enrolled in university-level biology outperformed all other groups, even though they had not yet encountered this topic at their courses; part of this phenomenon might be due to their affinity for learning about biological topics. However, even many first-year biology students had a high number of severe misconceptions, e.g., defining a virus as a pro- or eukaryotic cell, or falsely naming malaria as a viral disease. Since there was no significant difference in virus-related knowledge between high schools, virus biology seems to have been taught similarly among the tested schools. However, the majority of participants stated that the virus-related knowledge they had acquired at school was not sufficient. Based on the results presented here we urgently suggest improving and intensifying teaching this topic at school, since virus-related knowledge was by far too fragmentary among many participants. Such lack of health-relevant knowledge may contribute to pressure on physicians by patients to unnecessarily prescribe antibiotics, and possibly lead to potentially dangerous neglect concerning vaccination. The effectiveness of newly developed virus-related teaching units and material could be tested with the instrument used here. PMID:28350815

"The evil virus cell": Students' knowledge and beliefs about viruses.

PubMed

Simon, Uwe K; Enzinger, Sonja M; Fink, Andreas

2017-01-01

Education about virus biology at school is of pivotal interest to raise public awareness concerning means of disease transmission and, thus, methods to prevent infection, and to reduce unnecessary antibiotic treatment due to patient pressure on physicians in case of viral diseases such as influenza. This study aimed at making visible the knowledge of Austrian high school and university students with respect to virus biology, virus structure and health-education issues. The data presented here stem from comprehensive questionnaire analyses, including the task to draw a virus, from a cross-sectional study with 133 grade 7 and 199 grade 10 high school students, and 133 first-year biology and 181 first-year non-biology university students. Analyses were performed both quantitatively and qualitatively. ANOVA revealed a highly significant group effect for total knowledge relating to virus biology and health issues (F(3, 642) = 44.17, p < 0.01, η2p = 0.17). Specific post-hoc tests by means of the Tukey test showed significant differences between all groups (p < .01) with the exception of 1st year non-biology students and grade 10 high school students. Students enrolled in university-level biology outperformed all other groups, even though they had not yet encountered this topic at their courses; part of this phenomenon might be due to their affinity for learning about biological topics. However, even many first-year biology students had a high number of severe misconceptions, e.g., defining a virus as a pro- or eukaryotic cell, or falsely naming malaria as a viral disease. Since there was no significant difference in virus-related knowledge between high schools, virus biology seems to have been taught similarly among the tested schools. However, the majority of participants stated that the virus-related knowledge they had acquired at school was not sufficient. Based on the results presented here we urgently suggest improving and intensifying teaching this topic at school, since virus-related knowledge was by far too fragmentary among many participants. Such lack of health-relevant knowledge may contribute to pressure on physicians by patients to unnecessarily prescribe antibiotics, and possibly lead to potentially dangerous neglect concerning vaccination. The effectiveness of newly developed virus-related teaching units and material could be tested with the instrument used here.

Teaching statistics in biology: using inquiry-based learning to strengthen understanding of statistical analysis in biology laboratory courses.

PubMed

Metz, Anneke M

2008-01-01

There is an increasing need for students in the biological sciences to build a strong foundation in quantitative approaches to data analyses. Although most science, engineering, and math field majors are required to take at least one statistics course, statistical analysis is poorly integrated into undergraduate biology course work, particularly at the lower-division level. Elements of statistics were incorporated into an introductory biology course, including a review of statistics concepts and opportunity for students to perform statistical analysis in a biological context. Learning gains were measured with an 11-item statistics learning survey instrument developed for the course. Students showed a statistically significant 25% (p < 0.005) increase in statistics knowledge after completing introductory biology. Students improved their scores on the survey after completing introductory biology, even if they had previously completed an introductory statistics course (9%, improvement p < 0.005). Students retested 1 yr after completing introductory biology showed no loss of their statistics knowledge as measured by this instrument, suggesting that the use of statistics in biology course work may aid long-term retention of statistics knowledge. No statistically significant differences in learning were detected between male and female students in the study.

Investigating Undergraduate Students’ Use of Intuitive Reasoning and Evolutionary Knowledge in Explanations of Antibiotic Resistance

PubMed Central

Richard, Melissa; Coley, John D.; Tanner, Kimberly D.

2017-01-01

Natural selection is a central concept throughout biology; however, it is a process frequently misunderstood. Bacterial resistance to antibiotic medications provides a contextual example of the relevance of evolutionary theory and is also commonly misunderstood. While research has shed light on student misconceptions of natural selection, minimal study has focused on misconceptions of antibiotic resistance. Additionally, research has focused on the degree to which misconceptions may be based in the complexity of biological information or in pedagogical choices, rather than in deep-seated cognitive patterns. Cognitive psychology research has established that humans develop early intuitive assumptions to make sense of the world. In this study, we used a written assessment tool to investigate undergraduate students’ misconceptions of antibiotic resistance, use of intuitive reasoning, and application of evolutionary knowledge to antibiotic resistance. We found a majority of students produced and agreed with misconceptions, and intuitive reasoning was present in nearly all students’ written explanations. Acceptance of a misconception was significantly associated with production of a hypothesized form of intuitive thinking (all p ≤ 0.05). Intuitive reasoning may represent a subtle but innately appealing linguistic shorthand, and instructor awareness of intuitive reasoning’s relation to student misunderstandings has potential for addressing persistent misconceptions. PMID:28821540

Conceptual Demand of Practical Work in Science Curricula. A Methodological Approach

NASA Astrophysics Data System (ADS)

Ferreira, Sílvia; Morais, Ana M.

2014-02-01

This article addresses the issue of the level of complexity of practical work in science curricula and is focused on the discipline of Biology and Geology at high school. The level of complexity is seen in terms of the emphasis on and types of practical work and, most importantly, in terms of its level of conceptual demand as given by the complexity of scientific knowledge, the degree of inter-relation between knowledges, and the complexity of cognitive skills. The study also analyzes recontextualizing processes that may occur within the official recontextualizing field. The study is psychologically and sociologically grounded, particularly on Bernstein's theory of pedagogic discourse. It uses a mixed methodology. The results show that practical work is poorly represented in the curriculum, particularly in the case of laboratory work. The level of conceptual demand of practical work varies according to the text under analysis, between the two subjects Biology and Geology, and, within each of them, between general and specific guidelines. Aspects studied are not clearly explicated to curriculum receivers (teachers and textbooks authors). The meaning of these findings is discussed in the article. In methodological terms, the study explores assumptions used in the analysis of the level of conceptual demand and presents innovative instruments constructed for developing this analysis.

Contribution to the knowledge of Saprinus Erichson, 1834 of forensic relevance from Lebanon (Coleoptera, Histeridae)

PubMed Central

Shayya, Salman; Dégallier, Nicolas; Nel, André; Azar, Dany; Lackner, Tomáš

2018-01-01

Abstract Many histerid beetles are necrophilous on carrion during both active and advanced stages of decomposition. In this study, 13 species of Saprinus were recorded on carrion from Lebanon, containing eight that are new for the Lebanese fauna. The following Saprinus species are newly recorded from Lebanon: 1) Saprinus (S.) caerulescens caerulescens (Hoffmann, 1803); 2) S. (S.) calatravensis Fuente, 1899; 3) S. (S.) chalcites (Illiger, 1807); 4) S. (S.) godet (Brullé, 1832); 5) S. (S.) maculatus (P. Rossi, 1792); 6) S. (S.) strigil Marseul, 1855; 7) S. (S.) submarginatus J. Sahlberg, 1913; and 8) S. (S.) tenuistrius sparsutus Solsky, 1876. The peak activity was recorded, key for the species is provided, and habitus images and male genitalia are illustrated in order to facilitate their taxonomic identifications. Saprinus species are diverse and common on animal carcass; they were likewise collected from a human cadaver in Lebanon. Preliminary comments on biology and distribution of the studied species are given. Our paper represents the first faunistic study on Histeridae from Lebanon. A rigorous research program regarding the biology of Saprinus in Lebanon and the neighbouring countries would greatly improve the knowledge of the diversity, activity, and possible forensic value of Saprinus. PMID:29670426

Do biological-based strategies hold promise to biofouling control in MBRs?

PubMed

Malaeb, Lilian; Le-Clech, Pierre; Vrouwenvelder, Johannes S; Ayoub, George M; Saikaly, Pascal E

2013-10-01

Biofouling in membrane bioreactors (MBRs) remains a primary challenge for their wider application, despite the growing acceptance of MBRs worldwide. Research studies on membrane fouling are extensive in the literature, with more than 200 publications on MBR fouling in the last 3 years; yet, improvements in practice on biofouling control and management have been remarkably slow. Commonly applied cleaning methods are only partially effective and membrane replacement often becomes frequent. The reason for the slow advancement in successful control of biofouling is largely attributed to the complex interactions of involved biological compounds and the lack of representative-for-practice experimental approaches to evaluate potential effective control strategies. Biofouling is driven by microorganisms and their associated extra-cellular polymeric substances (EPS) and microbial products. Microorganisms and their products convene together to form matrices that are commonly treated as a black box in conventional control approaches. Biological-based antifouling strategies seem to be a promising constituent of an effective integrated control approach since they target the essence of biofouling problems. However, biological-based strategies are in their developmental phase and several questions should be addressed to set a roadmap for translating existing and new information into sustainable and effective control techniques. This paper investigates membrane biofouling in MBRs from the microbiological perspective to evaluate the potential of biological-based strategies in offering viable control alternatives. Limitations of available control methods highlight the importance of an integrated anti-fouling approach including biological strategies. Successful development of these strategies requires detailed characterization of microorganisms and EPS through the proper selection of analytical tools and assembly of results. Existing microbiological/EPS studies reveal a number of implications as well as knowledge gaps, warranting future targeted research. Systematic and representative microbiological studies, complementary utilization of molecular and biofilm characterization tools, standardized experimental methods and validation of successful biological-based antifouling strategies for MBR applications are needed. Specifically, in addition, linking these studies to relevant operational conditions in MBRs is an essential step to ultimately develop a better understanding and more effective and directed control strategy for biofouling. Copyright © 2013 Elsevier Ltd. All rights reserved.

Patients' Concerns and Perceptions Regarding Biologic Therapies in Ankylosing Spondylitis: Insights from a Large-Scale Survey of Social Media Platforms.

PubMed

Dzubur, Eldin; Khalil, Carine; Almario, Christopher V; Noah, Benjamin; Minhas, Deeba; Ishimori, Mariko; Arnold, Corey; Park, Yujin; Kay, Jonathan; Weisman, Michael H; Spiegel, Brennan M R

2018-05-21

Few studies have examined ankylosing spondylitis (AS) patients' concerns and perceptions of biologic therapies outside of traditional surveys. In this study, we used social media data to examine AS patients' knowledge, attitudes, and beliefs regarding biologic therapies. We collected posts from 601 social media sites made between 1/1/06-4/26/17. Each post mentioned both an AS keyword and a biologic. To explore themes within the collection in an unsupervised manner, a latent Dirichlet allocation topic model was fit to the dataset. Each discovered topic was represented as a discrete distribution over the words in the collection, similar to a word cloud. The topics were manually reviewed to identify themes, which were confirmed with thematic data analysis. We examined 27,416 social media posts and found 112 themes. The majority of themes (60%, 67/112) focused on discussions surrounding AS treatment. Other themes including psychological impact of AS, reporting of medical literature, and AS disease consequences accounted for the remaining 40% (45/112). Within AS treatment discussions, most topics (54%) involved biologics, and most subthemes (78%) centered on side-effects (e.g., fatigue, allergic reactions), biologic attributes (e.g., dosing, frequency), and concerns with biologic use (e.g., increased cancer risk). Additional implicit patient needs (e.g., support) were identified using qualitative analyses. Social media reveals a dynamic range of themes governing AS patients' experience and choice with biologics. The complexity of selecting among biologics and navigating their risk-benefit profiles suggests merit in creating online tailored decision-tools to support patients' decision-making with AS biologic therapies. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Cambrian archaeocyathan metazoans: revision of morphological characters and standardization of genus descriptions to establish an online identification tool.

PubMed Central

Kerner, Adeline; Debrenne, Françoise; Vignes-Lebbe, Régine

2011-01-01

Abstract Archaeocyatha represent the oldest calcified sponges and the first metazoans to build bioconstructions in association with calcimicrobes. They are a key group in biology, evolutionary studies, biostratigraphy, paleoecology and paleogeography of the early Cambrian times. The establishing of a new standardized terminology for archaeocyathans description has permitted the creation of the first knowledge base in English including descriptions of all archaeocyathan genera. This base, using the XPER² software package, is an integral part of the -Archaeocyatha- a knowledge base website, freely available at url http://www.infosyslab.fr/archaeocyatha. The website is composed of common information about Archaeocyatha, general remarks about the knowledge base, the description of the 307 genera recognized with images of type-specimens of type-species for each genus, as well as additional morphological data, an interactive free access key and its user guide. The automatic analysis and comparison of the digitized descriptions have identified some genera with highly similar morphology. These results are a great help for future taxonomic revisions and suggest a number of possible synonymies that require further study. PMID:22207818

Life beyond the limits of knowledge: crystalline life in the popular science of Desiderius Papp (1895-1993).

PubMed

Brandstetter, Thomas

2012-10-01

The aim of this article is to show how, and in which context, astrobiological reasoning was employed before the establishment of astrobiology as a scientific discipline. By way of an example, I will discuss a popular science book published in 1931 by the Hungarian journalist Desiderius Papp. The author claims that this book represents an innovation in astrobiological reasoning, as it draws on contemporary biological research to conduct thought experiments, thereby coming up with concrete forms of possible extraterrestrial life. One of the most interesting of these forms was crystalline life. After a short overview on the history of this concept, this article will show how Papp drew on recent research by Otto Lehmann on liquid crystals to convey the idea that life may be based on other elements than carbon. The author concludes by arguing that popular science did not only make specialist knowledge accessible to a general public but also served to probe the limits of knowledge and point toward the situatedness of established categories and definitions.

Requirements for the formal representation of pathophysiology mechanisms by clinicians

PubMed Central

Helvensteijn, M.; Kokash, N.; Martorelli, I.; Sarwar, D.; Islam, S.; Grenon, P.; Hunter, P.

2016-01-01

Knowledge of multiscale mechanisms in pathophysiology is the bedrock of clinical practice. If quantitative methods, predicting patient-specific behaviour of these pathophysiology mechanisms, are to be brought to bear on clinical decision-making, the Human Physiome community and Clinical community must share a common computational blueprint for pathophysiology mechanisms. A number of obstacles stand in the way of this sharing—not least the technical and operational challenges that must be overcome to ensure that (i) the explicit biological meanings of the Physiome's quantitative methods to represent mechanisms are open to articulation, verification and study by clinicians, and that (ii) clinicians are given the tools and training to explicitly express disease manifestations in direct contribution to modelling. To this end, the Physiome and Clinical communities must co-develop a common computational toolkit, based on this blueprint, to bridge the representation of knowledge of pathophysiology mechanisms (a) that is implicitly depicted in electronic health records and the literature, with (b) that found in mathematical models explicitly describing mechanisms. In particular, this paper makes use of a step-wise description of a specific disease mechanism as a means to elicit the requirements of representing pathophysiological meaning explicitly. The computational blueprint developed from these requirements addresses the Clinical community goals to (i) organize and manage healthcare resources in terms of relevant disease-related knowledge of mechanisms and (ii) train the next generation of physicians in the application of quantitative methods relevant to their research and practice. PMID:27051514

Influence of using challenging tasks in biology classrooms on students' cognitive knowledge structure: an empirical video study

NASA Astrophysics Data System (ADS)

Nawani, Jigna; Rixius, Julia; Neuhaus, Birgit J.

2016-08-01

Empirical analysis of secondary biology classrooms revealed that, on average, 68% of teaching time in Germany revolved around processing tasks. Quality of instruction can thus be assessed by analyzing the quality of tasks used in classroom discourse. This quasi-experimental study analyzed how teachers used tasks in 38 videotaped biology lessons pertaining to the topic 'blood and circulatory system'. Two fundamental characteristics used to analyze tasks include: (1) required cognitive level of processing (e.g. low level information processing: repetiition, summary, define, classify and high level information processing: interpret-analyze data, formulate hypothesis, etc.) and (2) complexity of task content (e.g. if tasks require use of factual, linking or concept level content). Additionally, students' cognitive knowledge structure about the topic 'blood and circulatory system' was measured using student-drawn concept maps (N = 970 students). Finally, linear multilevel models were created with high-level cognitive processing tasks and higher content complexity tasks as class-level predictors and students' prior knowledge, students' interest in biology, and students' interest in biology activities as control covariates. Results showed a positive influence of high-level cognitive processing tasks (β = 0.07; p < .01) on students' cognitive knowledge structure. However, there was no observed effect of higher content complexity tasks on students' cognitive knowledge structure. Presented findings encourage the use of high-level cognitive processing tasks in biology instruction.

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

PubMed

Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data

PubMed Central

Seok, Junhee; Davis, Ronald W.; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn’t been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge. PMID:25933378

Designing vaccines based on biology of human dendritic cell subsets

PubMed Central

Palucka, Karolina; Banchereau, Jacques; Mellman, Ira

2010-01-01

The effective vaccines developed against a variety of infectious agents, including polio, measles and Hepatitis B, represent major achievements in medicine. These vaccines, usually composed of microbial antigens, are often associated with an adjuvant that activates dendritic cells (DCs). Many infectious diseases are still in need of an effective vaccine including HIV, malaria, hepatitis C and tuberculosis. In some cases, the induction of cellular rather than humoral responses may be more important as the goal is to control and eliminate the existing infection rather than to prevent it. Our increased understanding of the mechanisms of antigen presentation, particularly with the description of DC subsets with distinct functions, as well as their plasticity in responding to extrinsic signals, represent opportunities to develop novel vaccines. In addition, we foresee that this increased knowledge will permit us to design vaccines that will reprogram the immune system to intervene therapeutically in cancer, allergy and autoimmunity. PMID:21029958

A look into the Medical and Veterinary Entomology crystal ball.

PubMed

Dantas-Torres, F; Cameron, M M; Colwell, D D; Otranto, D

2014-08-01

Medical and Veterinary Entomology (MVE) represents a leading periodical in its field and covers many aspects of the biology and control of insects, ticks, mites and other arthropods of medical and veterinary importance. Since the first issue of the journal, researchers working in both developed and developing countries have published in MVE, with direct impact on current knowledge in the field. An increasing number of articles dealing with the epidemiology and transmission of vector-borne pathogens have been published in MVE, reflecting rapid changes in vector distribution, pathogen transmission and host-arthropod interactions. This article represents a gaze into the crystal ball in which we identify areas of increasing interest, discuss the main changes that have occurred in the epidemiology of parasitic arthropods since the first issue of MVE, and predict the principal scientific topics that might arise in the next 25 years for scientists working in medical and veterinary entomology. © 2014 The Royal Entomological Society.

Cancer heterogeneity: origins and implications for genetic association studies

PubMed Central

Urbach, Davnah; Lupien, Mathieu; Karagas, Margaret R.; Moore, Jason H.

2012-01-01

Genetic association studies have become standard approaches to characterize the genetic and epigenetic variability associated with cancer development, including predispositions and mutations. However, the bewildering genetic and phenotypic heterogeneity inherent in cancer both magnifies the conceptual and methodological problems associated with these approaches and renders the translation of available genetic information into a knowledge that is both biologically sound and clinically relevant difficult. Here, we elaborate on the underlying causes of this complexity, illustrate why it represents a challenge for genetic association studies, and briefly discuss how it can be reconciled with the ultimate goal of identifying targetable disease pathways and successfully treating individual patients. PMID:22858414

Endosperm: food for humankind and fodder for scientific discoveries.

PubMed

Li, Jing; Berger, Frédéric

2012-07-01

The endosperm is an essential constituent of seeds in flowering plants. It originates from a fertilization event parallel to the fertilization that gives rise to the embryo. The endosperm nurtures embryo development and, in some species including cereals, stores the seed reserves and represents a major source of food for humankind. Endosperm biology is characterized by specific features, including idiosyncratic cellular controls of cell division and epigenetic controls associated with parental genomic imprinting. This review attempts a comprehensive summary of our current knowledge of endosperm development and highlights recent advances in this field. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.

Effect of Integrating a Sportfishing Curriculum into a Camp Program on the Knowledge, Awareness, and Attitudes of Participating Youth.

ERIC Educational Resources Information Center

Koupal, Keith; Krasny, Marianne

2003-01-01

The effect of a 1-week sportfishing and environmental curriculum on participants' (aged 9-14) knowledge of fishing and biology/ecology, awareness of ethical behavior, and attitudes was assessed with 127 completed pre-/post-surveys. The program developed fishing and biology/ecology knowledge, but did not affect ethical behavior awareness or…

The Relationships Between Epistemic Beliefs in Biology and Approaches to Learning Biology Among Biology-Major University Students in Taiwan

NASA Astrophysics Data System (ADS)

Lin, Yi-Chun; Liang, Jyh-Chong; Tsai, Chin-Chung

2012-12-01

The aim of this study was to investigate the relationships between students' epistemic beliefs in biology and their approaches to learning biology. To this end, two instruments, the epistemic beliefs in biology and the approaches to learning biology surveys, were developed and administered to 520 university biology students, respectively. By and large, it was found that the students reflected "mixed" motives in biology learning, while those who had more sophisticated epistemic beliefs tended to employ deep strategies. In addition, the results of paired t tests revealed that the female students were more likely to possess beliefs about biological knowledge residing in external authorities, to believe in a right answer, and to utilize rote learning as a learning strategy. Moreover, compared to juniors and seniors, freshmen and sophomores tended to hold less mature views on all factors of epistemic beliefs regarding biology. Another comparison indicated that theoretical biology students (e.g. students majoring in the Department of Biology) tended to have more mature beliefs in learning biology and more advanced strategies for biology learning than those students studying applied biology (e.g. in the Department of Biotechnology). Stepwise regression analysis, in general, indicated that students who valued the role of experiments and justify epistemic assumptions and knowledge claims based on evidence were more oriented towards having mixed motives and utilizing deep strategies to learn biology. In contrast, students who believed in the certainty of biological knowledge were more likely to adopt rote learning strategies and to aim to qualify in biology.

Weaving Traditional Ecological Knowledge into Biological Education: A Call to Action.

ERIC Educational Resources Information Center

Kimmerer, Robin Wall

2002-01-01

Traditional ecological knowledge has value not only for the wealth of biological information it contains but also for the cultural framework of respect, reciprocity, and responsibility in which it is embedded. (Contains 48 references.) (DDR)

Thinking processes of Filipino teachers representation of schema of some biology topics: Its effects to the students conceptual understanding

NASA Astrophysics Data System (ADS)

Barquilla, Manuel B.

2018-01-01

This study is a qualitative-quantitative research, where the main concern is to investigate Content knowledge representation of Filipino Teachers in their schema (proposition, linear ordering and imagery) of some biology topics. The five biology topics includes: Photosynthesis, Cellular Respiration, human reproductive system, Mendelian genetics and NonMendelian genetics. The study focuses on the six (6) biology teachers and a total of 222 students in their respective classes. Of the Six (6) teachers, three (3) are under the Science curriculum and three (3) under regular curriculum in both public and private schools in Iligan city and Lanao del Norte, Philippines. The study utilizes interpretative case-study method, bracketing method, and concept analysis for qualitative part. For quantitative, it uses a nonparametric statistical tool, Kendall's Tau to determine congruence of students and teachers' concept maps and paired t-test for testing the significant differences of pre-and post-instruction concept maps to determine the effects of students' conceptual understanding before and after the teacher's representation of their schema that requires the teachers' thinking processes. The data were cross-validated with two or more techniques used in the study. The data collection entailed seven (7) months immersion: one (1) month for preliminary phase for the researcher to gain teachers' and students' confidence and the succeeding six (6) months for main observation and data collection. Results indicate that the teacher utilize six methods to construct meaning of concepts, three methods of representing classification, four methods to represent relationships, seven methods to represent transformation and three methods to represent causation in planning and implementing the lessons. They often modify definitions in the textbook and express these in lingua franca to be better understood by the students. Furthermore, the teachers' analogs given to student are sometimes far from the things, objects, events or processes being compared to. This suggests that teachers sometimes provide the condition for students' developing alternative conception through analogy/metaphors that they give. Also, the results suggest that there is significant differences between the pre and post instruction mean scores of concept maps before and after the teacher representation of their schema. Moreover, most of the topic (photosynthesis, human reproductive system, Mendelian and non-Mendelian genetics) studied have moderately or substantial to high agreement between the two groups. Hence, suggest that the teachers' representation highly influence student conceptual.

Exploring Biology Teachers' Pedagogical Content Knowledge in the Teaching of Genetics in Swaziland Science Classrooms

NASA Astrophysics Data System (ADS)

Mthethwa-Kunene, Eunice; Oke Onwu, Gilbert; de Villiers, Rian

2015-05-01

This study explored the pedagogical content knowledge (PCK) and its development of four experienced biology teachers in the context of teaching school genetics. PCK was defined in terms of teacher content knowledge, pedagogical knowledge and knowledge of students' preconceptions and learning difficulties. Data sources of teacher knowledge base included teacher-constructed concept maps, pre- and post-lesson teacher interviews, video-recorded genetics lessons, post-lesson teacher questionnaire and document analysis of teacher's reflective journals and students' work samples. The results showed that the teachers' individual PCK profiles consisted predominantly of declarative and procedural content knowledge in teaching basic genetics concepts. Conditional knowledge, which is a type of meta-knowledge for blending together declarative and procedural knowledge, was also demonstrated by some teachers. Furthermore, the teachers used topic-specific instructional strategies such as context-based teaching, illustrations, peer teaching, and analogies in diverse forms but failed to use physical models and individual or group student experimental activities to assist students' internalization of the concepts. The finding that all four teachers lacked knowledge of students' genetics-related preconceptions was equally significant. Formal university education, school context, journal reflection and professional development programmes were considered as contributing to the teachers' continuing PCK development. Implications of the findings for biology teacher education are briefly discussed.

A dataset on the species composition of amphipods (Crustacea) in a Mexican marine national park: Alacranes Reef, Yucatan

PubMed Central

Simões, Nuno; Pech, Daniel

2018-01-01

Abstract Background Alacranes Reef was declared as a National Marine Park in 1994. Since then, many efforts have been made to inventory its biodiversity. However, groups such as amphipods have been underestimated or not considered when benthic invertebrates were inventoried. Here we present a dataset that contributes to the knowledge of benthic amphipods (Crustacea, Peracarida) from the inner lagoon habitats from the Alacranes Reef National Park, the largest coral reef ecosystem in the Gulf of Mexico. The dataset contains information on records collected from 2009 to 2011. Data are available through Global Biodiversity Information Facility (GBIF). New information A total of 110 amphipod species distributed in 93 nominal species and 17 generic species, belonging to 71 genera, 33 families and three suborders are presented here. This information represents the first online dataset of amphipods from the Alacranes Reef National Park. The biological material is currently deposited in the crustacean collection from the regional unit of the National Autonomous University of Mexico located at Sisal, Yucatan, Mexico (UAS-Sisal). The biological material includes 588 data records with a total abundance of 6,551 organisms. The species inventory represents, until now, the richest fauna of benthic amphipods registered from any discrete coral reef ecosystem in Mexico. PMID:29416428

A dataset on the species composition of amphipods (Crustacea) in a Mexican marine national park: Alacranes Reef, Yucatan.

PubMed

Paz-Ríos, Carlos E; Simões, Nuno; Pech, Daniel

2018-01-01

Alacranes Reef was declared as a National Marine Park in 1994. Since then, many efforts have been made to inventory its biodiversity. However, groups such as amphipods have been underestimated or not considered when benthic invertebrates were inventoried. Here we present a dataset that contributes to the knowledge of benthic amphipods (Crustacea, Peracarida) from the inner lagoon habitats from the Alacranes Reef National Park, the largest coral reef ecosystem in the Gulf of Mexico. The dataset contains information on records collected from 2009 to 2011. Data are available through Global Biodiversity Information Facility (GBIF). A total of 110 amphipod species distributed in 93 nominal species and 17 generic species, belonging to 71 genera, 33 families and three suborders are presented here. This information represents the first online dataset of amphipods from the Alacranes Reef National Park. The biological material is currently deposited in the crustacean collection from the regional unit of the National Autonomous University of Mexico located at Sisal, Yucatan, Mexico (UAS-Sisal). The biological material includes 588 data records with a total abundance of 6,551 organisms. The species inventory represents, until now, the richest fauna of benthic amphipods registered from any discrete coral reef ecosystem in Mexico.

The Anisakis Transcriptome Provides a Resource for Fundamental and Applied Studies on Allergy-Causing Parasites.

PubMed

Baird, Fiona J; Su, Xiaopei; Aibinu, Ibukun; Nolan, Matthew J; Sugiyama, Hiromu; Otranto, Domenico; Lopata, Andreas L; Cantacessi, Cinzia

2016-07-01

Food-borne nematodes of the genus Anisakis are responsible for a wide range of illnesses (= anisakiasis), from self-limiting gastrointestinal forms to severe systemic allergic reactions, which are often misdiagnosed and under-reported. In order to enhance and refine current diagnostic tools for anisakiasis, knowledge of the whole spectrum of parasite molecules transcribed and expressed by this parasite, including those acting as potential allergens, is necessary. In this study, we employ high-throughput (Illumina) sequencing and bioinformatics to characterise the transcriptomes of two Anisakis species, A. simplex and A. pegreffii, and utilize this resource to compile lists of potential allergens from these parasites. A total of ~65,000,000 reads were generated from cDNA libraries for each species, and assembled into ~34,000 transcripts (= Unigenes); ~18,000 peptides were predicted from each cDNA library and classified based on homology searches, protein motifs and gene ontology and biological pathway mapping. Using comparative analyses with sequence data available in public databases, 36 (A. simplex) and 29 (A. pegreffii) putative allergens were identified, including sequences encoding 'novel' Anisakis allergenic proteins (i.e. cyclophilins and ABA-1 domain containing proteins). This study represents a first step towards providing the research community with a curated dataset to use as a molecular resource for future investigations of the biology of Anisakis, including molecules putatively acting as allergens, using functional genomics, proteomics and immunological tools. Ultimately, an improved knowledge of the biological functions of these molecules in the parasite, as well as of their immunogenic properties, will assist the development of comprehensive, reliable and robust diagnostic tools.

Prior knowledge-based approach for associating ...

EPA Pesticide Factsheets

Evaluating the potential human health and/or ecological risks associated with exposures to complex chemical mixtures in the ambient environment is one of the central challenges of chemical safety assessment and environmental protection. There is a need for approaches that can help to integrate chemical monitoring and bio-effects data to evaluate risks associated with chemicals present in the environment. We used prior knowledge about chemical-gene interactions to develop a knowledge assembly model for detected chemicals at five locations near two wastewater treatment plants. The assembly model was used to generate hypotheses about the biological impacts of the chemicals at each location. The hypotheses were tested using empirical hepatic gene expression data from fathead minnows exposed for 12 d at each location. Empirical gene expression data was also mapped to the assembly models to statistically evaluate the likelihood of a chemical contributing to the observed biological responses. The prior knowledge approach was able reasonably hypothesize the biological impacts at one site but not the other. Chemicals most likely contributing to the observed biological responses were identified at each location. Despite limitations to the approach, knowledge assembly models have strong potential for associating chemical occurrence with potential biological effects and providing a foundation for hypothesis generation to guide research and/or monitoring efforts relat

Knowledge Driven Variable Selection (KDVS) – a new approach to enrichment analysis of gene signatures obtained from high–throughput data

PubMed Central

2013-01-01

Background High–throughput (HT) technologies provide huge amount of gene expression data that can be used to identify biomarkers useful in the clinical practice. The most frequently used approaches first select a set of genes (i.e. gene signature) able to characterize differences between two or more phenotypical conditions, and then provide a functional assessment of the selected genes with an a posteriori enrichment analysis, based on biological knowledge. However, this approach comes with some drawbacks. First, gene selection procedure often requires tunable parameters that affect the outcome, typically producing many false hits. Second, a posteriori enrichment analysis is based on mapping between biological concepts and gene expression measurements, which is hard to compute because of constant changes in biological knowledge and genome analysis. Third, such mapping is typically used in the assessment of the coverage of gene signature by biological concepts, that is either score–based or requires tunable parameters as well, limiting its power. Results We present Knowledge Driven Variable Selection (KDVS), a framework that uses a priori biological knowledge in HT data analysis. The expression data matrix is transformed, according to prior knowledge, into smaller matrices, easier to analyze and to interpret from both computational and biological viewpoints. Therefore KDVS, unlike most approaches, does not exclude a priori any function or process potentially relevant for the biological question under investigation. Differently from the standard approach where gene selection and functional assessment are applied independently, KDVS embeds these two steps into a unified statistical framework, decreasing the variability derived from the threshold–dependent selection, the mapping to the biological concepts, and the signature coverage. We present three case studies to assess the usefulness of the method. Conclusions We showed that KDVS not only enables the selection of known biological functionalities with accuracy, but also identification of new ones. An efficient implementation of KDVS was devised to obtain results in a fast and robust way. Computing time is drastically reduced by the effective use of distributed resources. Finally, integrated visualization techniques immediately increase the interpretability of results. Overall, KDVS approach can be considered as a viable alternative to enrichment–based approaches. PMID:23302187

Advances on plant-pathogen interactions from molecular toward systems biology perspectives.

PubMed

Peyraud, Rémi; Dubiella, Ullrich; Barbacci, Adelin; Genin, Stéphane; Raffaele, Sylvain; Roby, Dominique

2017-05-01

In the past 2 decades, progress in molecular analyses of the plant immune system has revealed key elements of a complex response network. Current paradigms depict the interaction of pathogen-secreted molecules with host target molecules leading to the activation of multiple plant response pathways. Further research will be required to fully understand how these responses are integrated in space and time, and exploit this knowledge in agriculture. In this review, we highlight systems biology as a promising approach to reveal properties of molecular plant-pathogen interactions and predict the outcome of such interactions. We first illustrate a few key concepts in plant immunity with a network and systems biology perspective. Next, we present some basic principles of systems biology and show how they allow integrating multiomics data and predict cell phenotypes. We identify challenges for systems biology of plant-pathogen interactions, including the reconstruction of multiscale mechanistic models and the connection of host and pathogen models. Finally, we outline studies on resistance durability through the robustness of immune system networks, the identification of trade-offs between immunity and growth and in silico plant-pathogen co-evolution as exciting perspectives in the field. We conclude that the development of sophisticated models of plant diseases incorporating plant, pathogen and climate properties represent a major challenge for agriculture in the future. © 2016 The Authors. The Plant Journal published by John Wiley & Sons Ltd and Society for Experimental Biology.

Structuring and extracting knowledge for the support of hypothesis generation in molecular biology

PubMed Central

Roos, Marco; Marshall, M Scott; Gibson, Andrew P; Schuemie, Martijn; Meij, Edgar; Katrenko, Sophia; van Hage, Willem Robert; Krommydas, Konstantinos; Adriaans, Pieter W

2009-01-01

Background Hypothesis generation in molecular and cellular biology is an empirical process in which knowledge derived from prior experiments is distilled into a comprehensible model. The requirement of automated support is exemplified by the difficulty of considering all relevant facts that are contained in the millions of documents available from PubMed. Semantic Web provides tools for sharing prior knowledge, while information retrieval and information extraction techniques enable its extraction from literature. Their combination makes prior knowledge available for computational analysis and inference. While some tools provide complete solutions that limit the control over the modeling and extraction processes, we seek a methodology that supports control by the experimenter over these critical processes. Results We describe progress towards automated support for the generation of biomolecular hypotheses. Semantic Web technologies are used to structure and store knowledge, while a workflow extracts knowledge from text. We designed minimal proto-ontologies in OWL for capturing different aspects of a text mining experiment: the biological hypothesis, text and documents, text mining, and workflow provenance. The models fit a methodology that allows focus on the requirements of a single experiment while supporting reuse and posterior analysis of extracted knowledge from multiple experiments. Our workflow is composed of services from the 'Adaptive Information Disclosure Application' (AIDA) toolkit as well as a few others. The output is a semantic model with putative biological relations, with each relation linked to the corresponding evidence. Conclusion We demonstrated a 'do-it-yourself' approach for structuring and extracting knowledge in the context of experimental research on biomolecular mechanisms. The methodology can be used to bootstrap the construction of semantically rich biological models using the results of knowledge extraction processes. Models specific to particular experiments can be constructed that, in turn, link with other semantic models, creating a web of knowledge that spans experiments. Mapping mechanisms can link to other knowledge resources such as OBO ontologies or SKOS vocabularies. AIDA Web Services can be used to design personalized knowledge extraction procedures. In our example experiment, we found three proteins (NF-Kappa B, p21, and Bax) potentially playing a role in the interplay between nutrients and epigenetic gene regulation. PMID:19796406

Teaching Statistics in Biology: Using Inquiry-based Learning to Strengthen Understanding of Statistical Analysis in Biology Laboratory Courses

PubMed Central

2008-01-01

There is an increasing need for students in the biological sciences to build a strong foundation in quantitative approaches to data analyses. Although most science, engineering, and math field majors are required to take at least one statistics course, statistical analysis is poorly integrated into undergraduate biology course work, particularly at the lower-division level. Elements of statistics were incorporated into an introductory biology course, including a review of statistics concepts and opportunity for students to perform statistical analysis in a biological context. Learning gains were measured with an 11-item statistics learning survey instrument developed for the course. Students showed a statistically significant 25% (p < 0.005) increase in statistics knowledge after completing introductory biology. Students improved their scores on the survey after completing introductory biology, even if they had previously completed an introductory statistics course (9%, improvement p < 0.005). Students retested 1 yr after completing introductory biology showed no loss of their statistics knowledge as measured by this instrument, suggesting that the use of statistics in biology course work may aid long-term retention of statistics knowledge. No statistically significant differences in learning were detected between male and female students in the study. PMID:18765754

"Trees Live on Soil and Sunshine!"--Coexistence of Scientific and Alternative Conception of Tree Assimilation.

PubMed

Thorn, Christine Johanna; Bissinger, Kerstin; Thorn, Simon; Bogner, Franz Xaver

2016-01-01

Successful learning is the integration of new knowledge into existing schemes, leading to an integrated and correct scientific conception. By contrast, the co-existence of scientific and alternative conceptions may indicate a fragmented knowledge profile. Every learner is unique and thus carries an individual set of preconceptions before classroom engagement due to prior experiences. Hence, instructors and teachers have to consider the heterogeneous knowledge profiles of their class when teaching. However, determinants of fragmented knowledge profiles are not well understood yet, which may hamper a development of adapted teaching schemes. We used a questionnaire-based approach to assess conceptual knowledge of tree assimilation and wood synthesis surveying 885 students of four educational levels: 6th graders, 10th graders, natural science freshmen and other academic studies freshmen. We analysed the influence of learner's characteristics such as educational level, age and sex on the coexistence of scientific and alternative conceptions. Within all subsamples well-known alternative conceptions regarding tree assimilation and wood synthesis coexisted with correct scientific ones. For example, students describe trees to be living on "soil and sunshine", representing scientific knowledge of photosynthesis mingled with an alternative conception of trees eating like animals. Fragmented knowledge profiles occurred in all subsamples, but our models showed that improved education and age foster knowledge integration. Sex had almost no influence on the existing scientific conceptions and evolution of knowledge integration. Consequently, complex biological issues such as tree assimilation and wood synthesis need specific support e.g. through repeated learning units in class- and seminar-rooms in order to help especially young students to handle and overcome common alternative conceptions and appropriately integrate scientific conceptions into their knowledge profile.

“Trees Live on Soil and Sunshine!”- Coexistence of Scientific and Alternative Conception of Tree Assimilation

PubMed Central

Thorn, Simon; Bogner, Franz Xaver

2016-01-01

Successful learning is the integration of new knowledge into existing schemes, leading to an integrated and correct scientific conception. By contrast, the co-existence of scientific and alternative conceptions may indicate a fragmented knowledge profile. Every learner is unique and thus carries an individual set of preconceptions before classroom engagement due to prior experiences. Hence, instructors and teachers have to consider the heterogeneous knowledge profiles of their class when teaching. However, determinants of fragmented knowledge profiles are not well understood yet, which may hamper a development of adapted teaching schemes. We used a questionnaire-based approach to assess conceptual knowledge of tree assimilation and wood synthesis surveying 885 students of four educational levels: 6th graders, 10th graders, natural science freshmen and other academic studies freshmen. We analysed the influence of learner’s characteristics such as educational level, age and sex on the coexistence of scientific and alternative conceptions. Within all subsamples well-known alternative conceptions regarding tree assimilation and wood synthesis coexisted with correct scientific ones. For example, students describe trees to be living on “soil and sunshine”, representing scientific knowledge of photosynthesis mingled with an alternative conception of trees eating like animals. Fragmented knowledge profiles occurred in all subsamples, but our models showed that improved education and age foster knowledge integration. Sex had almost no influence on the existing scientific conceptions and evolution of knowledge integration. Consequently, complex biological issues such as tree assimilation and wood synthesis need specific support e.g. through repeated learning units in class- and seminar-rooms in order to help especially young students to handle and overcome common alternative conceptions and appropriately integrate scientific conceptions into their knowledge profile. PMID:26807974

Extending gene ontology with gene association networks.

PubMed

Peng, Jiajie; Wang, Tao; Wang, Jixuan; Wang, Yadong; Chen, Jin

2016-04-15

Gene ontology (GO) is a widely used resource to describe the attributes for gene products. However, automatic GO maintenance remains to be difficult because of the complex logical reasoning and the need of biological knowledge that are not explicitly represented in the GO. The existing studies either construct whole GO based on network data or only infer the relations between existing GO terms. None is purposed to add new terms automatically to the existing GO. We proposed a new algorithm 'GOExtender' to efficiently identify all the connected gene pairs labeled by the same parent GO terms. GOExtender is used to predict new GO terms with biological network data, and connect them to the existing GO. Evaluation tests on biological process and cellular component categories of different GO releases showed that GOExtender can extend new GO terms automatically based on the biological network. Furthermore, we applied GOExtender to the recent release of GO and discovered new GO terms with strong support from literature. Software and supplementary document are available at www.msu.edu/%7Ejinchen/GOExtender jinchen@msu.edu or ydwang@hit.edu.cn Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

ChloroKB: A Web Application for the Integration of Knowledge Related to Chloroplast Metabolic Network1[OPEN

PubMed Central

Gloaguen, Pauline; Alban, Claude; Ravanel, Stéphane; Seigneurin-Berny, Daphné; Matringe, Michel; Ferro, Myriam; Bruley, Christophe; Rolland, Norbert; Vandenbrouck, Yves

2017-01-01

Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis (Arabidopsis thaliana) metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers. PMID:28442501

Imaging and the new biology: What's wrong with this picture?

NASA Astrophysics Data System (ADS)

Vannier, Michael W.

2004-05-01

The Human Genome has been defined, giving us one part of the equation that stems from the central dogma of molecular biology. Despite this awesome scientific achievement, the correspondence between genomics and imaging is weak, since we cannot predict an organism's phenotype from even perfect knowledge of its genetic complement. Biological knowledge comes in several forms, and the genome is perhaps the best known and most completely understood type. Imaging creates another form of biological information, providing the ability to study morphology, growth and development, metabolic processes, and diseases in vitro and in vivo at many levels of scale. The principal challenge in biomedical imaging for the future lies in the need to reconcile the data provided by one or multiple modalities with other forms of biological knowledge, most importantly the genome, proteome, physiome, and other "-ome's." To date, the imaging science community has not set a high priority on the unification of their results with genomics, proteomics, and physiological functions in most published work. Images are relatively isolated from other forms of biological data, impairing our ability to conceive and address many fundamental questions in research and clinical practice. This presentation will explain the challenge of biological knowledge integration in basic research and clinical applications from the standpoint of imaging and image processing. The impediments to progress, isolation of the imaging community, and mainstream of new and future biological science will be identified, so the critical and immediate need for change can be highlighted.

Integrating cell biology and proteomic approaches in plants.

PubMed

Takáč, Tomáš; Šamajová, Olga; Šamaj, Jozef

2017-10-03

Significant improvements of protein extraction, separation, mass spectrometry and bioinformatics nurtured advancements of proteomics during the past years. The usefulness of proteomics in the investigation of biological problems can be enhanced by integration with other experimental methods from cell biology, genetics, biochemistry, pharmacology, molecular biology and other omics approaches including transcriptomics and metabolomics. This review aims to summarize current trends integrating cell biology and proteomics in plant science. Cell biology approaches are most frequently used in proteomic studies investigating subcellular and developmental proteomes, however, they were also employed in proteomic studies exploring abiotic and biotic stress responses, vesicular transport, cytoskeleton and protein posttranslational modifications. They are used either for detailed cellular or ultrastructural characterization of the object subjected to proteomic study, validation of proteomic results or to expand proteomic data. In this respect, a broad spectrum of methods is employed to support proteomic studies including ultrastructural electron microscopy studies, histochemical staining, immunochemical localization, in vivo imaging of fluorescently tagged proteins and visualization of protein-protein interactions. Thus, cell biological observations on fixed or living cell compartments, cells, tissues and organs are feasible, and in some cases fundamental for the validation and complementation of proteomic data. Validation of proteomic data by independent experimental methods requires development of new complementary approaches. Benefits of cell biology methods and techniques are not sufficiently highlighted in current proteomic studies. This encouraged us to review most popular cell biology methods used in proteomic studies and to evaluate their relevance and potential for proteomic data validation and enrichment of purely proteomic analyses. We also provide examples of representative studies combining proteomic and cell biology methods for various purposes. Integrating cell biology approaches with proteomic ones allow validation and better interpretation of proteomic data. Moreover, cell biology methods remarkably extend the knowledge provided by proteomic studies and might be fundamental for the functional complementation of proteomic data. This review article summarizes current literature linking proteomics with cell biology. Copyright © 2017 Elsevier B.V. All rights reserved.

Mapping biological ideas: Concept maps as knowledge integration tools for evolution education

NASA Astrophysics Data System (ADS)

Schwendimann, Beat Adrian

Many students leave school with a fragmented understanding of biology that does not allow them to connect their ideas to their everyday lives (Wandersee, 1989; Mintzes, Wandersee, & Novak, 1998; Mintzes, Wandersee, & Novak, 2000a). Understanding evolution ideas is seen as central to building an integrated knowledge of biology (Blackwell, Powell, & Dukes, 2003; Thagard & Findlay, 2010). However, the theory of evolution has been found difficult to understand as it incorporates a wide range of ideas from different areas (Bahar et al., 1999; Tsui & Treagust, 2003) and multiple interacting levels (Wilensky & Resnick, 1999; Duncan & Reiser, 2007; Hmelo-Silver et al., 2007). Research suggests that learners can hold a rich repertoire of co-existing alternative ideas of evolution (for example, Bishop & Anderson, 1990; Demastes, Good, & Peebles, 1996; Evans, 2008), especially of human evolution (for example, Nelson, 1986; Sinatra et al., 2003; Poling & Evans, 2004). Evolution ideas are difficult to understand because they often contradict existing alternative ideas (Mayr, 1982; Wolpert, 1994; Evans, 2008). Research suggests that understanding human evolution is a key to evolution education (for example, Blackwell et al., 2003; Besterman & Baggott la Velle, 2007). This dissertation research investigates how different concept mapping forms embedded in a collaborative technology-enhanced learning environment can support students' integration of evolution ideas using case studies of human evolution. Knowledge Integration (KI) (Linn et al., 2000; Linn et al., 2004) is used as the operational framework to explore concept maps as knowledge integration tools to elicit, add, critically distinguish, group, connect, and sort out alternative evolution ideas. Concept maps are a form of node-link diagram for organizing and representing connections between ideas as a semantic network (Novak & Gowin, 1984). This dissertation research describes the iterative development of a novel biology-specific form of concept map, called Knowledge Integration Map (KIM), which aims to help learners connect ideas across levels (for example, genotype and phenotype levels) towards an integrated understanding of evolution. Using a design-based research approach (Brown, 1992; Cobb et al., 2003), three iterative studies were implemented in ethically and economically diverse public high schools classrooms using the web-based inquiry science environment (WISE) (Linn et al., 2003; Linn et al., 2004). Study 1 investigates concept maps as generative assessment tools. Study 1A compares the concept map generation and critique process of biology novices and experts. Findings suggest that concept maps are sensitive to different levels of knowledge integration but require scaffolding and revision. Study 1B investigates the implementation of concept maps as summative assessment tools in a WISE evolution module. Results indicate that concept maps can reveal connections between students' alternative ideas of evolution. Study 2 introduces KIMs as embedded collaborative learning tools. After generating KIMs, student dyads revise KIMs through two different critique activities (comparison against an expert or peer generated KIM). Findings indicate that different critique activities can promote the use of different criteria for critique. Results suggest that the combination of generating and critiquing KIMs can support integrating evolution ideas but can be time-consuming. As time in biology classrooms is limited, study 3 distinguishes the learning effects from either generating or critiquing KIMs as more time efficient embedded learning tools. Findings suggest that critiquing KIMs can be more time efficient than generating KIMs. Using KIMs that include common alternative ideas for critique activities can create genuine opportunities for students to critically reflect on new and existing ideas. Critiquing KIMs can encourage knowledge integration by fostering self-monitoring of students' learning progress, identifying knowledge gaps, and distinguishing alternative evolution ideas. This dissertation research demonstrates that science instruction of complex topics, such as human evolution, can succeed through a combination of scaffolded inquiry activities using dynamic visualizations, explanation activities, and collaborative KIM activities. This research contributes to educational research and practice by describing ways to make KIMs effective and time efficient learning tools for evolution education. Supporting students' building of a more coherent understanding of core ideas of biology can foster their life-long interest and learning of science.

High school biology evolution learning experiences in a rural context: a case of and for cultural border crossing

NASA Astrophysics Data System (ADS)

Borgerding, Lisa A.

2017-03-01

Although the concept of "rural" is difficult to define, rural science education provides the possibility for learning centered upon a strong connection to the local community. Rural American adolescents tend to be more religious than their urban counterparts and less accepting of evolution than their non-rural peers. Because the status and perception of evolutionary theory may be very different within the students' lifeworlds and the subcultures of the science classroom and science itself, a cultural border crossing metaphor can be applied to evolution teaching and learning. This study examines how a teacher may serve as a cultural border crossing tour guide for students at a rural high school as they explore the concept of biological evolution in their high school biology class. Data collection entailed two formal teacher interviews, field note observations of two biology class periods each day for 16 days during the Evolution unit, individual interviews with 14 students, student evolution acceptance surveys, student evolution content tests, and classroom artifacts. The major findings center upon three themes regarding how this teacher and these students had largely positive evolution learning experiences even as some students continued to reject evolution. First, the teacher strategically positioned himself in two ways: using his unique "local" trusted position in the community and school and taking a position in which he did not personally represent science by instead consistently teaching evolution "according to scientists." Second, his instruction honored local "rural" funds of knowledge with respect to local knowledge of nature and by treating students' religious knowledge as a form of local expertise about one set of answers to questions also addressed by evolution. Third, the teacher served as a border crossing "tour guide" by helping students identify how the culture of science and the culture of their lifeworlds may differ with respect to evolutionary theory. Students negotiated the cultural borders for learning evolution in several ways, and different types of border crossings are described. The students respected the teacher's apparent neutrality, sensitivity toward multiple positions, explicit attention to religion/evolution, and transparency of purposes for teaching evolution. These findings add to the current literature on rural science education by highlighting local funds of knowledge for evolution learning and how rural teachers may help students navigate seemingly hazardous scientific topics. The study's findings also add to the current evolution education literature by examining how students' religious perspectives may be respected as a form of expertise about questions of origins by allowing students to examine similarities and differences between scientific and religious approaches to questions of biological origins and change.

Features of Knowledge Building in Biology: Understanding Undergraduate Students' Ideas about Molecular Mechanisms.

PubMed

Southard, Katelyn; Wince, Tyler; Meddleton, Shanice; Bolger, Molly S

2016-01-01

Research has suggested that teaching and learning in molecular and cellular biology (MCB) is difficult. We used a new lens to understand undergraduate reasoning about molecular mechanisms: the knowledge-integration approach to conceptual change. Knowledge integration is the dynamic process by which learners acquire new ideas, develop connections between ideas, and reorganize and restructure prior knowledge. Semistructured, clinical think-aloud interviews were conducted with introductory and upper-division MCB students. Interviews included a written conceptual assessment, a concept-mapping activity, and an opportunity to explain the biomechanisms of DNA replication, transcription, and translation. Student reasoning patterns were explored through mixed-method analyses. Results suggested that students must sort mechanistic entities into appropriate mental categories that reflect the nature of MCB mechanisms and that conflation between these categories is common. We also showed how connections between molecular mechanisms and their biological roles are part of building an integrated knowledge network as students develop expertise. We observed differences in the nature of connections between ideas related to different forms of reasoning. Finally, we provide a tentative model for MCB knowledge integration and suggest its implications for undergraduate learning. © 2016 K. Southard et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

A knowledge base of the chemical compounds of intermediary metabolism.

PubMed

Karp, P D

1992-08-01

This paper describes a publicly available knowledge base of the chemical compounds involved in intermediary metabolism. We consider the motivations for constructing a knowledge base of metabolic compounds, the methodology by which it was constructed, and the information that it currently contains. Currently the knowledge base describes 981 compounds, listing for each: synonyms for its name, a systematic name, CAS registry number, chemical formula, molecular weight, chemical structure and two-dimensional display coordinates for the structure. The Compound Knowledge Base (CompoundKB) illustrates several methodological principles that should guide the development of biological knowledge bases. I argue that biological datasets should be made available in multiple representations to increase their accessibility to end users, and I present multiple representations of the CompoundKB (knowledge base, relational data base and ASN. 1 representations). I also analyze the general characteristics of these representations to provide an understanding of their relative advantages and disadvantages. Another principle is that the error rate of biological data bases should be estimated and documented-this analysis is performed for the CompoundKB.

Knowledge-making distinctions in synthetic biology.

PubMed

O'Malley, Maureen A; Powell, Alexander; Davies, Jonathan F; Calvert, Jane

2008-01-01

Synthetic biology is an increasingly high-profile area of research that can be understood as encompassing three broad approaches towards the synthesis of living systems: DNA-based device construction, genome-driven cell engineering and protocell creation. Each approach is characterized by different aims, methods and constructs, in addition to a range of positions on intellectual property and regulatory regimes. We identify subtle but important differences between the schools in relation to their treatments of genetic determinism, cellular context and complexity. These distinctions tie into two broader issues that define synthetic biology: the relationships between biology and engineering, and between synthesis and analysis. These themes also illuminate synthetic biology's connections to genetic and other forms of biological engineering, as well as to systems biology. We suggest that all these knowledge-making distinctions in synthetic biology raise fundamental questions about the nature of biological investigation and its relationship to the construction of biological components and systems. (c) 2007 Wiley Periodicals, Inc.

Virtually the Same: A Comparison of STEM Students' Content Knowledge, Course Performance, and Motivation to Learn in Virtual and Face-to-Face Introductory Biology Laboratories. Research and Teaching

ERIC Educational Resources Information Center

Reece, Amber J.; Butler, Malcolm B.

2017-01-01

Biology I is a required course for many science, technology, engineering, and mathematics (STEM) majors and is often their first college-level laboratory experience. The replacement of the traditional face-to-face laboratory experience with virtual laboratories could influence students' content knowledge, motivation to learn biology, and overall…

You can exercise your way out of HIV and other stories: The role of biological knowledge in adolescents' evaluation of myths

NASA Astrophysics Data System (ADS)

Keselman, Alla; Kaufman, David R.; Patel, Vimla L.

2004-07-01

A primary objective for science education is to impart robust knowledge that has applicability to real-world problems. This article presents research investigating the relationship between adolescents' conceptual understanding of the biological basis of HIV and critical reasoning. Middle and high school students were interviewed about their understanding of HIV and were subsequently asked to evaluate scenarios that contained myths about HIV. On the basis of their responses to the interview questions, students' understanding of HIV was categorized into three models, naïve, intermediate, and advanced. The results indicate that knowledge mediated students' responses in specific ways. Students at different levels of HIV knowledge reasoned in qualitatively different ways about the myths. A significant relationship was found between students' understanding of HIV biology and the level of biological reasoning. We found that students who employed cellular-level biological reasoning were more likely to reject the myths than students who employed just system-level reasoning or nonspecific biological reasoning. The findings emphasize the importance of conceptual understanding in the critical evaluation of information that may serve as a basis for making decisions about HIV. We conclude with discussing the implications of the findings for science and health education.

Systematic analysis of signaling pathways using an integrative environment.

PubMed

Visvanathan, Mahesh; Breit, Marc; Pfeifer, Bernhard; Baumgartner, Christian; Modre-Osprian, Robert; Tilg, Bernhard

2007-01-01

Understanding the biological processes of signaling pathways as a whole system requires an integrative software environment that has comprehensive capabilities. The environment should include tools for pathway design, visualization, simulation and a knowledge base concerning signaling pathways as one. In this paper we introduce a new integrative environment for the systematic analysis of signaling pathways. This system includes environments for pathway design, visualization, simulation and a knowledge base that combines biological and modeling information concerning signaling pathways that provides the basic understanding of the biological system, its structure and functioning. The system is designed with a client-server architecture. It contains a pathway designing environment and a simulation environment as upper layers with a relational knowledge base as the underlying layer. The TNFa-mediated NF-kB signal trans-duction pathway model was designed and tested using our integrative framework. It was also useful to define the structure of the knowledge base. Sensitivity analysis of this specific pathway was performed providing simulation data. Then the model was extended showing promising initial results. The proposed system offers a holistic view of pathways containing biological and modeling data. It will help us to perform biological interpretation of the simulation results and thus contribute to a better understanding of the biological system for drug identification.

The effect of cooperative learning on the attitudes toward science and the achievement of students in a non-science majors' general biology laboratory course at an urban community college

NASA Astrophysics Data System (ADS)

Chung-Schickler, Genevieve C.

The purpose of this study was to evaluate the effect of cooperative learning strategies on students' attitudes toward science and achievement in BSC 1005L, a non-science majors' general biology laboratory course at an urban community college. Data were gathered on the participants' attitudes toward science and cognitive biology level pre and post treatment in BSC 1005L. Elements of the Learning Together model developed by Johnson and Johnson and the Student Team-Achievement Divisions model created by Slavin were incorporated into the experimental sections of BSC 1005L. Four sections of BSC 1005L participated in this study. Participants were enrolled in the 1998 spring (January) term. Students met weekly in a two hour laboratory session. The treatment was administered to the experimental group over a ten week period. A quasi-experimental pretest-posttest control group design was used. Students in the cooperative learning group (nsb1 = 27) were administered the Test of Science-Related Attitudes (TOSRA) and the cognitive biology test at the same time as the control group (nsb2 = 19) (at the beginning and end of the term). Statistical analyses confirmed that both groups were equivalent regarding ethnicity, gender, college grade point average and number of absences. Independent sample t-tests performed on pretest mean scores indicated no significant differences in the TOSRA scale two or biology knowledge between the cooperative learning group and the control group. The scores of TOSRA scales: one, three, four, five, six, and seven were significantly lower in the cooperative learning group. Independent sample t-tests of the mean score differences did not show any significant differences in posttest attitudes toward science or biology knowledge between the two groups. Paired t-tests did not indicate any significant differences on the TOSRA or biology knowledge within the cooperative learning group. Paired t-tests did show significant differences within the control group on TOSRA scale two and biology knowledge. ANCOVAs did not indicate any significant differences on the post mean scores of the TOSRA or biology knowledge adjusted by differences in the pretest mean scores. Analysis of the research data did not show any significant correlation between attitudes toward science and biology knowledge.

CONCEPTUAL FRAMEWORK FOR THE CHEMICAL EFFECTS IN BIOLOGICAL SYSTEMS (CEBS) TOXICOGENOMICS KNOWLEDGE BASE

EPA Science Inventory

Conceptual Framework for the Chemical Effects in Biological Systems (CEBS) T oxicogenomics Knowledge Base

Abstract
Toxicogenomics studies how the genome is involved in responses to environmental stressors or toxicants. It combines genetics, genome-scale mRNA expressio...

[The practice and discussion of the physical knowledge stepping into genetics teaching].

PubMed

Luo, Shen; Luo, Peigao

2014-09-01

Genetics, one of the core courses of biological field, play a key role in biology teaching and research. In fact, there exists high similarity between many genetic knowledge and physical knowledge. Due to strong abstract of genetic contents and the weak basis of genetics, some students lack of interests to study genetics. How to apply the strong physical knowledge which students had been learned in the middle school in genetics teaching is worthwhile for genetics teachers. In this paper, we would like to introduce an infiltrative teaching model on applying physical knowledge into genetic contents by establishing the intrinsic logistic relationship between physical knowledge and genetic knowledge. This teaching model could help students more deeply understand genetic knowledge and enhance students' self-studying ability as well as creating ability.

Understanding students' explanations of biological phenomena: Conceptual frameworks or p-prims?

NASA Astrophysics Data System (ADS)

Southerland, Sherry A.; Abrams, Eleanor; Cummins, Catherine L.; Anzelmo, Julie

2001-07-01

This study explores two differing perspectives of the nature of students' biological knowledge structures, conceptual frameworks, and p-prims. Students from four grade levels and from three regions of the United States were asked to explain a variety of biological phenomena. Students' responses to the interview probes were analyzed to describe 1) patterns in the nature of students' explanations across grade levels and interview probes, and 2) the consistency of students' explanations across individual interview probes and across the range of probes. The results were interpreted from both perspectives of knowledge structures. While definitive assertions supporting either perspective could not be made, each hypothesis was explored. Although the more prevalent description of student conceptions within a broader conceptual framework could not be discounted, the p-prim of need as a rationale for change was also found to offer a useful description of knowledge frameworks for this content area. The difficulties endemic to the use of biology for the study of basic knowledge structures are also discussed.

Protecting Traditional Knowledge Related to Biological Resources: Is Scientific Research Going to Become More Bureaucratized?

PubMed Central

Reddy, Prashant; Lakshmikumaran, Malathi

2015-01-01

For the past several decades, there has been a world debate on the need for protecting traditional knowledge. A global treaty appears to be a distant reality. Of more immediate concern are the steps taken by the global community to protect access to biological resources in the name of protecting traditional knowledge. The Indian experience with implementing the Convention on Biological Diversity has created substantial legal uncertainty in collaborative scientific research between Indians and foreigners apart from bureaucratizing the entire process of scientific research, especially with regard to filing of applications for intellectual property rights. The issue therefore is whether the world needs to better balance the needs of the scientific community with the rights of those who have access to traditional knowledge. PMID:26101205

Top-down proteomics reveals a unique protein S-thiolation switch in Salmonella Typimurium in response to infection-like conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ansong, Charles; Wu, Si; Meng, Da

Characterization of the mature protein complement in cells is crucial for a better understanding of cellular processes on a systems-wide scale. Bottom-up proteomic approaches often lead to loss of critical information about an endogenous protein’s actual state due to post translational modifications (PTMs) and other processes. Top-down approaches that involve analysis of the intact protein can address this concern but present significant analytical challenges related to the separation quality needed, measurement sensitivity, and speed that result in low throughput and limited coverage. Here we used single-dimension ultra high pressure liquid chromatography mass spectrometry to investigate the comprehensive ‘intact’ proteome ofmore » the Gram negative bacterial pathogen Salmonella Typhimurium. Top-down proteomics analysis revealed 563 unique proteins including 1665 proteoforms generated by PTMs, representing the largest microbial top-down dataset reported to date. Our analysis not only confirmed several previously recognized aspects of Salmonella biology and bacterial PTMs in general, but also revealed several novel biological insights. Of particular interest was differential utilization of the protein S-thiolation forms S-glutathionylation and S-cysteinylation in response to infection-like conditions versus basal conditions, which was corroborated by changes in corresponding biosynthetic pathways. This differential utilization highlights underlying metabolic mechanisms that modulate changes in cellular signaling, and represents to our knowledge the first report of S-cysteinylation in Gram negative bacteria. The demonstrated utility of our simple proteome-wide intact protein level measurement strategy for gaining biological insight should promote broader adoption and applications of top-down proteomics approaches.« less

Knowledge of Adverse Drug Reaction Reporting and the Pharmacovigilance of Biological Medicines: A Survey of Healthcare Professionals in Ireland.

PubMed

O'Callaghan, J; Griffin, B T; Morris, J M; Bermingham, Margaret

2018-06-01

In Europe, changes to pharmacovigilance legislation, which include additional monitoring of medicines, aim to optimise adverse drug reaction (ADR) reporting systems. The legislation also makes provisions related to the traceability of biological medicines. The objective of this study was to assess (i) knowledge and general experience of ADR reporting, (ii) knowledge, behaviours, and attitudes related to the pharmacovigilance of biologicals, and (iii) awareness of additional monitoring among healthcare professionals (HCPs) in Ireland. Hospital doctors (n = 88), general practitioners (GPs) (n = 197), nurses (n = 104) and pharmacists (n = 309) completed an online questionnaire. There were differences in mean knowledge scores relating to ADR reporting and the pharmacovigilance of biologicals among the HCP groups. The majority of HCPs who use biological medicines in their practice generally record biologicals by brand name but practice behaviours relating to batch number recording differed between some professions. HCPs consider batch number recording to be valuable but also regard it as being more difficult than brand name recording. Most respondents were aware of the concept of additional monitoring but awareness rates differed between some groups. Among those who knew about additional monitoring, there was higher awareness of the inverted black triangle symbol among pharmacists (> 86.4%) compared with hospital doctors (35.1%), GPs (35.6%), and nurses (14.9%). Hospital pharmacists had more experience and knowledge of ADR reporting than other practising HCPs. This study highlights the important role hospital pharmacists play in post-marketing surveillance. There is a need to increase pharmacovigilance awareness of biological medicines and improve systems to support their batch traceability.

Knowledge represented using RDF semantic network in the concept of semantic web

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lukasova, A., E-mail: alena.lukasova@osu.cz; Vajgl, M., E-mail: marek.vajgl@osu.cz; Zacek, M., E-mail: martin.zacek@osu.cz

The RDF(S) model has been declared as the basic model to capture knowledge of the semantic web. It provides a common and flexible way to decompose composed knowledge to elementary statements, which can be represented by RDF triples or by RDF graph vectors. From the logical point of view, elements of knowledge can be expressed using at most binary predicates, which can be converted to RDF-triples or graph vectors. However, it is not able to capture implicit knowledge representable by logical formulas. This contribution shows how existing approaches (semantic networks and clausal form logic) can be combined together with RDFmore » to obtain RDF-compatible system with ability to represent implicit knowledge and inference over knowledge base.« less

Data structures and apparatuses for representing knowledge

DOEpatents

Hohimer, Ryan E; Thomson, Judi R; Harvey, William J; Paulson, Patrick R; Whiting, Mark A; Tratz, Stephen C; Chappell, Alan R; Butner, Robert S

2014-02-18

Data structures and apparatuses to represent knowledge are disclosed. The processes can comprise labeling elements in a knowledge signature according to concepts in an ontology and populating the elements with confidence values. The data structures can comprise knowledge signatures stored on computer-readable media. The knowledge signatures comprise a matrix structure having elements labeled according to concepts in an ontology, wherein the value of the element represents a confidence that the concept is present in an information space. The apparatus can comprise a knowledge representation unit having at least one ontology stored on a computer-readable medium, at least one data-receiving device, and a processor configured to generate knowledge signatures by comparing datasets obtained by the data-receiving devices to the ontologies.

Processes, data structures, and apparatuses for representing knowledge

DOEpatents

Hohimer, Ryan E [West Richland, WA; Thomson, Judi R [Guelph, CA; Harvey, William J [Richland, WA; Paulson, Patrick R [Pasco, WA; Whiting, Mark A [Richland, WA; Tratz, Stephen C [Richland, WA; Chappell, Alan R [Seattle, WA; Butner, R Scott [Richland, WA

2011-09-20

Processes, data structures, and apparatuses to represent knowledge are disclosed. The processes can comprise labeling elements in a knowledge signature according to concepts in an ontology and populating the elements with confidence values. The data structures can comprise knowledge signatures stored on computer-readable media. The knowledge signatures comprise a matrix structure having elements labeled according to concepts in an ontology, wherein the value of the element represents a confidence that the concept is present in an information space. The apparatus can comprise a knowledge representation unit having at least one ontology stored on a computer-readable medium, at least one data-receiving device, and a processor configured to generate knowledge signatures by comparing datasets obtained by the data-receiving devices to the ontologies.

OpenBiodiv-O: ontology of the OpenBiodiv knowledge management system.

PubMed

Senderov, Viktor; Simov, Kiril; Franz, Nico; Stoev, Pavel; Catapano, Terry; Agosti, Donat; Sautter, Guido; Morris, Robert A; Penev, Lyubomir

2018-01-18

The biodiversity domain, and in particular biological taxonomy, is moving in the direction of semantization of its research outputs. The present work introduces OpenBiodiv-O, the ontology that serves as the basis of the OpenBiodiv Knowledge Management System. Our intent is to provide an ontology that fills the gaps between ontologies for biodiversity resources, such as DarwinCore-based ontologies, and semantic publishing ontologies, such as the SPAR Ontologies. We bridge this gap by providing an ontology focusing on biological taxonomy. OpenBiodiv-O introduces classes, properties, and axioms in the domains of scholarly biodiversity publishing and biological taxonomy and aligns them with several important domain ontologies (FaBiO, DoCO, DwC, Darwin-SW, NOMEN, ENVO). By doing so, it bridges the ontological gap across scholarly biodiversity publishing and biological taxonomy and allows for the creation of a Linked Open Dataset (LOD) of biodiversity information (a biodiversity knowledge graph) and enables the creation of the OpenBiodiv Knowledge Management System. A key feature of the ontology is that it is an ontology of the scientific process of biological taxonomy and not of any particular state of knowledge. This feature allows it to express a multiplicity of scientific opinions. The resulting OpenBiodiv knowledge system may gain a high level of trust in the scientific community as it does not force a scientific opinion on its users (e.g. practicing taxonomists, library researchers, etc.), but rather provides the tools for experts to encode different views as science progresses. OpenBiodiv-O provides a conceptual model of the structure of a biodiversity publication and the development of related taxonomic concepts. It also serves as the basis for the OpenBiodiv Knowledge Management System.

High School Intervention for Influenza Biology and Epidemics/Pandemics: Impact on Conceptual Understanding among Adolescents

PubMed Central

Hasni, Abdelkrim

2009-01-01

Understanding real-life issues such as influenza epidemiology may be of particular interest to the development of scientific knowledge and initiation of conceptual changes about viruses and their life cycles for high school students. The goal of this research project was to foster the development of adolescents' conceptual understanding of viruses and influenza biology. Thus, the project included two components: 1) pre- and posttests to determine students' conceptions about influenza biology, epidemics/pandemics, and vaccination; and 2) design an intervention that supports conceptual change to promote improvements in influenza knowledge based on these primary conceptions. Thirty-five female students from a high school biology class participated in a series of instructional activities and pre- and posttest assessments. Results from the pretest indicated that high school students exhibit a limited understanding of concepts related to viruses. Six weeks after an intervention that promoted active learning, results from a posttest showed that conceptions about influenza are more accurately related to the provided scientific knowledge. Although adolescents have nonscientific models to explain influenza biology, we showed that a carefully designed intervention can affect students' knowledge as well as influence the implementation of health education programs in secondary schools. PMID:19255137

Personal protection during resuscitation of casualties contaminated with chemical or biological warfare agents--a survey of medical first responders.

PubMed

Brinker, Andrea; Prior, Kate; Schumacher, Jan

2009-01-01

The threat of mass casualties caused by an unconventional terrorist attack is a challenge for the public health system, with special implications for emergency medicine, anesthesia, and intensive care. Advanced life support of patients injured by chemical or biological warfare agents requires an adequate level of personal protection. The aim of this study was to evaluate the personal protection knowledge of emergency physicians and anesthetists who would be at the frontline of the initial health response to a chemical/biological warfare agent incident. After institutional review board approval, knowledge of personal protection measures among emergency medicine (n = 28) and anesthetics (n = 47) specialty registrars in the South Thames Region of the United Kingdom was surveyed using a standardized questionnaire. Participants were asked for the recommended level of personal protection if a chemical/biological warfare agent(s) casualty required advanced life support in the designated hospital resuscitation area. The best awareness within both groups was regarding severe acute respiratory syndrome, and fair knowledge was found regarding anthrax, plague, Ebola, and smallpox. In both groups, knowledge about personal protection requirements against chemical warfare agents was limited. Knowledge about personal protection measures for biological agents was acceptable, but was limited for chemical warfare agents. The results highlight the need to improve training and education regarding personal protection measures for medical first receivers.

Using Multiple Lenses to Examine the Development of Beginning Biology Teachers' Pedagogical Content Knowledge for Teaching Natural Selection Simulations

NASA Astrophysics Data System (ADS)

Sickel, Aaron J.; Friedrichsen, Patricia

2018-02-01

Pedagogical content knowledge (PCK) has become a useful construct to examine science teacher learning. Yet, researchers conceptualize PCK development in different ways. The purpose of this longitudinal study was to use three analytic lenses to understand the development of three beginning biology teachers' PCK for teaching natural selection simulations. We observed three early-career biology teachers as they taught natural selection in their respective school contexts over two consecutive years. Data consisted of six interviews with each participant. Using the PCK model developed by Magnusson et al. (1999), we examined topic-specific PCK development utilizing three different lenses: (1) expansion of knowledge within an individual knowledge base, (2) integration of knowledge across knowledge bases, and (3) knowledge that explicitly addressed core concepts of natural selection. We found commonalities across the participants, yet each lens was also useful to understand the influence of different factors (e.g., orientation, subject matter preparation, and the idiosyncratic nature of teacher knowledge) on PCK development. This multi-angle approach provides implications for considering the quality of beginning science teachers' knowledge and future research on PCK development. We conclude with an argument that explicitly communicating lenses used to understand PCK development will help the research community compare analytic approaches and better understand the nature of science teacher learning.

Using doubly latent multilevel analysis to elucidate relationships between science teachers' professional knowledge and students' performance

NASA Astrophysics Data System (ADS)

Mahler, Daniela; Großschedl, Jörg; Harms, Ute

2017-01-01

Teachers make a difference for the outcome of their students in science classrooms. One focus in this context lies on teachers' professional knowledge. We describe this knowledge according to three domains, namely (1) content knowledge (CK), (2) pedagogical content knowledge (PCK), and (3) curricular knowledge (CuK). We hypothesise a positive relationship between these three domains and students' performance in science. Students' science performance was conceptualised by system thinking performance in the context of biology teaching. In order to test our hypothesis, we examined the relationship between the knowledge triplet CK, PCK, and CuK and students' performance. 48 biology teachers and their students (N = 1036) participated in this study. Teachers' content-related professional knowledge and students' performance were measured by paper-and-pencil tests. Moreover, we used concept maps to further assess students' performance. By specifying doubly latent models, we found a significant positive relationship between biology teachers' PCK and students' performance. On the contrary, the results reveal no relationship between CK and CuK and students' performance. These findings are discussed in respect to modelling the interrelationship of teachers' content-related professional knowledge and students' learning in science, as well as concerning their relevance for further research and teacher education programmes.

Introduction of an agent-based multi-scale modular architecture for dynamic knowledge representation of acute inflammation.

PubMed

An, Gary

2008-05-27

One of the greatest challenges facing biomedical research is the integration and sharing of vast amounts of information, not only for individual researchers, but also for the community at large. Agent Based Modeling (ABM) can provide a means of addressing this challenge via a unifying translational architecture for dynamic knowledge representation. This paper presents a series of linked ABMs representing multiple levels of biological organization. They are intended to translate the knowledge derived from in vitro models of acute inflammation to clinically relevant phenomenon such as multiple organ failure. ABM development followed a sequence starting with relatively direct translation from in-vitro derived rules into a cell-as-agent level ABM, leading on to concatenated ABMs into multi-tissue models, eventually resulting in topologically linked aggregate multi-tissue ABMs modeling organ-organ crosstalk. As an underlying design principle organs were considered to be functionally composed of an epithelial surface, which determined organ integrity, and an endothelial/blood interface, representing the reaction surface for the initiation and propagation of inflammation. The development of the epithelial ABM derived from an in-vitro model of gut epithelial permeability is described. Next, the epithelial ABM was concatenated with the endothelial/inflammatory cell ABM to produce an organ model of the gut. This model was validated against in-vivo models of the inflammatory response of the gut to ischemia. Finally, the gut ABM was linked to a similarly constructed pulmonary ABM to simulate the gut-pulmonary axis in the pathogenesis of multiple organ failure. The behavior of this model was validated against in-vivo and clinical observations on the cross-talk between these two organ systems. A series of ABMs are presented extending from the level of intracellular mechanism to clinically observed behavior in the intensive care setting. The ABMs all utilize cell-level agents that encapsulate specific mechanistic knowledge extracted from in vitro experiments. The execution of the ABMs results in a dynamic representation of the multi-scale conceptual models derived from those experiments. These models represent a qualitative means of integrating basic scientific information on acute inflammation in a multi-scale, modular architecture as a means of conceptual model verification that can potentially be used to concatenate, communicate and advance community-wide knowledge.

Human and Animal Dirofilariasis: the Emergence of a Zoonotic Mosaic

PubMed Central

Siles-Lucas, Mar; Morchón, Rodrigo; González-Miguel, Javier; Mellado, Isabel; Carretón, Elena; Montoya-Alonso, Jose Alberto

2012-01-01

Summary: Dirofilariasis represents a zoonotic mosaic, which includes two main filarial species (Dirofilaria immitis and D. repens) that have adapted to canine, feline, and human hosts with distinct biological and clinical implications. At the same time, both D. immitis and D. repens are themselves hosts to symbiotic bacteria of the genus Wolbachia, the study of which has resulted in a profound shift in the understanding of filarial biology, the mechanisms of the pathologies that they produce in their hosts, and issues related to dirofilariasis treatment. Moreover, because dirofilariasis is a vector-borne transmitted disease, their distribution and infection rates have undergone significant modifications influenced by global climate change. Despite advances in our knowledge of D. immitis and D. repens and the pathologies that they inflict on different hosts, there are still many unknown aspects of dirofilariasis. This review is focused on human and animal dirofilariasis, including the basic morphology, biology, protein composition, and metabolism of Dirofilaria species; the climate and human behavioral factors that influence distribution dynamics; the disease pathology; the host-parasite relationship; the mechanisms involved in parasite survival; the immune response and pathogenesis; and the clinical management of human and animal infections. PMID:22763636

Anthraquinones and Derivatives from Marine-Derived Fungi: Structural Diversity and Selected Biological Activities

PubMed Central

Fouillaud, Mireille; Venkatachalam, Mekala; Girard-Valenciennes, Emmanuelle; Caro, Yanis; Dufossé, Laurent

2016-01-01

Anthraquinones and their derivatives constitute a large group of quinoid compounds with about 700 molecules described. They are widespread in fungi and their chemical diversity and biological activities recently attracted attention of industries in such fields as pharmaceuticals, clothes dyeing, and food colorants. Their positive and/or negative effect(s) due to the 9,10-anthracenedione structure and its substituents are still not clearly understood and their potential roles or effects on human health are today strongly discussed among scientists. As marine microorganisms recently appeared as producers of an astonishing variety of structurally unique secondary metabolites, they may represent a promising resource for identifying new candidates for therapeutic drugs or daily additives. Within this review, we investigate the present knowledge about the anthraquinones and derivatives listed to date from marine-derived filamentous fungi′s productions. This overview highlights the molecules which have been identified in microorganisms for the first time. The structures and colors of the anthraquinoid compounds come along with the known roles of some molecules in the life of the organisms. Some specific biological activities are also described. This may help to open doors towards innovative natural substances. PMID:27023571

Effects of pesticide chemicals on the activity of metabolic enzymes: focus on thiocarbamates.

PubMed

Mathieu, Cécile; Duval, Romain; Xu, Ximing; Rodrigues-Lima, Fernando; Dupret, Jean-Marie

2015-01-01

Thiocarbamates are chemicals widely used as pesticides. Occupational exposure is associated with acute intoxication. Populations can be exposed through food and water. Moreover, certain thiocarbamates are used clinically. The widespread use of thiocarbamates raises many issues regarding their toxicological and pharmacological impact. Thiocarbamates and their metabolites can modify biological macromolecules functions, in particular enzymes, through modification of cysteine residues, chelation of metal ions or modulation of the oxidative stress. Loss of enzyme activity can lead to the disruption of metabolic pathways, and explain, at least in part, the effects of these pesticides. Additionally, their reactivity and ability to easily cross biological barrier confer them a great interest for development of clinical applications. Many advances in the study of thiocarbamates metabolism and reactivity have led to a better knowledge of biological effects of these compounds. However, more data are needed on the determination of targets and specificity. Only few data concerning the exposure to a cocktail of pesticides/chemicals are available, raising the need to evaluate the toxic side effects of representative pesticides mixtures. Moreover, the dithiocarbamate Disulfiram has shown great potential in therapeutic applications and leads to the development of pharmacological thiocarbamates derivatives, highly specific to their target and easily distributed.

Plant metabolic modeling: achieving new insight into metabolism and metabolic engineering.

PubMed

Baghalian, Kambiz; Hajirezaei, Mohammad-Reza; Schreiber, Falk

2014-10-01

Models are used to represent aspects of the real world for specific purposes, and mathematical models have opened up new approaches in studying the behavior and complexity of biological systems. However, modeling is often time-consuming and requires significant computational resources for data development, data analysis, and simulation. Computational modeling has been successfully applied as an aid for metabolic engineering in microorganisms. But such model-based approaches have only recently been extended to plant metabolic engineering, mainly due to greater pathway complexity in plants and their highly compartmentalized cellular structure. Recent progress in plant systems biology and bioinformatics has begun to disentangle this complexity and facilitate the creation of efficient plant metabolic models. This review highlights several aspects of plant metabolic modeling in the context of understanding, predicting and modifying complex plant metabolism. We discuss opportunities for engineering photosynthetic carbon metabolism, sucrose synthesis, and the tricarboxylic acid cycle in leaves and oil synthesis in seeds and the application of metabolic modeling to the study of plant acclimation to the environment. The aim of the review is to offer a current perspective for plant biologists without requiring specialized knowledge of bioinformatics or systems biology. © 2014 American Society of Plant Biologists. All rights reserved.

Plant Metabolic Modeling: Achieving New Insight into Metabolism and Metabolic Engineering

PubMed Central

Baghalian, Kambiz; Hajirezaei, Mohammad-Reza; Schreiber, Falk

2014-01-01

Models are used to represent aspects of the real world for specific purposes, and mathematical models have opened up new approaches in studying the behavior and complexity of biological systems. However, modeling is often time-consuming and requires significant computational resources for data development, data analysis, and simulation. Computational modeling has been successfully applied as an aid for metabolic engineering in microorganisms. But such model-based approaches have only recently been extended to plant metabolic engineering, mainly due to greater pathway complexity in plants and their highly compartmentalized cellular structure. Recent progress in plant systems biology and bioinformatics has begun to disentangle this complexity and facilitate the creation of efficient plant metabolic models. This review highlights several aspects of plant metabolic modeling in the context of understanding, predicting and modifying complex plant metabolism. We discuss opportunities for engineering photosynthetic carbon metabolism, sucrose synthesis, and the tricarboxylic acid cycle in leaves and oil synthesis in seeds and the application of metabolic modeling to the study of plant acclimation to the environment. The aim of the review is to offer a current perspective for plant biologists without requiring specialized knowledge of bioinformatics or systems biology. PMID:25344492

The moss Physcomitrella patens: methods and tools from cultivation to targeted analysis of gene function.

PubMed

Strotbek, Christoph; Krinninger, Stefan; Frank, Wolfgang

2013-01-01

To comprehensively understand the major processes in plant biology, it is necessary to study a diverse set of species that represent the complexity of plants. This research will help to comprehend common conserved mechanisms and principles, as well as to elucidate those mechanisms that are specific to a particular plant clade. Thereby, we will gain knowledge about the invention and loss of mechanisms and their biological impact causing the distinct specifications throughout the plant kingdom. Since the establishment of transgenic plants, these studies concentrate on the elucidation of gene functions applying an increasing repertoire of molecular techniques. In the last two decades, the moss Physcomitrella patens joined the established set of plant models based on its evolutionary position bridging unicellular algae and vascular plants and a number of specific features alleviating gene function analysis. Here, we want to provide an overview of the specific features of P. patens making it an interesting model for many research fields in plant biology, to present the major achievements in P. patens genetic engineering, and to introduce common techniques to scientists who intend to use P. patens as a model in their research activities.

Body temperature variability (Part 1): a review of the history of body temperature and its variability due to site selection, biological rhythms, fitness, and aging.

PubMed

Kelly, Greg

2006-12-01

Body temperature is a complex, non-linear data point, subject to many sources of internal and external variation. While these sources of variation significantly complicate interpretation of temperature data, disregarding knowledge in favor of oversimplifying complex issues would represent a significant departure from practicing evidence-based medicine. Part 1 of this review outlines the historical work of Wunderlich on temperature and the origins of the concept that a healthy normal temperature is 98.6 degrees F (37.0 degrees C). Wunderlich's findings and methodology are reviewed and his results are contrasted with findings from modern clinical thermometry. Endogenous sources of temperature variability, including variations caused by site of measurement, circadian, menstrual, and annual biological rhythms, fitness, and aging are discussed. Part 2 will review the effects of exogenous masking agents - external factors in the environment, diet, or lifestyle that can influence body temperature, as well as temperature findings in disease states.

From Biology to Drug Development: New Approaches to Combat the Threat of Fungal Biofilms

PubMed Central

Pierce, Christopher G.; Srinivasan, Anand; Ramasubramanian, Anand K.; López-Ribot, José L.

2015-01-01

Fungal infections constitute a major threat to an escalating number of critically ill patients. Fungi are eukaryotic organisms and, as such, there is a limited armamentarium of antifungal drugs, leading to high mortality rates. Moreover, fungal infections are often associated with the formation of biofilms, which contribute to virulence and further complicate treatment due to the high level of antifungal drug resistance displayed by sessile cells within these microbial communities. Thus, the treatment of fungal infections associated with a biofilm aetiology represents a formidable and unmet clinical challenge. The increasing importance and awareness of fungal biofilms is reflected by the fact that this is now an area of very active research. Studies in the last decade have provided important insights into fungal biofilm biology, physiology and pathology, as well as into the molecular basis of biofilm resistance. Here we discuss how this accumulated knowledge may inform the development of new anti-biofilm strategies and therapeutics that are urgently needed. PMID:26185082

The role of the oncogenic Rab35 in cancer invasion, metastasis, and immune evasion, especially in leukemia.

PubMed

Villagomez, Fabian R; Medina-Contreras, Oscar; Cerna-Cortes, Jorge Francisco; Patino-Lopez, Genaro

2018-05-28

The study of cancer has allowed researchers to describe some biological characteristics that tumor cells acquire during their development, known as the "hallmarks of cancer" but more research is needed to expand our knowledge about cancer biology and to generate new strategies of treatment. The role that RabGTPases might play in some hallmarks of cancer represents interesting areas of study since these proteins are frequently altered in cancer. However, their participation is not well known. Recently, Rab35was recognized as an oncogenic RabGTPase and and because of its association with different cellular functions, distinctly important in immune cells, a possible role of Rab35 in leukemia can be suggested. Nevertheless, the involvement of Rab35 in cancer remains poorly understood and its possible specific role in leukemia remains unknown. In this review, we analyze general aspects of the participation of RabGTPases in cancer, and especially, the plausible role of Rab35 in leukemia.

Herpetofauna of the Beni Biological Station Biosphere Reserve, Amazonian Bolivia: Additional information, and current knowledge in context

USGS Publications Warehouse

Middendorf, G.; Reynolds, R.; Herrera-MacBryde, Olga; Dallmeier, Francisco; MacBryde, Bruce; Cominskey, James A.; Miranda, Carmen

2000-01-01

Previous collections in the Departamento del Beni in tropical Bolivia only hinted at high levels of herpetological biodiversity (Fugler 1986, 1988; de la Riva 1990a; Fugler and de la Riva 1990). Fieldwork (totaling 48 days) in July-August 1988 and September 1987 (dry seasons) and November-December 1990 (wet season) has resulted in collection and identification of 401 amphibian and reptilian specimens from the general area of the Beni Biological Station's (EBB) headquarters at El Porvenir. These collections represent 33 amphibian and 17 reptilian species in 29 genera (14 amphibian, 15 reptilian). The inventory of herpetofauna scientifically documented to occur in the Departamento del Beni is considered to have been increased by 6 amphibian and 10 reptilian species. Specimens that could not be definitively identified (reflecting taxonomic uncertainty and/or probably species new to science) include 3 amphibian species (anurans) and 2 reptilian species (snakes). The EBB harbors the richest savanna for anuran species known in South America.

New species of Plectromacronema Ulmer 1906 (Trichoptera: Hydropsychidae) from Brazil, with association of immature stages and aspects of its biology.

PubMed

Paprocki, Henrique; Moreira-Silva, Larissa

2018-01-01

Plectromacronema Ulmer 1906 is a Neotropical genus recorded sparsely from South of Mexico to the North of Argentina. The genus is placed within the Macronematinae sub-family, members of which are relatively large among the Trichoptera and bears conspicuous wing ornamentations. There are only two species recorded for Brazil, Plectromacronema comptum Ulmer 1906 and Plectromacronema subfuscum (Banks 1920). Plectromacronema lisae Flint 1983 recorded for Mexico and Costa Rica is the only species in the genus with immature stages described. Immature stages species level identification is required for water quality biomonitoring and most of the Trichoptera taxonomy is based only on adult male genitalia. In this paper, we propose a new species, Plectromacronema solaris sp.nov., larva, pupa, and adult. Aspects of the life history of the new species are also discussed. This record also represents a new genus record for the state of Minas Gerais, extending the knowledge on the diversity, distribution, biogeography, and biology of this remarkable genus.

Extracellular matrix in lung development, homeostasis and disease

DOE PAGES

Zhou, Yong; Horowitz, Jeffrey C.; Naba, Alexandra; ...

2018-03-08

Here, the lung's unique extracellular matrix (ECM), while providing structural support for cells, is critical in the regulation of developmental organogenesis, homeostasis and injury-repair responses. The ECM, via biochemical or biomechanical cues, regulates diverse cell functions, fate and phenotype. The composition and function of lung ECM become markedly deranged in pathological tissue remodeling. ECM-based therapeutics and bioengineering approaches represent promising novel strategies for regeneration/repair of the lung and treatment of chronic lung diseases. In this review, we assess the current state of lung ECM biology, including fundamental advances in ECM composition, dynamics, topography, and biomechanics; the role of the ECMmore » in normal and aberrant lung development, adult lung diseases and autoimmunity; and ECM in the regulation of the stem cell niche. We identify opportunities to advance the field of lung ECM biology and provide a set recommendations for research priorities to advance knowledge that would inform novel approaches to the pathogenesis, diagnosis, and treatment of chronic lung diseases.« less

Extracellular matrix in lung development, homeostasis and disease

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Yong; Horowitz, Jeffrey C.; Naba, Alexandra

Here, the lung's unique extracellular matrix (ECM), while providing structural support for cells, is critical in the regulation of developmental organogenesis, homeostasis and injury-repair responses. The ECM, via biochemical or biomechanical cues, regulates diverse cell functions, fate and phenotype. The composition and function of lung ECM become markedly deranged in pathological tissue remodeling. ECM-based therapeutics and bioengineering approaches represent promising novel strategies for regeneration/repair of the lung and treatment of chronic lung diseases. In this review, we assess the current state of lung ECM biology, including fundamental advances in ECM composition, dynamics, topography, and biomechanics; the role of the ECMmore » in normal and aberrant lung development, adult lung diseases and autoimmunity; and ECM in the regulation of the stem cell niche. We identify opportunities to advance the field of lung ECM biology and provide a set recommendations for research priorities to advance knowledge that would inform novel approaches to the pathogenesis, diagnosis, and treatment of chronic lung diseases.« less

Targeted therapies and immunotherapy in non-small-cell lung cancer

PubMed Central

Cortinovis, D; Abbate, M; Bidoli, P; Capici, S; Canova, S

2016-01-01

Non-small-cell lung cancer is still considered a difficult disease to manage because of its aggressiveness and resistance to common therapies. Chemotherapy remains the gold standard in nearly 80% of lung cancers, but clinical outcomes are discouraging, and the impact on median overall survival (OS) barely reaches 12 months. At the end of the last century, the discovery of oncogene-driven tumours completely changed the therapeutic landscape in lung cancers, harbouring specific gene mutations/translocations. Epidermal growth factors receptor (EGFR) common mutations first and anaplastic lymphoma kinase (ALK) translocations later led new insights in lung cancer biology knowledge. The use of specific tyrosine kinases inhibitors overturned the biological behaviour of EGFR mutation positive tumours and became a preclinical model to understand the heterogeneity of lung cancers and the mechanisms of drug resistance. In this review, we summarise the employment of targeted agents against the most representative biomolecular alterations and provide some criticisms of the therapeutic strategies. PMID:27433281

A call for virtual experiments: accelerating the scientific process.

PubMed

Cooper, Jonathan; Vik, Jon Olav; Waltemath, Dagmar

2015-01-01

Experimentation is fundamental to the scientific method, whether for exploration, description or explanation. We argue that promoting the reuse of virtual experiments (the in silico analogues of wet-lab or field experiments) would vastly improve the usefulness and relevance of computational models, encouraging critical scrutiny of models and serving as a common language between modellers and experimentalists. We review the benefits of reusable virtual experiments: in specifying, assaying, and comparing the behavioural repertoires of models; as prerequisites for reproducible research; to guide model reuse and composition; and for quality assurance in the translational application of models. A key step towards achieving this is that models and experimental protocols should be represented separately, but annotated so as to facilitate the linking of models to experiments and data. Lastly, we outline how the rigorous, streamlined confrontation between experimental datasets and candidate models would enable a "continuous integration" of biological knowledge, transforming our approach to systems biology. Copyright © 2014 Elsevier Ltd. All rights reserved.

Concluding remarks: what's in a name? "Negritos" in the context of the human prehistory of Southeast Asia.

PubMed

Ulijaszek, Stanley J

2013-01-01

The "negrito" hypothesis posits that various indigenous groups throughout Island and Mainland Southeast Asia have a shared phenotype due to common descent from a putative ancestral population, representing a pre-agricultural substrate of humanity in the region. This has been examined and tested many times in the past, with no clear resolution. With many new resources to hand, the articles in this volume reexamine this hypothesis in a range of different ways. The evidence presented in this double issue of Human Biology speaks more against the category of "negrito" than for it. While populations with the negrito phenotype form a small proportion of all contemporary populations in this region, they have remained a persistent presence. And without a fascination about their origins, there would not be such a depth of knowledge about the human biology of this region more broadly as there is now. Copyright © 2013 Wayne State University Press, Detroit, Michigan 48201-1309.

Extracellular matrix in lung development, homeostasis and disease

DOE PAGES

Zhou, Yong; Horowitz, Jeffrey C.; Naba, Alexandra; ...

2018-03-08

The lung's unique extracellular matrix (ECM), while providing structural support for cells, is critical in the regulation of developmental organogenesis, homeostasis and injury-repair responses. The ECM, via biochemical or biomechanical cues, regulates diverse cell functions, fate and phenotype. The composition and function of lung ECM become markedly deranged in pathological tissue remodeling. ECM-based therapeutics and bioengineering approaches represent promising novel strategies for regeneration/repair of the lung and treatment of chronic lung diseases. In this paper, we assess the current state of lung ECM biology, including fundamental advances in ECM composition, dynamics, topography, and biomechanics; the role of the ECM inmore » normal and aberrant lung development, adult lung diseases and autoimmunity; and ECM in the regulation of the stem cell niche. Finally, we identify opportunities to advance the field of lung ECM biology and provide a set recommendations for research priorities to advance knowledge that would inform novel approaches to the pathogenesis, diagnosis, and treatment of chronic lung diseases.« less

Active machine learning-driven experimentation to determine compound effects on protein patterns

PubMed Central

Naik, Armaghan W; Kangas, Joshua D; Sullivan, Devin P; Murphy, Robert F

2016-01-01

High throughput screening determines the effects of many conditions on a given biological target. Currently, to estimate the effects of those conditions on other targets requires either strong modeling assumptions (e.g. similarities among targets) or separate screens. Ideally, data-driven experimentation could be used to learn accurate models for many conditions and targets without doing all possible experiments. We have previously described an active machine learning algorithm that can iteratively choose small sets of experiments to learn models of multiple effects. We now show that, with no prior knowledge and with liquid handling robotics and automated microscopy under its control, this learner accurately learned the effects of 48 chemical compounds on the subcellular localization of 48 proteins while performing only 29% of all possible experiments. The results represent the first practical demonstration of the utility of active learning-driven biological experimentation in which the set of possible phenotypes is unknown in advance. DOI: http://dx.doi.org/10.7554/eLife.10047.001 PMID:26840049

Traditional medicines and globalization: current and future perspectives in ethnopharmacology.

PubMed

Leonti, Marco; Casu, Laura

2013-01-01

The ethnopharmacological approach toward the understanding and appraisal of traditional and herbal medicines is characterized by the inclusions of the social as well as the natural sciences. Anthropological field-observations describing the local use of nature-derived medicines are the basis for ethnopharmacological enquiries. The multidisciplinary scientific validation of indigenous drugs is of relevance to modern societies at large and helps to sustain local health care practices. Especially with respect to therapies related to aging related, chronic and infectious diseases traditional medicines offer promising alternatives to biomedicine. Bioassays applied in ethnopharmacology represent the molecular characteristics and complexities of the disease or symptoms for which an indigenous drug is used in "traditional" medicine to variable depth and extent. One-dimensional in vitro approaches rarely cope with the complexity of human diseases and ignore the concept of polypharmacological synergies. The recent focus on holistic approaches and systems biology in medicinal plant research represents the trend toward the description and the understanding of complex multi-parameter systems. Ethnopharmacopoeias are non-static cultural constructs shaped by belief and knowledge systems. Intensified globalization and economic liberalism currently accelerates the interchange between local and global pharmacopoeias via international trade, television, the World Wide Web and print media. The increased infiltration of newly generated biomedical knowledge and introduction of "foreign" medicines into local pharmacopoeias leads to syncretic developments and generates a feedback loop. While modern and post-modern cultures and knowledge systems adapt and transform the global impact, they become more relevant for ethnopharmacology. Moreover, what is traditional, alternative or complementary medicine depends on the adopted historic-cultural perspective.

Traditional medicines and globalization: current and future perspectives in ethnopharmacology

PubMed Central

Leonti, Marco; Casu, Laura

2013-01-01

The ethnopharmacological approach toward the understanding and appraisal of traditional and herbal medicines is characterized by the inclusions of the social as well as the natural sciences. Anthropological field-observations describing the local use of nature-derived medicines are the basis for ethnopharmacological enquiries. The multidisciplinary scientific validation of indigenous drugs is of relevance to modern societies at large and helps to sustain local health care practices. Especially with respect to therapies related to aging related, chronic and infectious diseases traditional medicines offer promising alternatives to biomedicine. Bioassays applied in ethnopharmacology represent the molecular characteristics and complexities of the disease or symptoms for which an indigenous drug is used in “traditional” medicine to variable depth and extent. One-dimensional in vitro approaches rarely cope with the complexity of human diseases and ignore the concept of polypharmacological synergies. The recent focus on holistic approaches and systems biology in medicinal plant research represents the trend toward the description and the understanding of complex multi-parameter systems. Ethnopharmacopoeias are non-static cultural constructs shaped by belief and knowledge systems. Intensified globalization and economic liberalism currently accelerates the interchange between local and global pharmacopoeias via international trade, television, the World Wide Web and print media. The increased infiltration of newly generated biomedical knowledge and introduction of “foreign” medicines into local pharmacopoeias leads to syncretic developments and generates a feedback loop. While modern and post-modern cultures and knowledge systems adapt and transform the global impact, they become more relevant for ethnopharmacology. Moreover, what is traditional, alternative or complementary medicine depends on the adopted historic-cultural perspective. PMID:23898296

Negotiating the dynamics of uncomfortable knowledge: The case of dual use and synthetic biology

PubMed Central

Marris, Claire; Jefferson, Catherine; Lentzos, Filippa

2014-01-01

Institutions need to ignore some knowledge in order to function. This is “uncomfortable knowledge” because it undermines the ability of those institutions to pursue their goals (Rayner, 2012). We identify three bodies of knowledge that are relevant to understandings of the dual use threat posed by synthetic biology but are excluded from related policy discussions. We demonstrate how these “unknown knowns” constitute uncomfortable knowledge because they disrupt the simplified worldview that underpins contemporary discourse on the potential misuse of synthetic biology by malign actors. We describe how these inconvenient truths have been systematically ignored and argue that this is because they are perceived as a threat by organisations involved in the promotion of synthetic biology as well as by those involved in managing biosecurity risks. This has led to a situation where concerns about the biosecurity threat posed by synthetic biology are not only exaggerated, but are, more importantly, misplaced. This, in turn, means that related policies are misdirected and unlikely to have much impact. We focus on the dynamics of discussions about synthetic biology and dual use to demonstrate how the same “knowns” that are denied or dismissed as “unknown knowns” in certain circumstances are sometimes mobilised as “known knowns” by the same category of actors in a different context, when this serves to sustain the goals of the individuals and institutions involved. Based on our own experience, we argue that negotiating the dynamics of uncomfortable knowledge is a difficult, but necessary, component of meaningful transdisciplinary collaborations. PMID:25484910

Instructional Implications of David C. Geary's Evolutionary Educational Psychology

ERIC Educational Resources Information Center

Sweller, John

2008-01-01

David C. Geary's thesis has the potential to alter our understanding of those aspects of human cognition relevant to instruction. His distinction between biologically primary knowledge that we have evolved to acquire and biologically secondary knowledge that is culturally important, taught in educational institutions and which we have not evolved…

From Noise to Order: The Psychological Development of Knowledge and Phenocopy in Biology

ERIC Educational Resources Information Center

Piaget, Jean

1975-01-01

Shows that one of the most general processes in the development of cognitive structures consists in replacing exogenous knowledge by endogenous reconstructions that reconstitute the same forms but incorporate them into systems whose internal composition is a pre-requisite. Biologically equivalent process is discussed. (Author/AM)

The Social Construction of Biological Knowledge.

ERIC Educational Resources Information Center

Bain, Linda L.

The influence of biological science research on the development of physical education curriculum is examined in this paper. The social construction of scientific knowledge is described as occurring in the selection of problems to be studied, the collection and interpretation of data, the dissemination of results, and the educational uses of…

An Object-Oriented Architecture for Intelligent Tutoring Systems. Technical Report No. LSP-3.

ERIC Educational Resources Information Center

Bonar, Jeffrey; And Others

This technical report describes a generic architecture for building intelligent tutoring systems which is developed around objects that represent the knowledge elements to be taught by the tutor. Each of these knowledge elements, called "bites," inherits both a knowledge organization describing the kind of knowledge represented and…

The Power of a Question: A Case Study of Two Organizational Knowledge Capture Systems

NASA Technical Reports Server (NTRS)

Cooper, Lynn P.

2003-01-01

This document represents a presentation regarding organizational knowledge capture systems which was delivered at the HICSS-36 conference held from January 6-9, 2003. An exploratory case study of two knowledge resources is offered. Then, two organizational knowledge capture systems are briefly described: knowledge transfer from practitioner and the use of questions to represent knowledge. Finally, the creation of a database of peer review questions is suggested as a method of promoting organizational discussions and knowledge representation and exchange.

Unbiased Protein Association Study on the Public Human Proteome Reveals Biological Connections between Co-Occurring Protein Pairs

PubMed Central

2017-01-01

Mass-spectrometry-based, high-throughput proteomics experiments produce large amounts of data. While typically acquired to answer specific biological questions, these data can also be reused in orthogonal ways to reveal new biological knowledge. We here present a novel method for such orthogonal data reuse of public proteomics data. Our method elucidates biological relationships between proteins based on the co-occurrence of these proteins across human experiments in the PRIDE database. The majority of the significantly co-occurring protein pairs that were detected by our method have been successfully mapped to existing biological knowledge. The validity of our novel method is substantiated by the extremely few pairs that can be mapped to existing knowledge based on random associations between the same set of proteins. Moreover, using literature searches and the STRING database, we were able to derive meaningful biological associations for unannotated protein pairs that were detected using our method, further illustrating that as-yet unknown associations present highly interesting targets for follow-up analysis. PMID:28480704

Biological Control of Mosquito Vectors: Past, Present, and Future.

PubMed

Benelli, Giovanni; Jeffries, Claire L; Walker, Thomas

2016-10-03

Mosquitoes represent the major arthropod vectors of human disease worldwide transmitting malaria, lymphatic filariasis, and arboviruses such as dengue virus and Zika virus. Unfortunately, no treatment (in the form of vaccines or drugs) is available for most of these diseases andvectorcontrolisstillthemainformofprevention. Thelimitationsoftraditionalinsecticide-based strategies, particularly the development of insecticide resistance, have resulted in significant efforts to develop alternative eco-friendly methods. Biocontrol strategies aim to be sustainable and target a range of different mosquito species to reduce the current reliance on insecticide-based mosquito control. In thisreview, weoutline non-insecticide basedstrategiesthat havebeenimplemented orare currently being tested. We also highlight the use of mosquito behavioural knowledge that can be exploited for control strategies.

“An Unusual and Fast Disappearing Opportunity”: Infectious Disease, Indigenous Populations, and New Biomedical Knowledge in Amazonia, 1960–1970

PubMed Central

Dent, Rosanna; Santos, Ricardo Ventura

2018-01-01

In the twentieth century, biomedical researchers believed the study of Indigenous Amazonians could inform global histories of human biological diversity. This paper examines the similarities and differences of two approaches to this mid-century biomedical research, comparing the work of virologist and epidemiologist Francis Black with human geneticists James V. Neel and Francisco Salzano. While both groups were interested in Indigenous populations as representatives of the past, their perspectives on epidemics diverged. For Black, outbreaks of infectious diseases were central to his methodological and theoretical interests; for Neel and Salzano, epidemics could potentially compromise the epistemological value of their data. PMID:29622948

Challenges and opportunities for the control and elimination of porcine reproductive and respiratory syndrome virus.

PubMed

Rowland, R R R; Morrison, R B

2012-03-01

The control and elimination of porcine reproductive and respiratory syndrome virus (PRRSV) represent two of the most challenging tasks facing the pig industry worldwide. Several factors related to the biology of the virus make disease detection and elimination difficult. Efforts are further hampered by the lack of vaccines that can protect naïve herds from infection. With this in mind, elimination efforts are being initiated which incorporate existing tools and knowledge. A new approach extends herd control strategies to the level of a region. One example of success in PRRSV regional elimination is the Stevens County project in Minnesota. © 2012 Blackwell Verlag GmbH.

The integrated disease network.

PubMed

Sun, Kai; Buchan, Natalie; Larminie, Chris; Pržulj, Nataša

2014-11-01

The growing body of transcriptomic, proteomic, metabolomic and genomic data generated from disease states provides a great opportunity to improve our current understanding of the molecular mechanisms driving diseases and shared between diseases. The use of both clinical and molecular phenotypes will lead to better disease understanding and classification. In this study, we set out to gain novel insights into diseases and their relationships by utilising knowledge gained from system-level molecular data. We integrated different types of biological data including genome-wide association studies data, disease-chemical associations, biological pathways and Gene Ontology annotations into an Integrated Disease Network (IDN), a heterogeneous network where nodes are bio-entities and edges between nodes represent their associations. We also introduced a novel disease similarity measure to infer disease-disease associations from the IDN. Our predicted associations were systemically evaluated against the Medical Subject Heading classification and a statistical measure of disease co-occurrence in PubMed. The strong correlation between our predictions and co-occurrence associations indicated the ability of our approach to recover known disease associations. Furthermore, we presented a case study of Crohn's disease. We demonstrated that our approach not only identified well-established connections between Crohn's disease and other diseases, but also revealed new, interesting connections consistent with emerging literature. Our approach also enabled ready access to the knowledge supporting these new connections, making this a powerful approach for exploring connections between diseases.

Plants in silico: why, why now and what?--an integrative platform for plant systems biology research.

PubMed

Zhu, Xin-Guang; Lynch, Jonathan P; LeBauer, David S; Millar, Andrew J; Stitt, Mark; Long, Stephen P

2016-05-01

A paradigm shift is needed and timely in moving plant modelling from largely isolated efforts to a connected community endeavour that can take full advantage of advances in computer science and in mechanistic understanding of plant processes. Plants in silico (Psi) envisions a digital representation of layered dynamic modules, linking from gene networks and metabolic pathways through to cellular organization, tissue, organ and whole plant development, together with resource capture and use efficiency in dynamic competitive environments, ultimately allowing a mechanistically rich simulation of the plant or of a community of plants in silico. The concept is to integrate models or modules from different layers of organization spanning from genome to phenome to ecosystem in a modular framework allowing the use of modules of varying mechanistic detail representing the same biological process. Developments in high-performance computing, functional knowledge of plants, the internet and open-source version controlled software make achieving the concept realistic. Open source will enhance collaboration and move towards testing and consensus on quantitative theoretical frameworks. Importantly, Psi provides a quantitative knowledge framework where the implications of a discovery at one level, for example, single gene function or developmental response, can be examined at the whole plant or even crop and natural ecosystem levels. © 2015 The Authors Plant, Cell & Environment Published by John Wiley & Sons Ltd.

STARLIFE-An International Campaign to Study the Role of Galactic Cosmic Radiation in Astrobiological Model Systems.

PubMed

Moeller, Ralf; Raguse, Marina; Leuko, Stefan; Berger, Thomas; Hellweg, Christine Elisabeth; Fujimori, Akira; Okayasu, Ryuichi; Horneck, Gerda

2017-02-01

In-depth knowledge regarding the biological effects of the radiation field in space is required for assessing the radiation risks in space. To obtain this knowledge, a set of different astrobiological model systems has been studied within the STARLIFE radiation campaign during six irradiation campaigns (2013-2015). The STARLIFE group is an international consortium with the aim to investigate the responses of different astrobiological model systems to the different types of ionizing radiation (X-rays, γ rays, heavy ions) representing major parts of the galactic cosmic radiation spectrum. Low- and high-energy charged particle radiation experiments have been conducted at the Heavy Ion Medical Accelerator in Chiba (HIMAC) facility at the National Institute of Radiological Sciences (NIRS) in Chiba, Japan. X-rays or γ rays were used as reference radiation at the German Aerospace Center (DLR, Cologne, Germany) or Beta-Gamma-Service GmbH (BGS, Wiehl, Germany) to derive the biological efficiency of different radiation qualities. All samples were exposed under identical conditions to the same dose and qualities of ionizing radiation (i) allowing a direct comparison between the tested specimens and (ii) providing information on the impact of the space radiation environment on currently used astrobiological model organisms. Key Words: Space radiation environment-Sparsely ionizing radiation-Densely ionizing radiation-Heavy ions-Gamma radiation-Astrobiological model systems. Astrobiology 17, 101-109.

Integrative Sparse K-Means With Overlapping Group Lasso in Genomic Applications for Disease Subtype Discovery

PubMed Central

Huo, Zhiguang; Tseng, George

2017-01-01

Cancer subtypes discovery is the first step to deliver personalized medicine to cancer patients. With the accumulation of massive multi-level omics datasets and established biological knowledge databases, omics data integration with incorporation of rich existing biological knowledge is essential for deciphering a biological mechanism behind the complex diseases. In this manuscript, we propose an integrative sparse K-means (is-K means) approach to discover disease subtypes with the guidance of prior biological knowledge via sparse overlapping group lasso. An algorithm using an alternating direction method of multiplier (ADMM) will be applied for fast optimization. Simulation and three real applications in breast cancer and leukemia will be used to compare is-K means with existing methods and demonstrate its superior clustering accuracy, feature selection, functional annotation of detected molecular features and computing efficiency. PMID:28959370

Integrative Sparse K-Means With Overlapping Group Lasso in Genomic Applications for Disease Subtype Discovery.

PubMed

Huo, Zhiguang; Tseng, George

2017-06-01

Cancer subtypes discovery is the first step to deliver personalized medicine to cancer patients. With the accumulation of massive multi-level omics datasets and established biological knowledge databases, omics data integration with incorporation of rich existing biological knowledge is essential for deciphering a biological mechanism behind the complex diseases. In this manuscript, we propose an integrative sparse K -means (is- K means) approach to discover disease subtypes with the guidance of prior biological knowledge via sparse overlapping group lasso. An algorithm using an alternating direction method of multiplier (ADMM) will be applied for fast optimization. Simulation and three real applications in breast cancer and leukemia will be used to compare is- K means with existing methods and demonstrate its superior clustering accuracy, feature selection, functional annotation of detected molecular features and computing efficiency.

Managing biological networks by using text mining and computer-aided curation

NASA Astrophysics Data System (ADS)

Yu, Seok Jong; Cho, Yongseong; Lee, Min-Ho; Lim, Jongtae; Yoo, Jaesoo

2015-11-01

In order to understand a biological mechanism in a cell, a researcher should collect a huge number of protein interactions with experimental data from experiments and the literature. Text mining systems that extract biological interactions from papers have been used to construct biological networks for a few decades. Even though the text mining of literature is necessary to construct a biological network, few systems with a text mining tool are available for biologists who want to construct their own biological networks. We have developed a biological network construction system called BioKnowledge Viewer that can generate a biological interaction network by using a text mining tool and biological taggers. It also Boolean simulation software to provide a biological modeling system to simulate the model that is made with the text mining tool. A user can download PubMed articles and construct a biological network by using the Multi-level Knowledge Emergence Model (KMEM), MetaMap, and A Biomedical Named Entity Recognizer (ABNER) as a text mining tool. To evaluate the system, we constructed an aging-related biological network that consist 9,415 nodes (genes) by using manual curation. With network analysis, we found that several genes, including JNK, AP-1, and BCL-2, were highly related in aging biological network. We provide a semi-automatic curation environment so that users can obtain a graph database for managing text mining results that are generated in the server system and can navigate the network with BioKnowledge Viewer, which is freely available at http://bioknowledgeviewer.kisti.re.kr.

Investigating Novice and Expert Conceptions of Genetically Modified Organisms.

PubMed

Potter, Lisa M; Bissonnette, Sarah A; Knight, Jonathan D; Tanner, Kimberly D

2017-01-01

The aspiration of biology education is to give students tools to apply knowledge learned in the classroom to everyday life. Genetic modification is a real-world biological concept that relies on an in-depth understanding of the molecular behavior of DNA and proteins. This study investigated undergraduate biology students' conceptions of genetically modified organisms (GMOs) when probed with real-world, molecular and cellular, and essentialist cues, and how those conceptions compared across biology expertise. We developed a novel written assessment tool and administered it to 120 non-biology majors, 154 entering biology majors, 120 advanced biology majors (ABM), and nine biology faculty. Results indicated that undergraduate biology majors rarely included molecular and cellular rationales in their initial explanations of GMOs. Despite ABM demonstrating that they have much of the biology knowledge necessary to understand genetic modification, they did not appear to apply this knowledge to explaining GMOs. Further, this study showed that all undergraduate student populations exhibited evidence of essentialist thinking while explaining GMOs, regardless of their level of biology training. Finally, our results suggest an association between scientifically accurate ideas and the application of molecular and cellular rationales, as well as an association between misconceptions and essentialist rationales. © 2017 L. M. Potter et al. CBE—Life Sciences Education © 2016 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

A New Method Using Single-Particle Mass Spectrometry Data to Distinguish Mineral Dust and Biological Aerosols

NASA Astrophysics Data System (ADS)

Al-Mashat, H.; Kristensen, L.; Sultana, C. M.; Prather, K. A.

2016-12-01

The ability to distinguish types of particles present within a cloud is important for determining accurate inputs to climate models. The chemical composition of particles within cloud liquid droplets and ice crystals can have a significant impact on the timing, location, and amount of precipitation that falls. Precipitation efficiency is increased by the presence of ice crystals in clouds, and both mineral dust and biological aerosols have been shown to be effective ice nucleating particles (INPs) in the atmosphere. A current challenge in aerosol science is distinguishing mineral dust and biological material in the analysis of real-time, ambient, single-particle mass spectral data. Single-particle mass spectrometers are capable of measuring the size-resolved chemical composition of individual atmospheric particles. However, there is no consistent analytical method for distinguishing dust and biological aerosols. Sampling and characterization of control samples (i.e. of known identity) of mineral dust and bacteria were performed by the Aerosol Time-of-Flight Mass Spectrometer (ATOFMS) as part of the Fifth Ice Nucleation (FIN01) Workshop at the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) facility in Karlsruhe, Germany. Using data collected by the ATOFMS of control samples, a new metric has been developed to classify single particles as dust or biological independent of spectral cluster analysis. This method, involving the use of a ratio of mass spectral peak areas for organic nitrogen and silicates, is easily reproducible and does not rely on extensive knowledge of particle chemistry or the ionization characteristics of mass spectrometers. This represents a step toward rapidly distinguishing particle types responsible for ice nucleation activity during real-time sampling in clouds. The ability to distinguish types of particles present within a cloud is important for determining accurate inputs to climate models. The chemical composition of particles within cloud liquid droplets and ice crystals can have a significant impact on the timing, location, and amount of precipitation that falls. Precipitation efficiency is increased by the presence of ice crystals in clouds, and both mineral dust and biological aerosols have been shown to be effective ice nucleating particles (INPs) in the atmosphere. A current challenge in aerosol science is distinguishing mineral dust and biological material in the analysis of real-time, ambient, single-particle mass spectral data. Single-particle mass spectrometers are capable of measuring the size-resolved chemical composition of individual atmospheric particles. However, there is no consistent analytical method for distinguishing dust and biological aerosols. Sampling and characterization of control samples (i.e. of known identity) of mineral dust and bacteria were performed by the Aerosol Time-of-Flight Mass Spectrometer (ATOFMS) as part of the Fifth Ice Nucleation (FIN01) Workshop at the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) facility in Karlsruhe, Germany. Using data collected by the ATOFMS of control samples, a new metric has been developed to classify single particles as dust or biological independent of spectral cluster analysis. This method, involving the use of a ratio of mass spectral peak areas for organic nitrogen and silicates, is easily reproducible and does not rely on extensive knowledge of particle chemistry or the ionization characteristics of mass spectrometers. This represents a step toward rapidly distinguishing particle types responsible for ice nucleation activity during real-time sampling in clouds.

Exploring science teachers' pedagogical content knowledge in the teaching of genetics in Swaziland

NASA Astrophysics Data System (ADS)

Mthethwa-Kunene, Khetsiwe Eunice Faith

Recent trends show that learners' enrolment and performance in science at secondary school level is dwindling. Some science topics including genetics in biology are said to be difficult for learners to learn and thus they perform poorly in examinations. Teacher knowledge base, particularly topic-specific pedagogical content knowledge (PCK), has been identified by many researchers as an important factor that is linked with learner understanding and achievement in science. This qualitative study was an attempt to explore the PCK of four successful biology teachers and how they developed it in the context of teaching genetics. The purposive sampling technique was employed to select the participating teachers based on their schools' performance in biology public examinations and recommendations by science specialists and school principals. Pedagogical content knowledge was used as a theoretical framework for the study, which guided the inquiry in data collection, analysis and discussion of the research findings. The study adopted the case study method and various sources of evidence including concept maps, lesson plans, pre-lesson interviews, lesson observations, post-teaching teacher questionnaire, post-lesson interviews and document analysis were used to collect data on teachers' PCK as well as how PCK was assumed to have developed. The data were analysed in an attempt to determine the individual teachers' school genetics' content knowledge, related knowledge of instructional strategies and knowledge of learners' preconceptions and learning difficulties. The analysis involved an iterative process of coding data into PCK categories of content knowledge, pedagogical knowledge and knowledge of learners' preconceptions and learning difficulties. The findings of the study indicate that the four successful biology teachers generally have the necessary content knowledge of school genetics, used certain topic-specific instructional strategies, but lacked knowledge of genetics-related learners' preconceptions and learning difficulties despite having taught the topic for many years. There were some instructional deficits in their approaches and techniques in teaching genetics. The teachers failed to use physical models, teacher demonstration and/or learner experimentation in their lessons (or include them in their lesson plans) to assist learners in visualizing or internalizing the genetics concepts or processes located at the sub-microscopic level. The teachers' PCK in genetics teaching was assumed to have developed mainly through formal university education programmes, classroom teaching experiences, peer support and participation in in-service workshops. The implications for biology teacher education are also discussed.

Protecting Traditional Knowledge Related to Biological Resources: Is Scientific Research Going to Become More Bureaucratized?

PubMed

Reddy, Prashant; Lakshmikumaran, Malathi

2015-06-22

For the past several decades, there has been a world debate on the need for protecting traditional knowledge. A global treaty appears to be a distant reality. Of more immediate concern are the steps taken by the global community to protect access to biological resources in the name of protecting traditional knowledge. The Indian experience with implementing the Convention on Biological Diversity has created substantial legal uncertainty in collaborative scientific research between Indians and foreigners apart from bureaucratizing the entire process of scientific research, especially with regard to filing of applications for intellectual property rights. The issue therefore is whether the world needs to better balance the needs of the scientific community with the rights of those who have access to traditional knowledge. Copyright © 2015 Cold Spring Harbor Laboratory Press; all rights reserved.

The SwissLipids knowledgebase for lipid biology

PubMed Central

Liechti, Robin; Hyka-Nouspikel, Nevila; Niknejad, Anne; Gleizes, Anne; Götz, Lou; Kuznetsov, Dmitry; David, Fabrice P.A.; van der Goot, F. Gisou; Riezman, Howard; Bougueleret, Lydie; Xenarios, Ioannis; Bridge, Alan

2015-01-01

Motivation: Lipids are a large and diverse group of biological molecules with roles in membrane formation, energy storage and signaling. Cellular lipidomes may contain tens of thousands of structures, a staggering degree of complexity whose significance is not yet fully understood. High-throughput mass spectrometry-based platforms provide a means to study this complexity, but the interpretation of lipidomic data and its integration with prior knowledge of lipid biology suffers from a lack of appropriate tools to manage the data and extract knowledge from it. Results: To facilitate the description and exploration of lipidomic data and its integration with prior biological knowledge, we have developed a knowledge resource for lipids and their biology—SwissLipids. SwissLipids provides curated knowledge of lipid structures and metabolism which is used to generate an in silico library of feasible lipid structures. These are arranged in a hierarchical classification that links mass spectrometry analytical outputs to all possible lipid structures, metabolic reactions and enzymes. SwissLipids provides a reference namespace for lipidomic data publication, data exploration and hypothesis generation. The current version of SwissLipids includes over 244 000 known and theoretically possible lipid structures, over 800 proteins, and curated links to published knowledge from over 620 peer-reviewed publications. We are continually updating the SwissLipids hierarchy with new lipid categories and new expert curated knowledge. Availability: SwissLipids is freely available at http://www.swisslipids.org/. Contact: alan.bridge@isb-sib.ch Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25943471

Physical Samples Linked Data in Action

NASA Astrophysics Data System (ADS)

Ji, P.; Arko, R. A.; Lehnert, K.; Bristol, S.

2017-12-01

Most data and metadata related to physical samples currently reside in isolated relational databases driven by diverse data models. How to approach the challenge for sharing, interchanging and integrating data from these difference relational databases motivated us to publish Linked Open Data for collections of physical samples, using Semantic Web technologies including the Resource Description Framework (RDF), RDF Query Language (SPARQL), and Web Ontology Language (OWL). In last few years, we have released four knowledge graphs concentrated on physical samples, including System for Earth Sample Registration (SESAR), USGS National Geochemical Database (NGDC), Ocean Biogeographic Information System (OBIS), and Earthchem Database. Currently the four knowledge graphs contain over 12 million facets (triples) about objects of interest to the geoscience domain. Choosing appropriate domain ontologies for representing context of data is the core of the whole work. Geolink ontology developed by Earthcube Geolink project was used as top level to represent common concepts like person, organization, cruise, etc. Physical sample ontology developed by Interdisciplinary Earth Data Alliance (IEDA) and Darwin Core vocabulary were used as second level to describe details about geological samples and biological diversity. We also focused on finding and building best tool chains to support the whole life cycle of publishing linked data we have, including information retrieval, linked data browsing and data visualization. Currently, Morph, Virtuoso Server, LodView, LodLive, and YASGUI were employed for converting, storing, representing, and querying data in a knowledge base (RDF triplestore). Persistent digital identifier is another main point we concentrated on. Open Researcher & Contributor IDs (ORCIDs), International Geo Sample Numbers (IGSNs), Global Research Identifier Database (GRID) and other persistent identifiers were used to link different resources from various graphs with person, sample, organization, cruise, etc. This work is supported by the EarthCube "GeoLink" project (NSF# ICER14-40221 and others) and the "USGS-IEDA Partnership to Support a Data Lifecycle Framework and Tools" project (USGS# G13AC00381).

Semantics-driven modelling of user preferences for information retrieval in the biomedical domain.

PubMed

Gladun, Anatoly; Rogushina, Julia; Valencia-García, Rafael; Béjar, Rodrigo Martínez

2013-03-01

A large amount of biomedical and genomic data are currently available on the Internet. However, data are distributed into heterogeneous biological information sources, with little or even no organization. Semantic technologies provide a consistent and reliable basis with which to confront the challenges involved in the organization, manipulation and visualization of data and knowledge. One of the knowledge representation techniques used in semantic processing is the ontology, which is commonly defined as a formal and explicit specification of a shared conceptualization of a domain of interest. The work presented here introduces a set of interoperable algorithms that can use domain and ontological information to improve information-retrieval processes. This work presents an ontology-based information-retrieval system for the biomedical domain. This system, with which some experiments have been carried out that are described in this paper, is based on the use of domain ontologies for the creation and normalization of lightweight ontologies that represent user preferences in a determined domain in order to improve information-retrieval processes.

Aporrectodea caliginosa, a relevant earthworm species for a posteriori pesticide risk assessment: current knowledge and recommendations for culture and experimental design.

PubMed

Bart, Sylvain; Amossé, Joël; Lowe, Christopher N; Mougin, Christian; Péry, Alexandre R R; Pelosi, Céline

2018-06-21

Ecotoxicological tests with earthworms are widely used and are mandatory for the risk assessment of pesticides prior to registration and commercial use. The current model species for standardized tests is Eisenia fetida or Eisenia andrei. However, these species are absent from agricultural soils and often less sensitive to pesticides than other earthworm species found in mineral soils. To move towards a better assessment of pesticide effects on non-target organisms, there is a need to perform a posteriori tests using relevant species. The endogeic species Aporrectodea caliginosa (Savigny, 1826) is representative of cultivated fields in temperate regions and is suggested as a relevant model test species. After providing information on its taxonomy, biology, and ecology, we reviewed current knowledge concerning its sensitivity towards pesticides. Moreover, we highlighted research gaps and promising perspectives. Finally, advice and recommendations are given for the establishment of laboratory cultures and experiments using this soil-dwelling earthworm species.

Extremophiles and the search for extraterrestrial life.

PubMed

Cavicchioli, Ricardo

2002-01-01

Extremophiles thrive in ice, boiling water, acid, the water core of nuclear reactors, salt crystals, and toxic waste and in a range of other extreme habitats that were previously thought to be inhospitable for life. Extremophiles include representatives of all three domains (Bacteria, Archaea, and Eucarya); however, the majority are microorganisms, and a high proportion of these are Archaea. Knowledge of extremophile habitats is expanding the number and types of extraterrestrial locations that may be targeted for exploration. In addition, contemporary biological studies are being fueled by the increasing availability of genome sequences and associated functional studies of extremophiles. This is leading to the identification of new biomarkers, an accurate assessment of cellular evolution, insight into the ability of microorganisms to survive in meteorites and during periods of global extinction, and knowledge of how to process and examine environmental samples to detect viable life forms. This paper evaluates extremophiles and extreme environments in the context of astrobiology and the search for extraterrestrial life.

Mycorrhizal compatibility and symbiotic reproduction of Gavilea australis, an endangered terrestrial orchid from south Patagonia.

PubMed

Fracchia, Sebastián; Aranda-Rickert, Adriana; Flachsland, Eduardo; Terada, Graciela; Sede, Silvana

2014-11-01

Gavilea australis is a terrestrial orchid endemic from insular south Argentina and Chile. Meeting aspects of mycorrhizal fungi identity and compatibility in this orchid species is essential for propagation and conservation purposes. These knowledge represent also a first approach to elucidate the mycorrhizal specificity of this species. In order to evaluate both the mycorrhizal compatibility and the symbiotic seed germination of G. australis, we isolated and identified its root endophytic fungal strains as well as those from two sympatric species: Gavilea lutea and Codonorchis lessonii. In addition, we tested two other strains isolated from allopatric terrestrial orchid species from central Argentina. All fungal strains formed coilings and pelotons inside protocorms and promoted, at varying degrees, seed germination, and protocorm development until seedlings had two to three leaves. These results suggest a low mycorrhizal specificity of G. australis and contribute to a better knowledge of the biology of this orchid as well as of other sympatric Patagonian orchid species, all of them currently under serious risk of extinction.

Female students receiving post-secondary education in Greece: the results of a collaborative human papillomavirus knowledge survey.

PubMed

Michail, G; Smaili, M; Vozikis, A; Jelastopulu, E; Adonakis, G; Poulas, K

2014-12-01

Contrary to the optimistic forecasts, existing until 2008 and despite the incorporation of the vaccine into the Greek National Immunization Program, six years later, the percentage of HPV vaccination coverage in Greece remains disappointingly low. The aim of this extended study was to investigate the knowledge, behaviour and attitude of a representative sample of the initial target group; young female students of Greek higher education institutions to Pap cervical screening, biology of HPV infection and principles of HPV vaccination. Cross-sectional study. One thousand two hundred ten (1210) questionnaires were completed by young female students aged 17-24 years. The survey questionnaire sought data relating to sociodemographic characteristics, health behaviour and knowledge about HPV, as well as vaccination status. 79.6% of the sample reported at least one annual gynaecologic examination and 92.6% were familiar with the rationale of cervical screening; however only 52.9% had undergone a Pap smear. 69.7% reported adequate knowledge about HPV and 89.3% were aware of the possible course of HPV infection. Despite most (95.9%) were aware of vaccine availability, vaccinated students represented only 33.1%. According to the multivariate analysis, vaccination status was associated with university studies (OR 1.96; 95% CI: 1.19-3.20), parental area of expertise (OR 2.77; 95% CI: 1.18-6.53, OR 2.03; 95% CI: 1.05-3.94), and adequate knowledge of the reasons for which women should undergo regular cervical screening (OR 4.23; 85% CI: 1.55-11.55). Fear of side-effects and equivocal information were the main reasons of non-vaccination (52.2% and 33.1% respectively). Finally, the majority of unvaccinated individuals showed a positive attitude towards prospective HPV vaccination, providing they received well-documented advising. Young women attending Greek higher education exhibit a good level of knowledge about HPV and its correlation with cervical cancer. These data highlight the need for further sensitization of the general population. Copyright © 2014 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

An ethnomedicinal study of the Seri people; a group of hunter-gatherers and fishers native to the Sonoran Desert.

PubMed

Narchi, Nemer E; Aguilar-Rosas, Luis Ernesto; Sánchez-Escalante, José Jesús; Waumann-Rojas, Dora Ofelia

2015-08-11

Worldwide, coastal communities' ethnomedicinal knowledge has been sporadically recorded and poorly understood. Based on the ethnomedicinal knowledge of the Seri people; a hunting-gathering and fishing society of Northwestern Mexico, this study assesses a) the biological richness of Seri ethnomedicinal knowledge, b) the fidelity level of Seri remedies, and c) the association between gender, age, years of formal schooling and Seri ethnomedicinal knowledge. To assess the degree of ethnomedicinal knowledge proficiency, we conducted 75 open-ended semi-structured interviews collecting information on ethnomedicinal knowledge of marine and terrestrial organisms and the socio-demographic profile of each collaborator. With the support of primary collaborators, we collected the materials to be used as stimuli along our interviews. A correlation analysis was used to determine the relationship between gender, literacy and age with the ethnomedicinal knowledge proficiency. A paired t-test was used to determine differences in the number of remedies known by gender among members of the Seri community. A total of 28 medicinal specimens were presented as stimuli material. Marine remedies (12 species), were represented by 4 algae, 3 mollusks, 3 echinoderms, on reptile, and one annelid. Terrestrial plants (13 species) were distributed in 12 families. About 40 % of marine preparations used the organism in whole. In contrast, 29 % of of the remedies involving plants made use of leafy branches. Stimuli materials are used against 17 ailments mainly, being diarrhea, colds, menstrual problems, and swelling the ailments against most organisms (44 %) are used for. Marine organisms presented higher fidelity level values overall, suggesting that lower fidelity levels in terrestrial plants reflect a process of continuous and ongoing experimentation with easily accessible biological materials. Highest fidelity level values were recorded for Atriplex barclayana (93.87 %) Batis maritima (84.37 %), and Turbo fluctuosus (84.21 %). Age moderately correlates to ethnomedicinal knowledge proficiency (r = 0.41). Conversely, years of formal schooling show a negative correlation with ethnomedicinal knowledge proficiency (r = -0.49). Significant differences (p <0.05) were observed on ethnomedicinal knowledge proficiency when gender groups were compared under a paired t-test. This research contributes to describing the complex biodiversity present in the ethnomedicinal systems of coastal non-agricultural societies. In addition, our research improves our understanding of the role that gender plays in the intra-cultural distribution of ethnomedicinal knowledge among Seri. Our results broaden our understanding of human adaptations to coastal and xeric environments. This research can potentially benefit the development of proposals to improve coastal and marine resource management and conservation while strengthening ethnomedicinal knowledge systems in populations, such as the Seri, limited by precarious socio-economic conditions and inadequate health services.

Knowledge Discovery in Biological Databases for Revealing Candidate Genes Linked to Complex Phenotypes.

PubMed

Hassani-Pak, Keywan; Rawlings, Christopher

2017-06-13

Genetics and "omics" studies designed to uncover genotype to phenotype relationships often identify large numbers of potential candidate genes, among which the causal genes are hidden. Scientists generally lack the time and technical expertise to review all relevant information available from the literature, from key model species and from a potentially wide range of related biological databases in a variety of data formats with variable quality and coverage. Computational tools are needed for the integration and evaluation of heterogeneous information in order to prioritise candidate genes and components of interaction networks that, if perturbed through potential interventions, have a positive impact on the biological outcome in the whole organism without producing negative side effects. Here we review several bioinformatics tools and databases that play an important role in biological knowledge discovery and candidate gene prioritization. We conclude with several key challenges that need to be addressed in order to facilitate biological knowledge discovery in the future.

Teaching About "Brain and Learning" in High School Biology Classes: Effects on Teachers' Knowledge and Students' Theory of Intelligence.

PubMed

Dekker, Sanne; Jolles, Jelle

2015-01-01

This study evaluated a new teaching module about "Brain and Learning" using a controlled design. The module was implemented in high school biology classes and comprised three lessons: (1) brain processes underlying learning; (2) neuropsychological development during adolescence; and (3) lifestyle factors that influence learning performance. Participants were 32 biology teachers who were interested in "Brain and Learning" and 1241 students in grades 8-9. Teachers' knowledge and students' beliefs about learning potential were examined using online questionnaires. Results indicated that before intervention, biology teachers were significantly less familiar with how the brain functions and develops than with its structure and with basic neuroscientific concepts (46 vs. 75% correct answers). After intervention, teachers' knowledge of "Brain and Learning" had significantly increased (64%), and more students believed that intelligence is malleable (incremental theory). This emphasizes the potential value of a short teaching module, both for improving biology teachers' insights into "Brain and Learning," and for changing students' beliefs about intelligence.

Integrated Analysis of Pharmacologic, Clinical, and SNP Microarray Data using Projection onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing

PubMed Central

Pounds, Stan; Cao, Xueyuan; Cheng, Cheng; Yang, Jun; Campana, Dario; Evans, William E.; Pui, Ching-Hon; Relling, Mary V.

2010-01-01

Powerful methods for integrated analysis of multiple biological data sets are needed to maximize interpretation capacity and acquire meaningful knowledge. We recently developed Projection Onto the Most Interesting Statistical Evidence (PROMISE). PROMISE is a statistical procedure that incorporates prior knowledge about the biological relationships among endpoint variables into an integrated analysis of microarray gene expression data with multiple biological and clinical endpoints. Here, PROMISE is adapted to the integrated analysis of pharmacologic, clinical, and genome-wide genotype data that incorporating knowledge about the biological relationships among pharmacologic and clinical response data. An efficient permutation-testing algorithm is introduced so that statistical calculations are computationally feasible in this higher-dimension setting. The new method is applied to a pediatric leukemia data set. The results clearly indicate that PROMISE is a powerful statistical tool for identifying genomic features that exhibit a biologically meaningful pattern of association with multiple endpoint variables. PMID:21516175

On the Limitations of Biological Knowledge

PubMed Central

Dougherty, Edward R; Shmulevich, Ilya

2012-01-01

Scientific knowledge is grounded in a particular epistemology and, owing to the requirements of that epistemology, possesses limitations. Some limitations are intrinsic, in the sense that they depend inherently on the nature of scientific knowledge; others are contingent, depending on the present state of knowledge, including technology. Understanding limitations facilitates scientific research because one can then recognize when one is confronted by a limitation, as opposed to simply being unable to solve a problem within the existing bounds of possibility. In the hope that the role of limiting factors can be brought more clearly into focus and discussed, we consider several sources of limitation as they apply to biological knowledge: mathematical complexity, experimental constraints, validation, knowledge discovery, and human intellectual capacity. PMID:23633917

A biological compression model and its applications.

PubMed

Cao, Minh Duc; Dix, Trevor I; Allison, Lloyd

2011-01-01

A biological compression model, expert model, is presented which is superior to existing compression algorithms in both compression performance and speed. The model is able to compress whole eukaryotic genomes. Most importantly, the model provides a framework for knowledge discovery from biological data. It can be used for repeat element discovery, sequence alignment and phylogenetic analysis. We demonstrate that the model can handle statistically biased sequences and distantly related sequences where conventional knowledge discovery tools often fail.

The Effects of the SUN Project on Teacher Knowledge and Self-Efficacy Regarding Biological Energy Transfer Are Significant and Long-Lasting: Results of a Randomized Controlled Trial

PubMed Central

Batiza, Ann Finney; Gruhl, Mary; Zhang, Bo; Harrington, Tom; Roberts, Marisa; LaFlamme, Donna; Haasch, Mary Anne; Knopp, Jonathan; Vogt, Gina; Goodsell, David; Hagedorn, Eric; Marcey, David; Hoelzer, Mark; Nelson, Dave

2013-01-01

Biological energy flow has been notoriously difficult to teach. Our approach to this topic relies on abiotic and biotic examples of the energy released by moving electrons in thermodynamically spontaneous reactions. A series of analogical model-building experiences was supported with common language and representations including manipulatives. These materials were designed to help learners understand why electrons move in a hydrogen explosion and hydrogen fuel cell, so they could ultimately understand the rationale for energy transfer in the mitochondrion and the chloroplast. High school biology teachers attended a 2-wk Students Understanding eNergy (SUN) workshop during a randomized controlled trial. These treatment group teachers then took hydrogen fuel cells, manipulatives, and other materials into their regular biology classrooms. In this paper, we report significant gains in teacher knowledge and self-efficacy regarding biological energy transfer in the treatment group versus randomized controls. Significant effects on treatment group teacher knowledge and self-efficacy were found not only post–SUN workshop but even 1 yr later. Teacher knowledge was measured with both a multiple-choice exam and a drawing with a written explanation. Teacher confidence in their ability to teach biological energy transfer was measured by a modified form of the Science Teaching Efficacy Belief Instrument, In-Service A. Professional development implications regarding this topic are discussed. PMID:23737635

The effects of the SUN project on teacher knowledge and self-efficacy regarding biological energy transfer are significant and long-lasting: results of a randomized controlled trial.

PubMed

Batiza, Ann Finney; Gruhl, Mary; Zhang, Bo; Harrington, Tom; Roberts, Marisa; LaFlamme, Donna; Haasch, Mary Anne; Knopp, Jonathan; Vogt, Gina; Goodsell, David; Hagedorn, Eric; Marcey, David; Hoelzer, Mark; Nelson, Dave

2013-06-01

Biological energy flow has been notoriously difficult to teach. Our approach to this topic relies on abiotic and biotic examples of the energy released by moving electrons in thermodynamically spontaneous reactions. A series of analogical model-building experiences was supported with common language and representations including manipulatives. These materials were designed to help learners understand why electrons move in a hydrogen explosion and hydrogen fuel cell, so they could ultimately understand the rationale for energy transfer in the mitochondrion and the chloroplast. High school biology teachers attended a 2-wk Students Understanding eNergy (SUN) workshop during a randomized controlled trial. These treatment group teachers then took hydrogen fuel cells, manipulatives, and other materials into their regular biology classrooms. In this paper, we report significant gains in teacher knowledge and self-efficacy regarding biological energy transfer in the treatment group versus randomized controls. Significant effects on treatment group teacher knowledge and self-efficacy were found not only post-SUN workshop but even 1 yr later. Teacher knowledge was measured with both a multiple-choice exam and a drawing with a written explanation. Teacher confidence in their ability to teach biological energy transfer was measured by a modified form of the Science Teaching Efficacy Belief Instrument, In-Service A. Professional development implications regarding this topic are discussed.

Development of the biology card sorting task to measure conceptual expertise in biology.

PubMed

Smith, Julia I; Combs, Elijah D; Nagami, Paul H; Alto, Valerie M; Goh, Henry G; Gourdet, Muryam A A; Hough, Christina M; Nickell, Ashley E; Peer, Adrian G; Coley, John D; Tanner, Kimberly D

2013-01-01

There are widespread aspirations to focus undergraduate biology education on teaching students to think conceptually like biologists; however, there is a dearth of assessment tools designed to measure progress from novice to expert biological conceptual thinking. We present the development of a novel assessment tool, the Biology Card Sorting Task, designed to probe how individuals organize their conceptual knowledge of biology. While modeled on tasks from cognitive psychology, this task is unique in its design to test two hypothesized conceptual frameworks for the organization of biological knowledge: 1) a surface feature organization focused on organism type and 2) a deep feature organization focused on fundamental biological concepts. In this initial investigation of the Biology Card Sorting Task, each of six analytical measures showed statistically significant differences when used to compare the card sorting results of putative biological experts (biology faculty) and novices (non-biology major undergraduates). Consistently, biology faculty appeared to sort based on hypothesized deep features, while non-biology majors appeared to sort based on either surface features or nonhypothesized organizational frameworks. Results suggest that this novel task is robust in distinguishing populations of biology experts and biology novices and may be an adaptable tool for tracking emerging biology conceptual expertise.

Issues In Space Radiation Protection: Galactic Cosmic Rays

NASA Technical Reports Server (NTRS)

Wilson, J. W.; Kim, M.; Schimmerling, W.; Badavi, F. F.; Thibeault, S. A.; Cucinotta, F. A.; Shinn, J. L.; Kiefer, R.

1995-01-01

When shielding from cosmic heavy ions, one is faced with limited knowledge about the physical properties and biological responses of these radiations. Herein, the current health is discussed in terms of conventional protection practice and a test biological response model. The impact of biological response on optimum materials selection for cosmic ray shielding is presented in terms of the transmission characteristics of the shield material. Although liquid hydrogen is an optimum shield material, evaluation of the effectiveness of polymeric structural materials must await improvement in our knowledge of both the biological response and the nuclear processes.

[Problems of world outlook and methodology of science integration in biological studies].

PubMed

Khododova, Iu D

1981-01-01

Problems of worldoutlook and methodology of the natural-science knowledge are considered basing on the analysis of tendencies in the development of the membrane theory of cell processes and the use of principles of biological membrane functioning when solving some scientific and applied problems pertaining to different branches of chemistry and biology. The notion scientific knowledge integration is defined as interpenetration of approaches, methods and ideas of different branches of knowledge and enrichment on this basis of their content resulting in knowledge augmentation in each field taken separately. These processes are accompanied by appearance of new branches of knowledge - sciences "on junction" and their subsequent differentiations. The analysis of some gnoseological situations shows that integration of sciences contributes to coordination and some agreement of thinking styles of different specialists, puts forward keen personality of a scientist demanding, in particular, his high professional mobility. Problems of scientific activity organization are considered, which involve social sciences into the integration processes. The role of philosophy in the integration processes is emphasized.

[History of the Strasbourg Society of Biology].

PubMed

Antony, Pierre; Romier, Christophe; Mantz, Jean-Marie

2017-01-01

The Society of Biology of Strasbourg (SBS) is a learned society that was created in 1919 based on the model of the Society of Biology of which it is a subsidiary. Like its Parisian colleague, SBS aims at diffusing and promoting scientific knowledge in biology. To achieve this goal, SBS initiated since its creation a dialogue interface between researchers in biology and physicians, and more recently with other scientific disciplines, industry and the civil society. At the dawn of its first century, the Society of Biology of Strasbourg must continue to reinvent itself to pursue its development and to fulfil its mission of sharing scientific knowledge. This work continues in strong collaboration with our partners that share with SBS the willingness to foster excellence in biological research in Strasbourg, its region and beyond. © Société de Biologie, 2017.

Systems Biology for Organotypic Cell Cultures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis J.

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data. This consensus report summarizes the discussions held.« less

Workshop Report: Systems Biology for Organotypic Cell Cultures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis Joseph

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.« less

Workshop Report: Systems Biology for Organotypic Cell Cultures

DOE PAGES

Grego, Sonia; Dougherty, Edward R.; Alexander, Francis Joseph; ...

2016-11-14

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomicmore » data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.« less

Systems biology for organotypic cell cultures.

PubMed

Grego, Sonia; Dougherty, Edward R; Alexander, Francis J; Auerbach, Scott S; Berridge, Brian R; Bittner, Michael L; Casey, Warren; Cooley, Philip C; Dash, Ajit; Ferguson, Stephen S; Fennell, Timothy R; Hawkins, Brian T; Hickey, Anthony J; Kleensang, Andre; Liebman, Michael N J; Martin, Florian; Maull, Elizabeth A; Paragas, Jason; Qiao, Guilin Gary; Ramaiahgari, Sreenivasa; Sumner, Susan J; Yoon, Miyoung

2017-01-01

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, "organotypic" cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomic data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.

Omics Advances in Ecotoxicology.

PubMed

Zhang, Xiaowei; Xia, Pu; Wang, Pingping; Yang, Jianghu; Baird, Donald J

2018-04-03

Toxic substances in the environment generate adverse effects at all levels of biological organization from the molecular level to community and ecosystem. Given this complexity, it is not surprising that ecotoxicologists have struggled to address the full consequences of toxic substance release at ecosystem level, due to the limits of observational and experimental tools to reveal the changes in deep structure at different levels of organization. -Omics technologies, consisting of genomics and ecogenomics, have the power to reveal, in unprecedented detail, the cellular processes of an individual or biodiversity of a community in response to environmental change with high sample/observation throughput. This represents a historic opportunity to transform the way we study toxic substances in ecosystems, through direct linkage of ecological effects with the systems biology of organisms. Three recent examples of -omics advance in the assessment of toxic substances are explored here: (1) the use of functional genomics in the discovery of novel molecular mechanisms of toxicity of chemicals in the environment; (2) the development of laboratory pipelines of dose-dependent, reduced transcriptomics to support high-throughput chemical testing at the biological pathway level; and (3) the use of eDNA metabarcoding approaches for assessing chemical effects on biological communities in mesocosm experiments and through direct observation in field monitoring. -Omics advances in ecotoxicological studies not only generate new knowledge regarding mechanisms of toxicity and environmental effect, improving the relevance and immediacy of laboratory toxicological assessment, but can provide a wholly new paradigm for ecotoxicology by linking ecological models to mechanism-based, systems biology approaches.

Glycosylation Is a Major Regulator of Phenylpropanoid Availability and Biological Activity in Plants

PubMed Central

Le Roy, Julien; Huss, Brigitte; Creach, Anne; Hawkins, Simon; Neutelings, Godfrey

2016-01-01

The phenylpropanoid pathway in plants is responsible for the biosynthesis of a huge amount of secondary metabolites derived from phenylalanine and tyrosine. Both flavonoids and lignins are synthesized at the end of this very diverse metabolic pathway, as well as many intermediate molecules whose precise biological functions remain largely unknown. The diversity of these molecules can be further increased under the action of UDP-glycosyltransferases (UGTs) leading to the production of glycosylated hydroxycinnamates and related aldehydes, alcohols and esters. Glycosylation can change phenylpropanoid solubility, stability and toxic potential, as well as influencing compartmentalization and biological activity. (De)-glycosylation therefore represents an extremely important regulation point in phenylpropanoid homeostasis. In this article we review recent knowledge on the enzymes involved in regulating phenylpropanoid glycosylation status and availability in different subcellular compartments. We also examine the potential link between monolignol glycosylation and lignification by exploring co-expression of lignin biosynthesis genes and phenolic (de)glycosylation genes. Of the different biological roles linked with their particular chemical properties, phenylpropanoids are often correlated with the plant's stress management strategies that are also regulated by glycosylation. UGTs can for instance influence the resistance of plants during infection by microorganisms and be involved in the mechanisms related to environmental changes. The impact of flavonoid glycosylation on the color of flowers, leaves, seeds and fruits will also be discussed. Altogether this paper underlies the fact that glycosylation and deglycosylation are powerful mechanisms allowing plants to regulate phenylpropanoid localisation, availability and biological activity. PMID:27303427

The Anisakis Transcriptome Provides a Resource for Fundamental and Applied Studies on Allergy-Causing Parasites

PubMed Central

Baird, Fiona J.; Su, Xiaopei; Aibinu, Ibukun; Nolan, Matthew J.; Sugiyama, Hiromu; Otranto, Domenico

2016-01-01

Background Food-borne nematodes of the genus Anisakis are responsible for a wide range of illnesses (= anisakiasis), from self-limiting gastrointestinal forms to severe systemic allergic reactions, which are often misdiagnosed and under-reported. In order to enhance and refine current diagnostic tools for anisakiasis, knowledge of the whole spectrum of parasite molecules transcribed and expressed by this parasite, including those acting as potential allergens, is necessary. Methodology/Principal Findings In this study, we employ high-throughput (Illumina) sequencing and bioinformatics to characterise the transcriptomes of two Anisakis species, A. simplex and A. pegreffii, and utilize this resource to compile lists of potential allergens from these parasites. A total of ~65,000,000 reads were generated from cDNA libraries for each species, and assembled into ~34,000 transcripts (= Unigenes); ~18,000 peptides were predicted from each cDNA library and classified based on homology searches, protein motifs and gene ontology and biological pathway mapping. Using comparative analyses with sequence data available in public databases, 36 (A. simplex) and 29 (A. pegreffii) putative allergens were identified, including sequences encoding ‘novel’ Anisakis allergenic proteins (i.e. cyclophilins and ABA-1 domain containing proteins). Conclusions/Significance This study represents a first step towards providing the research community with a curated dataset to use as a molecular resource for future investigations of the biology of Anisakis, including molecules putatively acting as allergens, using functional genomics, proteomics and immunological tools. Ultimately, an improved knowledge of the biological functions of these molecules in the parasite, as well as of their immunogenic properties, will assist the development of comprehensive, reliable and robust diagnostic tools. PMID:27472517

Finding a needle in the virus metagenome haystack--micro-metagenome analysis captures a snapshot of the diversity of a bacteriophage armoire.

PubMed

Ray, Jessica; Dondrup, Michael; Modha, Sejal; Steen, Ida Helene; Sandaa, Ruth-Anne; Clokie, Martha

2012-01-01

Viruses are ubiquitous in the oceans and critical components of marine microbial communities, regulating nutrient transfer to higher trophic levels or to the dissolved organic pool through lysis of host cells. Hydrothermal vent systems are oases of biological activity in the deep oceans, for which knowledge of biodiversity and its impact on global ocean biogeochemical cycling is still in its infancy. In order to gain biological insight into viral communities present in hydrothermal vent systems, we developed a method based on deep-sequencing of pulsed field gel electrophoretic bands representing key viral fractions present in seawater within and surrounding a hydrothermal plume derived from Loki's Castle vent field at the Arctic Mid-Ocean Ridge. The reduction in virus community complexity afforded by this novel approach enabled the near-complete reconstruction of a lambda-like phage genome from the virus fraction of the plume. Phylogenetic examination of distinct gene regions in this lambdoid phage genome unveiled diversity at loci encoding superinfection exclusion- and integrase-like proteins. This suggests the importance of fine-tuning lyosgenic conversion as a viral survival strategy, and provides insights into the nature of host-virus and virus-virus interactions, within hydrothermal plumes. By reducing the complexity of the viral community through targeted sequencing of prominent dsDNA viral fractions, this method has selectively mimicked virus dominance approaching that hitherto achieved only through culturing, thus enabling bioinformatic analysis to locate a lambdoid viral "needle" within the greater viral community "haystack". Such targeted analyses have great potential for accelerating the extraction of biological knowledge from diverse and poorly understood environmental viral communities.

A Biological Conception of Knowledge: One Problematic Consequence.

ERIC Educational Resources Information Center

Haroutunian, Sophie

1980-01-01

Piaget's use of the equilibrium model to define knowledge results in a cybernetic conception of knowledge that cannot explain how knowledge becomes possible. The knowledge that behaviors apply discriminately must be acquired, and cannot be programed, and therefore cannot be learned. (FG)

A Map-Based Service Supporting Different Types of Geographic Knowledge for the Public

PubMed Central

Zhou, Mengjie; Wang, Rui; Tian, Jing; Ye, Ning; Mai, Shumin

2016-01-01

The internet enables the rapid and easy creation, storage, and transfer of knowledge; however, services that transfer geographic knowledge and facilitate the public understanding of geographic knowledge are still underdeveloped to date. Existing online maps (or atlases) can support limited types of geographic knowledge. In this study, we propose a framework for map-based services to represent and transfer different types of geographic knowledge to the public. A map-based service provides tools to ensure the effective transfer of geographic knowledge. We discuss the types of geographic knowledge that should be represented and transferred to the public, and we propose guidelines and a method to represent various types of knowledge through a map-based service. To facilitate the effective transfer of geographic knowledge, tools such as auxiliary background knowledge and auxiliary map-reading tools are provided through interactions with maps. An experiment conducted to illustrate our idea and to evaluate the usefulness of the map-based service is described; the results demonstrate that the map-based service is useful for transferring different types of geographic knowledge. PMID:27045314

A Map-Based Service Supporting Different Types of Geographic Knowledge for the Public.

PubMed

Zhou, Mengjie; Wang, Rui; Tian, Jing; Ye, Ning; Mai, Shumin

2016-01-01

The internet enables the rapid and easy creation, storage, and transfer of knowledge; however, services that transfer geographic knowledge and facilitate the public understanding of geographic knowledge are still underdeveloped to date. Existing online maps (or atlases) can support limited types of geographic knowledge. In this study, we propose a framework for map-based services to represent and transfer different types of geographic knowledge to the public. A map-based service provides tools to ensure the effective transfer of geographic knowledge. We discuss the types of geographic knowledge that should be represented and transferred to the public, and we propose guidelines and a method to represent various types of knowledge through a map-based service. To facilitate the effective transfer of geographic knowledge, tools such as auxiliary background knowledge and auxiliary map-reading tools are provided through interactions with maps. An experiment conducted to illustrate our idea and to evaluate the usefulness of the map-based service is described; the results demonstrate that the map-based service is useful for transferring different types of geographic knowledge.

A Short Note on Haroutunian's View of Piaget's Biological Conception of Knowledge.

ERIC Educational Resources Information Center

Doll, William E., Jr.

1981-01-01

The author discusses major premises of a paper, by Sophie Haroutunian (Educational Theory, v30 n3), that relates Jean Piaget's conception of knowledge to his biological theory of equilibrium. Doll argues that Piaget's theory of equilibration (striving for control over the environment) is not sufficiently appreciated by Haroutunian. (PP)

Measuring the Disparities between Biology Undergraduates' Perceptions and Their Actual Knowledge of Scientific Literature with Clickers

ERIC Educational Resources Information Center

Bandyopadhyay, Aditi

2013-01-01

This article demonstrates an innovative method used to determine the need for information literacy among science undergraduate students at Adelphi University. Using clickers technology, this study measured the disconnect between biology undergraduates' perceived and actual knowledge of scientific literature. The quantitative data collected in the…

Indications of Knowledge Retention in the Transition to Higher Education

ERIC Educational Resources Information Center

Jones, Harriet; Black, Beth; Green, Jon; Langton, Phil; Rutherford, Stephen; Scott, Jon; Brown, Sally

2015-01-01

First year undergraduate courses in higher education tend to be designed based on assumptions of students' prior knowledge. Almost 600 undergraduates at five UK universities, studying biological sciences, were given an MCQ test in their first week at university, based on biology A-level (pre-university examination) core criteria. Results…

Pre-Service Science Teachers' Pedagogical Content Knowledge in the Physics, Chemistry, and Biology Topics

ERIC Educational Resources Information Center

Bektas, Oktay

2015-01-01

This study investigated pre-service science teachers' pedagogical content knowledge in the physics, chemistry, and biology topics. These topics were the light and sound, the physical and chemical changes, and reproduction, growth, and evolution. Qualitative research design was utilized. Data were collected from 33 pre-service science teachers…

S3QL: A distributed domain specific language for controlled semantic integration of life sciences data

PubMed Central

2011-01-01

Background The value and usefulness of data increases when it is explicitly interlinked with related data. This is the core principle of Linked Data. For life sciences researchers, harnessing the power of Linked Data to improve biological discovery is still challenged by a need to keep pace with rapidly evolving domains and requirements for collaboration and control as well as with the reference semantic web ontologies and standards. Knowledge organization systems (KOSs) can provide an abstraction for publishing biological discoveries as Linked Data without complicating transactions with contextual minutia such as provenance and access control. We have previously described the Simple Sloppy Semantic Database (S3DB) as an efficient model for creating knowledge organization systems using Linked Data best practices with explicit distinction between domain and instantiation and support for a permission control mechanism that automatically migrates between the two. In this report we present a domain specific language, the S3DB query language (S3QL), to operate on its underlying core model and facilitate management of Linked Data. Results Reflecting the data driven nature of our approach, S3QL has been implemented as an application programming interface for S3DB systems hosting biomedical data, and its syntax was subsequently generalized beyond the S3DB core model. This achievement is illustrated with the assembly of an S3QL query to manage entities from the Simple Knowledge Organization System. The illustrative use cases include gastrointestinal clinical trials, genomic characterization of cancer by The Cancer Genome Atlas (TCGA) and molecular epidemiology of infectious diseases. Conclusions S3QL was found to provide a convenient mechanism to represent context for interoperation between public and private datasets hosted at biomedical research institutions and linked data formalisms. PMID:21756325

Fishers' knowledge and seahorse conservation in Brazil

PubMed Central

Rosa, Ierecê ML; Alves, Rômulo RN; Bonifácio, Kallyne M; Mourão, José S; Osório, Frederico M; Oliveira, Tacyana PR; Nottingham, Mara C

2005-01-01

From a conservationist perspective, seahorses are threatened fishes. Concomitantly, from a socioeconomic perspective, they represent a source of income to many fishing communities in developing countries. An integration between these two views requires, among other things, the recognition that seahorse fishers have knowledge and abilities that can assist the implementation of conservation strategies and of management plans for seahorses and their habitats. This paper documents the knowledge held by Brazilian fishers on the biology and ecology of the longsnout seahorse Hippocampus reidi. Its aims were to explore collaborative approaches to seahorse conservation and management in Brazil; to assess fishers' perception of seahorse biology and ecology, in the context evaluating potential management options; to increase fishers' involvement with seahorse conservation in Brazil. Data were obtained through questionnaires and interviews made during field surveys conducted in fishing villages located in the States of Piauí, Ceará, Paraíba, Maranhão, Pernambuco and Pará. We consider the following aspects as positive for the conservation of seahorses and their habitats in Brazil: fishers were willing to dialogue with researchers; although captures and/or trade of brooding seahorses occurred, most interviewees recognized the importance of reproduction to the maintenance of seahorses in the wild (and therefore of their source of income), and expressed concern over population declines; fishers associated the presence of a ventral pouch with reproduction in seahorses (regardless of them knowing which sex bears the pouch), and this may facilitate the construction of collaborative management options designed to eliminate captures of brooding specimens; fishers recognized microhabitats of importance to the maintenance of seahorse wild populations; fishers who kept seahorses in captivity tended to recognize the condtions as poor, and as being a cause of seahorse mortality. PMID:16336660

Fishers' knowledge and seahorse conservation in Brazil.

PubMed

Rosa, Ierecê Ml; Alves, Rômulo Rn; Bonifácio, Kallyne M; Mourão, José S; Osório, Frederico M; Oliveira, Tacyana Pr; Nottingham, Mara C

2005-12-08

From a conservationist perspective, seahorses are threatened fishes. Concomitantly, from a socioeconomic perspective, they represent a source of income to many fishing communities in developing countries. An integration between these two views requires, among other things, the recognition that seahorse fishers have knowledge and abilities that can assist the implementation of conservation strategies and of management plans for seahorses and their habitats. This paper documents the knowledge held by Brazilian fishers on the biology and ecology of the longsnout seahorse Hippocampus reidi. Its aims were to explore collaborative approaches to seahorse conservation and management in Brazil; to assess fishers' perception of seahorse biology and ecology, in the context evaluating potential management options; to increase fishers' involvement with seahorse conservation in Brazil. Data were obtained through questionnaires and interviews made during field surveys conducted in fishing villages located in the States of Piauí, Ceará, Paraíba, Maranhão, Pernambuco and Pará. We consider the following aspects as positive for the conservation of seahorses and their habitats in Brazil: fishers were willing to dialogue with researchers; although captures and/or trade of brooding seahorses occurred, most interviewees recognized the importance of reproduction to the maintenance of seahorses in the wild (and therefore of their source of income), and expressed concern over population declines; fishers associated the presence of a ventral pouch with reproduction in seahorses (regardless of them knowing which sex bears the pouch), and this may facilitate the construction of collaborative management options designed to eliminate captures of brooding specimens; fishers recognized microhabitats of importance to the maintenance of seahorse wild populations; fishers who kept seahorses in captivity tended to recognize the condtions as poor, and as being a cause of seahorse mortality.

S3QL: a distributed domain specific language for controlled semantic integration of life sciences data.

PubMed

Deus, Helena F; Correa, Miriã C; Stanislaus, Romesh; Miragaia, Maria; Maass, Wolfgang; de Lencastre, Hermínia; Fox, Ronan; Almeida, Jonas S

2011-07-14

The value and usefulness of data increases when it is explicitly interlinked with related data. This is the core principle of Linked Data. For life sciences researchers, harnessing the power of Linked Data to improve biological discovery is still challenged by a need to keep pace with rapidly evolving domains and requirements for collaboration and control as well as with the reference semantic web ontologies and standards. Knowledge organization systems (KOSs) can provide an abstraction for publishing biological discoveries as Linked Data without complicating transactions with contextual minutia such as provenance and access control.We have previously described the Simple Sloppy Semantic Database (S3DB) as an efficient model for creating knowledge organization systems using Linked Data best practices with explicit distinction between domain and instantiation and support for a permission control mechanism that automatically migrates between the two. In this report we present a domain specific language, the S3DB query language (S3QL), to operate on its underlying core model and facilitate management of Linked Data. Reflecting the data driven nature of our approach, S3QL has been implemented as an application programming interface for S3DB systems hosting biomedical data, and its syntax was subsequently generalized beyond the S3DB core model. This achievement is illustrated with the assembly of an S3QL query to manage entities from the Simple Knowledge Organization System. The illustrative use cases include gastrointestinal clinical trials, genomic characterization of cancer by The Cancer Genome Atlas (TCGA) and molecular epidemiology of infectious diseases. S3QL was found to provide a convenient mechanism to represent context for interoperation between public and private datasets hosted at biomedical research institutions and linked data formalisms.

Network reconstruction based on proteomic data and prior knowledge of protein connectivity using graph theory.

PubMed

Stavrakas, Vassilis; Melas, Ioannis N; Sakellaropoulos, Theodore; Alexopoulos, Leonidas G

2015-01-01

Modeling of signal transduction pathways is instrumental for understanding cells' function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells' biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN) with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways' logic modeling using optimization formulations or machine learning algorithms have been published on this front over the past few years. Here, we introduce a light and fast approach that uses a breadth-first traversal of the graph to identify the shortest pathways and score proteins in the PKN, fitting the dependencies extracted from the experimental design. The pathways are then combined through a heuristic formulation to produce a final topology handling inconsistencies between the PKN and the experimental scenarios. Our results show that the algorithm we developed is efficient and accurate for the construction of medium and large scale signaling networks. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGF/TNFA stimulation against made up experimental data. To avoid the possibility of erroneous predictions, we performed a cross-validation analysis. Finally, we validate that the introduced approach generates predictive topologies, comparable to the ILP formulation. Overall, an efficient approach based on graph theory is presented herein to interrogate protein-protein interaction networks and to provide meaningful biological insights.

ChloroKB: A Web Application for the Integration of Knowledge Related to Chloroplast Metabolic Network.

PubMed

Gloaguen, Pauline; Bournais, Sylvain; Alban, Claude; Ravanel, Stéphane; Seigneurin-Berny, Daphné; Matringe, Michel; Tardif, Marianne; Kuntz, Marcel; Ferro, Myriam; Bruley, Christophe; Rolland, Norbert; Vandenbrouck, Yves; Curien, Gilles

2017-06-01

Higher plants, as autotrophic organisms, are effective sources of molecules. They hold great promise for metabolic engineering, but the behavior of plant metabolism at the network level is still incompletely described. Although structural models (stoichiometry matrices) and pathway databases are extremely useful, they cannot describe the complexity of the metabolic context, and new tools are required to visually represent integrated biocurated knowledge for use by both humans and computers. Here, we describe ChloroKB, a Web application (http://chlorokb.fr/) for visual exploration and analysis of the Arabidopsis ( Arabidopsis thaliana ) metabolic network in the chloroplast and related cellular pathways. The network was manually reconstructed through extensive biocuration to provide transparent traceability of experimental data. Proteins and metabolites were placed in their biological context (spatial distribution within cells, connectivity in the network, participation in supramolecular complexes, and regulatory interactions) using CellDesigner software. The network contains 1,147 reviewed proteins (559 localized exclusively in plastids, 68 in at least one additional compartment, and 520 outside the plastid), 122 proteins awaiting biochemical/genetic characterization, and 228 proteins for which genes have not yet been identified. The visual presentation is intuitive and browsing is fluid, providing instant access to the graphical representation of integrated processes and to a wealth of refined qualitative and quantitative data. ChloroKB will be a significant support for structural and quantitative kinetic modeling, for biological reasoning, when comparing novel data with established knowledge, for computer analyses, and for educational purposes. ChloroKB will be enhanced by continuous updates following contributions from plant researchers. © 2017 American Society of Plant Biologists. All Rights Reserved.

Eliciting and Representing High-Level Knowledge Requirements to Discover Ecological Knowledge in Flower-Visiting Data

PubMed Central

2016-01-01

Observations of individual organisms (data) can be combined with expert ecological knowledge of species, especially causal knowledge, to model and extract from flower–visiting data useful information about behavioral interactions between insect and plant organisms, such as nectar foraging and pollen transfer. We describe and evaluate a method to elicit and represent such expert causal knowledge of behavioral ecology, and discuss the potential for wider application of this method to the design of knowledge-based systems for knowledge discovery in biodiversity and ecosystem informatics. PMID:27851814

Using diagrams versus text for spaced restudy: Effects on learning in 10th grade biology classes.

PubMed

Bergey, Bradley W; Cromley, Jennifer G; Kirchgessner, Mandy L; Newcombe, Nora S

2015-03-01

Spaced restudy has been typically tested with written learning materials, but restudy with visual representations in actual classrooms is under-researched. We compared the effects of two spaced restudy interventions: A Diagram-Based Restudy (DBR) warm-up condition and a business-as-usual Text-Based Restudy (TBR) warm-up condition. One hundred and twenty-eight consented high school students in 15 classes. Students completed daily warm-ups over a 4-week period. Students were randomly assigned to conditions within classrooms. Warm-ups were independently completed at the start of class meetings and consisted of questions about content covered 1-10 days prior to each warm-up. Students received feedback on their answers each week. A series of ANOVAs and ANCOVAs was conducted. Results showed equal and significant growth from pre- to post-test for both conditions (d = .31-.67) on three outcomes: Biology knowledge, biology diagram comprehension (near transfer), and geology diagram comprehension (far transfer). ANCOVA results suggested that the magnitude of this increase was linked to the number of questions attempted during the intervention. For the DBR condition only, there were interactions with content knowledge on diagram comprehension gain scores and interactions with spatial scores on biology knowledge gain scores. Students with lower biology knowledge and lower Paper Folding Test scores were disadvantaged in the DBR condition, whereas the TBR condition was equitable across all levels of knowledge and spatial ability. © 2014 The British Psychological Society.

AlexSys: a knowledge-based expert system for multiple sequence alignment construction and analysis

PubMed Central

Aniba, Mohamed Radhouene; Poch, Olivier; Marchler-Bauer, Aron; Thompson, Julie Dawn

2010-01-01

Multiple sequence alignment (MSA) is a cornerstone of modern molecular biology and represents a unique means of investigating the patterns of conservation and diversity in complex biological systems. Many different algorithms have been developed to construct MSAs, but previous studies have shown that no single aligner consistently outperforms the rest. This has led to the development of a number of ‘meta-methods’ that systematically run several aligners and merge the output into one single solution. Although these methods generally produce more accurate alignments, they are inefficient because all the aligners need to be run first and the choice of the best solution is made a posteriori. Here, we describe the development of a new expert system, AlexSys, for the multiple alignment of protein sequences. AlexSys incorporates an intelligent inference engine to automatically select an appropriate aligner a priori, depending only on the nature of the input sequences. The inference engine was trained on a large set of reference multiple alignments, using a novel machine learning approach. Applying AlexSys to a test set of 178 alignments, we show that the expert system represents a good compromise between alignment quality and running time, making it suitable for high throughput projects. AlexSys is freely available from http://alnitak.u-strasbg.fr/∼aniba/alexsys. PMID:20530533

Total, chemical, and biological oxygen consumption of the sediments in the Ziya River watershed, China.

PubMed

Rong, Nan; Shan, Baoqing

2016-07-01

Sediment oxygen demand (SOD) is a critical dissolved oxygen (DO) sink in many rivers. Understanding the relative contributions of the biological and chemical components of SOD would improve our knowledge of the potential environmental harm SOD could cause and allow appropriate management systems to be developed. A various inhibitors addition technique was conducted to measure the total, chemical, and biological SOD of sediment samples from 13 sites in the Ziya River watershed, a severely polluted and anoxic river system in the north of China. The results showed that the major component of SOD was chemical SOD due to iron predominate. The ferrous SOD accounted for 21.6-78.9 % of the total SOD and 33.26-96.79 % of the chemical SOD. Biological SOD represented 41.13 % of the overall SOD averagely. Sulfide SOD accounted for 1.78-45.71 % of the total SOD and it was the secondary predominate of the chemical SOD. Manganous SOD accounted for 1.2-16.6 % of the total SOD and it was insignificant at many sites. Only four kinds of benthos were collected in the Ziya River watershed, resulting from the low DO concentration in the sediment surface due to SOD. This study would be helpful for understanding and preventing the potential sediment oxygen depletion during river restoration.

"Saber" and "Conocer."

ERIC Educational Resources Information Center

Taylor, Kathy

1985-01-01

Attempts to redefine the meaning of the two Spanish verbs "saber" and "conocer" and explores some possible extralinguistic factors affecting their usage. Shows that "conocer" represents knowledge which is firsthand and that this type of knowledge is a building block for the more thorough, systematic knowledge represented by "saber." (SED)

Iberian Odonata distribution: data of the BOS Arthropod Collection (University of Oviedo, Spain)

PubMed Central

Torralba-Burrial, Antonio; Ocharan, Francisco J.

2013-01-01

Abstract Odonata are represented from the Iberian Peninsula by 79 species. However, there exists a significant gap in accessible knowledge about these species,especially regarding their distribution. This data paper describes the specimen-based Odonata data of the Arthropod Collection of the Department of Biología de Organismos y Sistemas (BOS), University of Oviedo, Spain. The specimens were mainly collected from the Iberian Peninsula (98.63% of the data records), especially the northern region. The earliest specimen deposited in the collection dates back to 1950, while the 1980’s and 2000’s are the best-represented time periods. Between 1950 and 2009, 16, 604 Odonata specimens were deposited and are documented in the dataset. Approximately 20% of the specimens belong to the families Coenagrionidae and Calopterygidae. Specimens include the holotype and paratypes of the Iberian subspecies Calopteryx haemorrhoidalis asturica Ocharan, 1983 and Sympetrum vulgatum ibericum Ocharan, 1985. The complete dataset is also provided in Darwin Core Archive format. PMID:23794917

Iberian Odonata distribution: data of the BOS Arthropod Collection (University of Oviedo, Spain).

PubMed

Torralba-Burrial, Antonio; Ocharan, Francisco J

2013-01-01

Odonata are represented from the Iberian Peninsula by 79 species. However, there exists a significant gap in accessible knowledge about these species,especially regarding their distribution. This data paper describes the specimen-based Odonata data of the Arthropod Collection of the Department of Biología de Organismos y Sistemas (BOS), University of Oviedo, Spain. The specimens were mainly collected from the Iberian Peninsula (98.63% of the data records), especially the northern region. The earliest specimen deposited in the collection dates back to 1950, while the 1980's and 2000's are the best-represented time periods. Between 1950 and 2009, 16, 604 Odonata specimens were deposited and are documented in the dataset. Approximately 20% of the specimens belong to the families Coenagrionidae and Calopterygidae. Specimens include the holotype and paratypes of the Iberian subspecies Calopteryx haemorrhoidalis asturica Ocharan, 1983 and Sympetrum vulgatum ibericum Ocharan, 1985. The complete dataset is also provided in Darwin Core Archive format.

Long non-coding RNAs in B-cell malignancies: a comprehensive overview

PubMed Central

Taiana, Elisa; Neri, Antonino

2017-01-01

B-cell malignancies constitute a large part of hematological neoplasias. They represent a heterogeneous group of diseases, including Hodgkin's lymphoma, most non-Hodgkin's lymphomas (NHL), some leukemias and myelomas. B-cell malignancies reflect defined stages of normal B-cell differentiation and this represents the major basis for their classification. Long non-coding RNAs (lncRNAs) are non-protein-coding transcripts longer than 200 nucleotides, for which many recent studies have demonstrated a function in regulating gene expression, cell biology and carcinogenesis. Deregulated expression levels of lncRNAs have been observed in various types of cancers including hematological malignancies. The involvement of lncRNAs in cancer initiation and progression and their attractive features both as biomarker and for therapeutic research are becoming increasingly evident. In this review, we summarize the recent literature to highlight the status of the knowledge of lncRNAs role in normal B-cell development and in the pathogenesis of B-cell tumors. PMID:28947998

BioTCM-SE: a semantic search engine for the information retrieval of modern biology and traditional Chinese medicine.

PubMed

Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui

2014-01-01

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM.

BioTCM-SE: A Semantic Search Engine for the Information Retrieval of Modern Biology and Traditional Chinese Medicine

PubMed Central

Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui

2014-01-01

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM. PMID:24772189

Subject-specific pedagogical content knowledge: Implications for alternatively and traditionally trained biology teachers

NASA Astrophysics Data System (ADS)

Ravgiala, Rebekah Rae

Theories regarding the development of expertise hold implications for alternative and traditional certification programs and the teachers they train. The literature suggests that when compared to experts in the field of teaching, the behaviors of novices differ in ways that are directly attributed to their pedagogical content knowledge. However, few studies have examined how first and second year biology teachers entering the profession from traditional and alternative training differ in their demonstration of subject-specific pedagogical content knowledge. The research problem in this multicase, naturalistic inquiry investigated how subject-specific pedagogical content knowledge was manifested among first and second year biology teachers in the task of transforming subject matter into forms that are potentially meaningful to students when explicit formal training has been and has not been imparted to them as preservice teachers. Two first year and two second year biology teachers were the subjects of this investigation. Allen and Amber obtained their certification through an alternative summer training institute in consecutive years. Tiffany and Tricia obtained their certification through a traditional, graduate level training program in consecutive years. Both programs were offered at the same northeastern state university. Participants contributed to six data gathering techniques including an initial semi-structured interview, responses to the Conceptions of Teaching Science questionnaire (Hewson & Hewson, 1989), three videotaped biology lessons, evaluation of three corresponding lesson plans, and a final semi-structured interview conducted at the end of the investigation. An informal, end-of-study survey intended to offer participants an opportunity to disclose their thoughts and needs as first year teachers was also employed. Results indicate that while conceptions of teaching science may vary slightly among participants, there is no evidence to suggest that instructional strategies and lesson planning habits differ. The characteristics that may distinguish alternatively from traditionally trained biology teachers are subtle enough to be masked at this point in their careers by the more observable qualities that describe the behaviors and conceptions of beginning teachers. As a result, demonstration of subject-specific pedagogical content knowledge depends highly upon the ability of the individual teacher to transform his/her knowledge of content and pedagogy into meaningful forms for biology students.

Commentary: Prerequisite Knowledge

ERIC Educational Resources Information Center

Taylor, Ann T. S.

2013-01-01

Most biochemistry, genetics, cell biology, and molecular biology classes have extensive prerequisite or co-requisite requirements, often including introductory chemistry, introductory biology, and organic chemistry coursework. But what is the function of these prerequisites? While it seems logical that a basic understanding of biological and…

Learning Biology by Designing

ERIC Educational Resources Information Center

Janssen, Fred; Waarlo, Arend Jan

2010-01-01

According to a century-old tradition in biological thinking, organisms can be considered as being optimally designed. In modern biology this idea still has great heuristic value. In evolutionary biology a so-called design heuristic has been formulated which provides guidance to researchers in the generation of knowledge about biological systems.…

Finding gene regulatory network candidates using the gene expression knowledge base.

PubMed

Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

2014-12-10

Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

A Chado case study: an ontology-based modular schema for representing genome-associated biological information.

PubMed

Mungall, Christopher J; Emmert, David B

2007-07-01

A few years ago, FlyBase undertook to design a new database schema to store Drosophila data. It would fully integrate genomic sequence and annotation data with bibliographic, genetic, phenotypic and molecular data from the literature representing a distillation of the first 100 years of research on this major animal model system. In developing this new integrated schema, FlyBase also made a commitment to ensure that its design was generic, extensible and available as open source, so that it could be employed as the core schema of any model organism data repository, thereby avoiding redundant software development and potentially increasing interoperability. Our question was whether we could create a relational database schema that would be successfully reused. Chado is a relational database schema now being used to manage biological knowledge for a wide variety of organisms, from human to pathogens, especially the classes of information that directly or indirectly can be associated with genome sequences or the primary RNA and protein products encoded by a genome. Biological databases that conform to this schema can interoperate with one another, and with application software from the Generic Model Organism Database (GMOD) toolkit. Chado is distinctive because its design is driven by ontologies. The use of ontologies (or controlled vocabularies) is ubiquitous across the schema, as they are used as a means of typing entities. The Chado schema is partitioned into integrated subschemas (modules), each encapsulating a different biological domain, and each described using representations in appropriate ontologies. To illustrate this methodology, we describe here the Chado modules used for describing genomic sequences. GMOD is a collaboration of several model organism database groups, including FlyBase, to develop a set of open-source software for managing model organism data. The Chado schema is freely distributed under the terms of the Artistic License (http://www.opensource.org/licenses/artistic-license.php) from GMOD (www.gmod.org).

Molecular Biology of Nitrogen Fixation

ERIC Educational Resources Information Center

Shanmugam, K. T.; Valentine, Raymond C.

1975-01-01

Reports that as a result of our increasing knowledge of the molecular biology of nitrogen fixation it might eventually be possible to increase the biological production of nitrogenous fertilizer from atmospheric nitrogen. (GS)

Data Integration and Mining for Synthetic Biology Design.

PubMed

Mısırlı, Göksel; Hallinan, Jennifer; Pocock, Matthew; Lord, Phillip; McLaughlin, James Alastair; Sauro, Herbert; Wipat, Anil

2016-10-21

One aim of synthetic biologists is to create novel and predictable biological systems from simpler modular parts. This approach is currently hampered by a lack of well-defined and characterized parts and devices. However, there is a wealth of existing biological information, which can be used to identify and characterize biological parts, and their design constraints in the literature and numerous biological databases. However, this information is spread among these databases in many different formats. New computational approaches are required to make this information available in an integrated format that is more amenable to data mining. A tried and tested approach to this problem is to map disparate data sources into a single data set, with common syntax and semantics, to produce a data warehouse or knowledge base. Ontologies have been used extensively in the life sciences, providing this common syntax and semantics as a model for a given biological domain, in a fashion that is amenable to computational analysis and reasoning. Here, we present an ontology for applications in synthetic biology design, SyBiOnt, which facilitates the modeling of information about biological parts and their relationships. SyBiOnt was used to create the SyBiOntKB knowledge base, incorporating and building upon existing life sciences ontologies and standards. The reasoning capabilities of ontologies were then applied to automate the mining of biological parts from this knowledge base. We propose that this approach will be useful to speed up synthetic biology design and ultimately help facilitate the automation of the biological engineering life cycle.

[Knowledge about viral hepatitis in a sample of Brazilian students from Vale do Araguaia, Legal Amazonia].

PubMed

Ferrari, Carlos K B; Savazzi, Kamirri; Honorio-França, Adenilda C; Ferrari, Graziele S L; França, Eduardo L

2012-06-01

Viral and non-viral hepatitis are of great concern among developing nations because of their pathogenicity and virulence, and also their wide spreading by contaminated blood, food or water. The objective of this work was to evaluate the knowledge about hepatitis of academic students from three life/health sciences courses and also students from the last year of high school To measure the students' knowledge on hepatitis an instrument containing 22 questions was applied. Surprinsingly, it was verified that 41.9% of students had poor knowledge of viral hepatitis. Among the high school students, 31.8% ignored that viral hepatitis are infectious and transmissible diseases. Considering hepatitis symptomatology, just 18% of high school students declared knowledge of the symptons, but none of those cited the ictericia. Among the academic students, 75.9% of nursing students had adequate knowledge of hepatitis, followed by pharmacy (51.3%), and biology students (18.2%). Nursing students had also higher scores of right answers regarding viral hepatitis and chronic disease. On contrary, biology and high school students had poor knowledge of that matter (37% and 44.5%, respectively). Less than 15% of nursing and pharmacy students did not know that viral hepatitis are sexually transmissible, whereas 78.6% of the 3rd year and 52.4% of the 4th year biology course ignored the sexual transmission of viral hepatitis. Still considering the same question, 54.5% of the high school students also ignored that viral hepatitis are sexually transmitted diseases. Important conclusions can be drawn from this study, since the higher hepatitis knowledge scores were found among nursing students, followed by pharmacy academics. However, biology students, which will serve as high school teachers, had poor and insufficient knowledge on hepatitis. This finding could explain the same poor disease knowledge among high school pupils.

Photoperiodic Diapause and the Establishment of Aedes albopictus (Diptera: Culicidae) in North America

PubMed Central

2016-01-01

The invasion and range expansion of Aedes albopictus (Skuse) in North America represents an outstanding opportunity to study processes of invasion, range expansion, and climatic adaptation. Furthermore, knowledge obtained from such research is relevant to developing novel strategies to control this important vector species. Substantial evidence indicates that the photoperiodic diapause response is an important adaptation to climatic variation across the range of Ae. albopictus in North America. Photoperiodic diapause is a key determinant of abundance in both space and time, and the timing of entry into and exit out of diapause strongly affects seasonal population dynamics and thus the potential for arbovirus transmission. Emerging genomic technologies are making it possible to develop high-resolution, genome-wide genetic markers that can be used for genetic mapping of traits relevant to disease transmission and phylogeographic studies to elucidate invasion history. Recent work using next-generation sequencing technologies (e.g., RNA-seq), combined with physiological experiments, has provided extensive insight into the transcriptional basis of the diapause response in Ae. albopictus. Applying this knowledge to identify novel targets for vector control represents an important future challenge. Finally, recent studies have begun to identify traits other than diapause that are affected by photoperiodism. Extending this work to identify additional traits influenced by photoperiod should produce important insights into the seasonal biology of Ae. albopictus. PMID:27354438

Pathogen bacteria adhesion to skin mucus of fishes.

PubMed

Benhamed, Said; Guardiola, Francisco A; Mars, Mohammed; Esteban, María Ángeles

2014-06-25

Fish are always in intimate contact with their environment; therefore they are permanently exposed to very vary external hazards (e.g. aerobic and anaerobic bacteria, viruses, parasites, pollutants). To fight off pathogenic microorganisms, the epidermis and its secretion, the mucus acts as a barrier between the fish and the environment. Fish are surrounded by a continuous layer of mucus which is the first physical, chemical and biological barrier from infection and the first site of interaction between fish's skin cells and pathogens. The mucus composition is very complex and includes numerous antibacterial factors secreted by fish's skin cells, such as immunoglobulins, agglutinins, lectins, lysins and lysozymes. These factors have a very important role to discriminate between pathogenic and commensal microorganisms and to protect fish from invading pathogens. Furthermore, the skin mucus represents an important portal of entry of pathogens since it induces the development of biofilms, and represents a favorable microenvironment for bacteria, the main disease agents for fish. The purpose of this review is to summarize the current knowledge of the interaction between bacteria and fish skin mucus, the adhesion mechanisms of pathogens and the major factors influencing pathogen adhesion to mucus. The better knowledge of the interaction between fish and their environment could inspire other new perspectives to study as well as to exploit the mucus properties for different purposes. Copyright © 2014 Elsevier B.V. All rights reserved.

The Representation of Object-Directed Action and Function Knowledge in the Human Brain

PubMed Central

Chen, Quanjing; Garcea, Frank E.; Mahon, Bradford Z.

2016-01-01

The appropriate use of everyday objects requires the integration of action and function knowledge. Previous research suggests that action knowledge is represented in frontoparietal areas while function knowledge is represented in temporal lobe regions. Here we used multivoxel pattern analysis to investigate the representation of object-directed action and function knowledge while participants executed pantomimes of familiar tool actions. A novel approach for decoding object knowledge was used in which classifiers were trained on one pair of objects and then tested on a distinct pair; this permitted a measurement of classification accuracy over and above object-specific information. Region of interest (ROI) analyses showed that object-directed actions could be decoded in tool-preferring regions of both parietal and temporal cortex, while no independently defined tool-preferring ROI showed successful decoding of object function. However, a whole-brain searchlight analysis revealed that while frontoparietal motor and peri-motor regions are engaged in the representation of object-directed actions, medial temporal lobe areas in the left hemisphere are involved in the representation of function knowledge. These results indicate that both action and function knowledge are represented in a topographically coherent manner that is amenable to study with multivariate approaches, and that the left medial temporal cortex represents knowledge of object function. PMID:25595179

Content-Related Knowledge of Biology Teachers from Secondary Schools: Structure and Learning Opportunities

ERIC Educational Resources Information Center

Großschedl, Jörg; Mahler, Daniela; Kleickmann, Thilo; Harms, Ute

2014-01-01

Teachers' content-related knowledge is a key factor influencing the learning progress of students. Different models of content-related knowledge have been proposed by educational researchers; most of them take into account three categories: content knowledge, pedagogical content knowledge, and curricular knowledge. As there is no consensus about…

Computational approaches to metabolic engineering utilizing systems biology and synthetic biology.

PubMed

Fong, Stephen S

2014-08-01

Metabolic engineering modifies cellular function to address various biochemical applications. Underlying metabolic engineering efforts are a host of tools and knowledge that are integrated to enable successful outcomes. Concurrent development of computational and experimental tools has enabled different approaches to metabolic engineering. One approach is to leverage knowledge and computational tools to prospectively predict designs to achieve the desired outcome. An alternative approach is to utilize combinatorial experimental tools to empirically explore the range of cellular function and to screen for desired traits. This mini-review focuses on computational systems biology and synthetic biology tools that can be used in combination for prospective in silico strain design.

Issues in Space Radiation Protection: Galactic Cosmic Rays

NASA Technical Reports Server (NTRS)

Wilson, J. W.; Kim, M.; Schimmerling, W.; Badavi, F. F.; Thibeault, S. A.; Cucinotta, F. A.; Shinn, J. L.; Kiefer, R.

1995-01-01

With shielding from cosmic heavy ions, one is faced with limited knowledge about the physical properties and biological responses of these radiations. Herein, the current status of space shielding technology and its impact on radiation health is discussed in terms of conventional protection practice and a test biological response model. The impact of biological response on optimum materials selection for cosmic ray shielding is presented in terms of the transmission characteristics of the shield material. Although liquid hydrogen gas is an optimum shield material, evaluation of the effectiveness of polymeric structural materials must await improvement in our knowledge of both the biological response and the nuclear processes.

Interactions among Children in Scholastic Contexts and Knowledge Acquisition in Biology

ERIC Educational Resources Information Center

Ponce, Corinne; Schneeberger, Patricia

2002-01-01

This article presents the first results of an investigation in a scholastic context aimed a determining the conditions that favour the acquisition of knowledge in biology within interactions in groups of 4 pupils. There were three work sessions in small groups, and some sessions in class groups. The pupils' conceptions were assessed at the…

The Interpretation of Cellular Transport Graphics by Students with Low and High Prior Knowledge

ERIC Educational Resources Information Center

Cook, Michelle; Carter, Glenda; Wiebe, Eric N.

2008-01-01

The purpose of this study was to examine how prior knowledge of cellular transport influenced how high school students in the USA viewed and interpreted graphic representations of this topic. The participants were Advanced Placement Biology students (n = 65); each participant had previously taken a biology course in high school. After assessing…

Confronting the Canon of Science: Gender and the Role of Informal Writing in Constructing Disciplinary Knowledge.

ERIC Educational Resources Information Center

Kalamaras, George

1993-01-01

Discusses the language practices of introductory biology courses, the means by which knowledge is constructed in such courses, and how it may exclude female students. Provides student responses to writing tasks in the biology class, and analyzes those responses. Shows how male and female students differ in their responses. (HB)

Physics of Non-Newtonian Fluids and Interdisciplinary Relations (Biology and Criminology)

ERIC Educational Resources Information Center

Holubova, R.

2018-01-01

The aim of the paper is the presentation of an interdisciplinary topic that allows applying content knowledge in physics, mathematics and biology in real life environment. Students use to play games and view crime scenes but in common they have little knowledge about the science used during crime scene investigation. In this paper the science…

Elaboration of Cognitive Knowledge of Biology from Childhood to Adulthood.

ERIC Educational Resources Information Center

Fisher, Kathleen M.

Word association techniques were used to examine the growth of biological knowledge over a period of years, from fourth-grade to college students. Results were analyzed by classifying stimulus-response word pairs according to the nature of the relationship between the words in each pair. Three hypotheses were tested: (1) the proportion of enactive…

EMICORON: A multi-targeting G4 ligand with a promising preclinical profile.

PubMed

Porru, Manuela; Zizza, Pasquale; Franceschin, Marco; Leonetti, Carlo; Biroccio, Annamaria

2017-05-01

During the last decade, guanine G-rich sequences folding into G-quadruplex (G4) structures have received a lot of attention and their biological role is now a matter of large debate. Rising amounts of experimental evidence have validated several G-rich motifs as molecular targets in cancer treatment. Despite that an increasing number of small molecules has been reported to possess excellent G4 stabilizing properties, none of them has progressed through the drug-development pipeline due to their poor drug-like properties. In this context, the identification of G4 ligands with more favorable pharmacological properties and with a well-defined target activity could be fruitful for anticancer therapy application. This manuscript outlines the current state of knowledge regarding EMICORON, a G4-interactive molecule structurally and biologically similar, on the one side, to coronene and, on the other side, to a bay-monosubstituted perylene. Overall this work evidences that EMICORON, a new promising G4 ligand, possesses a marked antitumoral activity both standing alone and in combination with chemotherapeutics. Moreover, EMICORON represents a good example of multimodal class of antitumoral drug, able to simultaneously affect multiple targets participating in several distinct signaling pathways, thus simplifying the treatment modalities and improving the selectivity against cancer cells. Due to the importance of G4 forming sequences in crucial biological processes participating in tumor progression, their successful targeting with small molecules could represent a very important innovation in the development of effective therapeutic strategies against cancer. This article is part of a Special Issue entitled "G-quadruplex" Guest Editor: Dr. Concetta Giancola and Dr. Daniela Montesarchio. Copyright © 2016 Elsevier B.V. All rights reserved.

Development of the Biology Card Sorting Task to Measure Conceptual Expertise in Biology

PubMed Central

Smith, Julia I.; Combs, Elijah D.; Nagami, Paul H.; Alto, Valerie M.; Goh, Henry G.; Gourdet, Muryam A. A.; Hough, Christina M.; Nickell, Ashley E.; Peer, Adrian G.; Coley, John D.; Tanner, Kimberly D.

2013-01-01

There are widespread aspirations to focus undergraduate biology education on teaching students to think conceptually like biologists; however, there is a dearth of assessment tools designed to measure progress from novice to expert biological conceptual thinking. We present the development of a novel assessment tool, the Biology Card Sorting Task, designed to probe how individuals organize their conceptual knowledge of biology. While modeled on tasks from cognitive psychology, this task is unique in its design to test two hypothesized conceptual frameworks for the organization of biological knowledge: 1) a surface feature organization focused on organism type and 2) a deep feature organization focused on fundamental biological concepts. In this initial investigation of the Biology Card Sorting Task, each of six analytical measures showed statistically significant differences when used to compare the card sorting results of putative biological experts (biology faculty) and novices (non–biology major undergraduates). Consistently, biology faculty appeared to sort based on hypothesized deep features, while non–biology majors appeared to sort based on either surface features or nonhypothesized organizational frameworks. Results suggest that this novel task is robust in distinguishing populations of biology experts and biology novices and may be an adaptable tool for tracking emerging biology conceptual expertise. PMID:24297290

Nursing and the new biology: towards a realist, anti-reductionist approach to nursing knowledge.

PubMed

Nairn, Stuart

2014-10-01

As a system of knowledge, nursing has utilized a range of subjects and reconstituted them to reflect the thinking and practice of health care. Often drawn to a holistic model, nursing finds it difficult to resist the reductionist tendencies in biological and medical thinking. In this paper I will propose a relational approach to knowledge that is able to address this issue. The paper argues that biology is not characterized by one stable theory but is often a contentious topic and employs philosophically diverse models in its scientific research. Biology need not be seen as a reductionist science, but reductionism is nonetheless an important current within biological thinking. These reductionist currents can undermine nursing knowledge in four main ways. Firstly, that the conclusions drawn from reductionism go far beyond their data based on an approach that prioritizes biological explanations and eliminates others. Secondly, that the methods employed by biologists are sometimes weak, and the limitations are insufficiently acknowledged. Thirdly, that the assumptions that drive the research agenda are problematic, and finally that uncritical application of these ideas can be potentially disastrous for nursing practice. These issues are explored through an examination of the problems reductionism poses for the issue of gender, mental health, and altruism. I then propose an approach based on critical realism that adopts an anti-reductionist philosophy that utilizes the conceptual tools of emergence and a relational ontology. © 2014 John Wiley & Sons Ltd.

Identification of Boolean Network Models From Time Series Data Incorporating Prior Knowledge.

PubMed

Leifeld, Thomas; Zhang, Zhihua; Zhang, Ping

2018-01-01

Motivation: Mathematical models take an important place in science and engineering. A model can help scientists to explain dynamic behavior of a system and to understand the functionality of system components. Since length of a time series and number of replicates is limited by the cost of experiments, Boolean networks as a structurally simple and parameter-free logical model for gene regulatory networks have attracted interests of many scientists. In order to fit into the biological contexts and to lower the data requirements, biological prior knowledge is taken into consideration during the inference procedure. In the literature, the existing identification approaches can only deal with a subset of possible types of prior knowledge. Results: We propose a new approach to identify Boolean networks from time series data incorporating prior knowledge, such as partial network structure, canalizing property, positive and negative unateness. Using vector form of Boolean variables and applying a generalized matrix multiplication called the semi-tensor product (STP), each Boolean function can be equivalently converted into a matrix expression. Based on this, the identification problem is reformulated as an integer linear programming problem to reveal the system matrix of Boolean model in a computationally efficient way, whose dynamics are consistent with the important dynamics captured in the data. By using prior knowledge the number of candidate functions can be reduced during the inference. Hence, identification incorporating prior knowledge is especially suitable for the case of small size time series data and data without sufficient stimuli. The proposed approach is illustrated with the help of a biological model of the network of oxidative stress response. Conclusions: The combination of efficient reformulation of the identification problem with the possibility to incorporate various types of prior knowledge enables the application of computational model inference to systems with limited amount of time series data. The general applicability of this methodological approach makes it suitable for a variety of biological systems and of general interest for biological and medical research.

MetNetAPI: A flexible method to access and manipulate biological network data from MetNet

PubMed Central

2010-01-01

Background Convenient programmatic access to different biological databases allows automated integration of scientific knowledge. Many databases support a function to download files or data snapshots, or a webservice that offers "live" data. However, the functionality that a database offers cannot be represented in a static data download file, and webservices may consume considerable computational resources from the host server. Results MetNetAPI is a versatile Application Programming Interface (API) to the MetNetDB database. It abstracts, captures and retains operations away from a biological network repository and website. A range of database functions, previously only available online, can be immediately (and independently from the website) applied to a dataset of interest. Data is available in four layers: molecular entities, localized entities (linked to a specific organelle), interactions, and pathways. Navigation between these layers is intuitive (e.g. one can request the molecular entities in a pathway, as well as request in what pathways a specific entity participates). Data retrieval can be customized: Network objects allow the construction of new and integration of existing pathways and interactions, which can be uploaded back to our server. In contrast to webservices, the computational demand on the host server is limited to processing data-related queries only. Conclusions An API provides several advantages to a systems biology software platform. MetNetAPI illustrates an interface with a central repository of data that represents the complex interrelationships of a metabolic and regulatory network. As an alternative to data-dumps and webservices, it allows access to a current and "live" database and exposes analytical functions to application developers. Yet it only requires limited resources on the server-side (thin server/fat client setup). The API is available for Java, Microsoft.NET and R programming environments and offers flexible query and broad data- retrieval methods. Data retrieval can be customized to client needs and the API offers a framework to construct and manipulate user-defined networks. The design principles can be used as a template to build programmable interfaces for other biological databases. The API software and tutorials are available at http://www.metnetonline.org/api. PMID:21083943

Biological variation in a large sample of mouse lemurs from Amboasary, Madagascar: implications for interpreting variation in primate biology and paleobiology.

PubMed

Cuozzo, Frank P; Rasoazanabary, Emilienne; Godfrey, Laurie R; Sauther, Michelle L; Youssouf, Ibrahim Antho; LaFleur, Marni M

2013-01-01

A thorough knowledge of biological variation in extant primates is imperative for interpreting variation, and for delineating species in primate biology and paleobiology. This is especially the case given the recent, rapid taxonomic expansion in many primate groups, notably among small-bodied nocturnal forms. Here we present data on dental, cranial, and pelage variation in a single-locality museum sample of mouse lemurs from Amboasary, Madagascar. To interpret these data, we include comparative information from other museum samples, and from a newly collected mouse lemur skeletal sample from the Beza Mahafaly Special Reserve (BMSR), Madagascar. We scored forty dental traits (n = 126) and three pelage variants (n = 19), and collected 21 cranial/dental measures. Most dental traits exhibit variable frequencies, with some only rarely present. Individual dental variants include misshapen and supernumerary teeth. All Amboasary pelage specimens display a "reversed V" on the cap, and a distinct dorsal median stripe on the back. All but two displayed the dominant gray-brown pelage coloration typical of Microcebus griseorufus. Cranial and dental metric variability are each quite low, and craniometric variation does not illustrate heteroscedasticity. To assess whether this sample represents a single species, we compared dental and pelage variation to a documented, single-species M. griseorufus sample from BMSR. As at Amboasary, BMSR mouse lemurs display limited odontometric variation and wide variation in non-metric dental traits. In contrast, BMSR mouse lemurs display diverse pelage, despite reported genetic homogeneity. Ranges of dental and pelage variation at BMSR and Amboasary overlap. Thus, we conclude that the Amboasary mouse lemurs represent a single species - most likely (in the absence of genetic data to the contrary) M. griseorufus, and we reject their previous allocation to Microcebus murinus. Patterns of variation in the Amboasary sample provide a comparative template for recognizing the degree of variation manifested in a single primate population, and by implication, they provide minimum values for this species' intraspecific variation. Finally, discordance between different biological systems in our mouse lemur samples illustrates the need to examine multiple systems when conducting taxonomic analyses among living or fossil primates. Copyright © 2012 Elsevier Ltd. All rights reserved.

Translational systems biology using an agent-based approach for dynamic knowledge representation: An evolutionary paradigm for biomedical research.

PubMed

An, Gary C

2010-01-01

The greatest challenge facing the biomedical research community is the effective translation of basic mechanistic knowledge into clinically effective therapeutics. This challenge is most evident in attempts to understand and modulate "systems" processes/disorders, such as sepsis, cancer, and wound healing. Formulating an investigatory strategy for these issues requires the recognition that these are dynamic processes. Representation of the dynamic behavior of biological systems can aid in the investigation of complex pathophysiological processes by augmenting existing discovery procedures by integrating disparate information sources and knowledge. This approach is termed Translational Systems Biology. Focusing on the development of computational models capturing the behavior of mechanistic hypotheses provides a tool that bridges gaps in the understanding of a disease process by visualizing "thought experiments" to fill those gaps. Agent-based modeling is a computational method particularly well suited to the translation of mechanistic knowledge into a computational framework. Utilizing agent-based models as a means of dynamic hypothesis representation will be a vital means of describing, communicating, and integrating community-wide knowledge. The transparent representation of hypotheses in this dynamic fashion can form the basis of "knowledge ecologies," where selection between competing hypotheses will apply an evolutionary paradigm to the development of community knowledge.

Causality, randomness, intelligibility, and the epistemology of the cell.

PubMed

Dougherty, Edward R; Bittner, Michael L

2010-06-01

Because the basic unit of biology is the cell, biological knowledge is rooted in the epistemology of the cell, and because life is the salient characteristic of the cell, its epistemology must be centered on its livingness, not its constituent components. The organization and regulation of these components in the pursuit of life constitute the fundamental nature of the cell. Thus, regulation sits at the heart of biological knowledge of the cell and the extraordinary complexity of this regulation conditions the kind of knowledge that can be obtained, in particular, the representation and intelligibility of that knowledge. This paper is essentially split into two parts. The first part discusses the inadequacy of everyday intelligibility and intuition in science and the consequent need for scientific theories to be expressed mathematically without appeal to commonsense categories of understanding, such as causality. Having set the backdrop, the second part addresses biological knowledge. It briefly reviews modern scientific epistemology from a general perspective and then turns to the epistemology of the cell. In analogy with a multi-faceted factory, the cell utilizes a highly parallel distributed control system to maintain its organization and regulate its dynamical operation in the face of both internal and external changes. Hence, scientific knowledge is constituted by the mathematics of stochastic dynamical systems, which model the overall relational structure of the cell and how these structures evolve over time, stochasticity being a consequence of the need to ignore a large number of factors while modeling relatively few in an extremely complex environment.

Features of Knowledge Building in Biology: Understanding Undergraduate Students’ Ideas about Molecular Mechanisms

PubMed Central

Southard, Katelyn; Wince, Tyler; Meddleton, Shanice; Bolger, Molly S.

2016-01-01

Research has suggested that teaching and learning in molecular and cellular biology (MCB) is difficult. We used a new lens to understand undergraduate reasoning about molecular mechanisms: the knowledge-integration approach to conceptual change. Knowledge integration is the dynamic process by which learners acquire new ideas, develop connections between ideas, and reorganize and restructure prior knowledge. Semistructured, clinical think-aloud interviews were conducted with introductory and upper-division MCB students. Interviews included a written conceptual assessment, a concept-mapping activity, and an opportunity to explain the biomechanisms of DNA replication, transcription, and translation. Student reasoning patterns were explored through mixed-method analyses. Results suggested that students must sort mechanistic entities into appropriate mental categories that reflect the nature of MCB mechanisms and that conflation between these categories is common. We also showed how connections between molecular mechanisms and their biological roles are part of building an integrated knowledge network as students develop expertise. We observed differences in the nature of connections between ideas related to different forms of reasoning. Finally, we provide a tentative model for MCB knowledge integration and suggest its implications for undergraduate learning. PMID:26931398

WikiPathways: a multifaceted pathway database bridging metabolomics to other omics research.

PubMed

Slenter, Denise N; Kutmon, Martina; Hanspers, Kristina; Riutta, Anders; Windsor, Jacob; Nunes, Nuno; Mélius, Jonathan; Cirillo, Elisa; Coort, Susan L; Digles, Daniela; Ehrhart, Friederike; Giesbertz, Pieter; Kalafati, Marianthi; Martens, Marvin; Miller, Ryan; Nishida, Kozo; Rieswijk, Linda; Waagmeester, Andra; Eijssen, Lars M T; Evelo, Chris T; Pico, Alexander R; Willighagen, Egon L

2018-01-04

WikiPathways (wikipathways.org) captures the collective knowledge represented in biological pathways. By providing a database in a curated, machine readable way, omics data analysis and visualization is enabled. WikiPathways and other pathway databases are used to analyze experimental data by research groups in many fields. Due to the open and collaborative nature of the WikiPathways platform, our content keeps growing and is getting more accurate, making WikiPathways a reliable and rich pathway database. Previously, however, the focus was primarily on genes and proteins, leaving many metabolites with only limited annotation. Recent curation efforts focused on improving the annotation of metabolism and metabolic pathways by associating unmapped metabolites with database identifiers and providing more detailed interaction knowledge. Here, we report the outcomes of the continued growth and curation efforts, such as a doubling of the number of annotated metabolite nodes in WikiPathways. Furthermore, we introduce an OpenAPI documentation of our web services and the FAIR (Findable, Accessible, Interoperable and Reusable) annotation of resources to increase the interoperability of the knowledge encoded in these pathways and experimental omics data. New search options, monthly downloads, more links to metabolite databases, and new portals make pathway knowledge more effortlessly accessible to individual researchers and research communities. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Perceptions, opinions and knowledge of pharmacists towards the use of complementary medicines by people living with cancer.

PubMed

Harnett, Joanna; Le, Trong Quy; Smith, Lorraine; Krass, Ines

2018-05-09

Background Biologically-based complementary medicine (BB-CM) use is prevalent amongst people living with cancer. Pharmacists play an important role in the provision of standard treatments for cancer. Less is known about pharmacist's provision of BB-CM information. Objective This study investigated the opinions, perceptions and knowledge of pharmacists regarding the use of BB-CMs by people living with cancer and the facilitators and barriers to providing information and advice. Setting Australia. Method A cross-sectional 53-item survey was developed and the survey link distributed in two professional associations newsletters. The associations represent ~29,000 pharmacists. Questions were categories into pharmacist's perceptions, opinions, and knowledge towards the use of BB-CM in cancer. Main Outcome Measure Scores obtained from responses to perception, opinion and knowledge statements and responses to demographic questions Results Respondents (n=70) were predominantly female (73%), Caucasian (66%) and under 40 years of age (78%). Respondents estimated that 19% of daily inquiries related to BB-CMs. Seventy-two per cent of respondents believed they had a responsibility to advise about the concomitant use of BB-CM with standard cancer treatments despite 60% reporting a lack of confidence in their knowledge. There was a moderate positive association (Spearman's rho 0.41 p= 0.001) between a pharmacists confidence in their level of knowledge and their total knowledge scores. The main barriers to providing information about BB-CMs reported were inadequate training in BB-CMs (94%) and reservations about the evidence base for efficacy and safety (50%). Conclusion Pharmacists have a role to play in counselling people living with cancer about their use of BB-CMs and this role could be maximized with further training and education in this area.

Teaching About “Brain and Learning” in High School Biology Classes: Effects on Teachers' Knowledge and Students' Theory of Intelligence

PubMed Central

Dekker, Sanne; Jolles, Jelle

2015-01-01

This study evaluated a new teaching module about “Brain and Learning” using a controlled design. The module was implemented in high school biology classes and comprised three lessons: (1) brain processes underlying learning; (2) neuropsychological development during adolescence; and (3) lifestyle factors that influence learning performance. Participants were 32 biology teachers who were interested in “Brain and Learning” and 1241 students in grades 8–9. Teachers' knowledge and students' beliefs about learning potential were examined using online questionnaires. Results indicated that before intervention, biology teachers were significantly less familiar with how the brain functions and develops than with its structure and with basic neuroscientific concepts (46 vs. 75% correct answers). After intervention, teachers' knowledge of “Brain and Learning” had significantly increased (64%), and more students believed that intelligence is malleable (incremental theory). This emphasizes the potential value of a short teaching module, both for improving biology teachers' insights into “Brain and Learning,” and for changing students' beliefs about intelligence. PMID:26648900

A framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps

NASA Astrophysics Data System (ADS)

Xu, Jin; Li, Zheng; Li, Shuliang; Zhang, Yanyan

2015-07-01

There is still a lack of effective paradigms and tools for analysing and discovering the contents and relationships of project knowledge contexts in the field of project management. In this paper, a new framework for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps under big data environments is proposed and developed. The conceptual paradigm, theoretical underpinning, extended topic model, and illustration examples of the ontology model for project knowledge maps are presented, with further research work envisaged.

The Effectiveness of an Online Curriculum on High School Students' Understanding of Biological Evolution

ERIC Educational Resources Information Center

Marsteller, Robert B.; Bodzin, Alec M.

2015-01-01

An online curriculum about biological evolution was designed to promote increased student content knowledge and evidentiary reasoning. A feasibility study was conducted with 77 rural high school biology students who learned with the online biological evolution unit. Data sources included the Biological Evolution Assessment Measure (BEAM), an…

Targeted Therapy Database (TTD): A Model to Match Patient's Molecular Profile with Current Knowledge on Cancer Biology

PubMed Central

Mocellin, Simone; Shrager, Jeff; Scolyer, Richard; Pasquali, Sandro; Verdi, Daunia; Marincola, Francesco M.; Briarava, Marta; Gobbel, Randy; Rossi, Carlo; Nitti, Donato

2010-01-01

Background The efficacy of current anticancer treatments is far from satisfactory and many patients still die of their disease. A general agreement exists on the urgency of developing molecularly targeted therapies, although their implementation in the clinical setting is in its infancy. In fact, despite the wealth of preclinical studies addressing these issues, the difficulty of testing each targeted therapy hypothesis in the clinical arena represents an intrinsic obstacle. As a consequence, we are witnessing a paradoxical situation where most hypotheses about the molecular and cellular biology of cancer remain clinically untested and therefore do not translate into a therapeutic benefit for patients. Objective To present a computational method aimed to comprehensively exploit the scientific knowledge in order to foster the development of personalized cancer treatment by matching the patient's molecular profile with the available evidence on targeted therapy. Methods To this aim we focused on melanoma, an increasingly diagnosed malignancy for which the need for novel therapeutic approaches is paradigmatic since no effective treatment is available in the advanced setting. Relevant data were manually extracted from peer-reviewed full-text original articles describing any type of anti-melanoma targeted therapy tested in any type of experimental or clinical model. To this purpose, Medline, Embase, Cancerlit and the Cochrane databases were searched. Results and Conclusions We created a manually annotated database (Targeted Therapy Database, TTD) where the relevant data are gathered in a formal representation that can be computationally analyzed. Dedicated algorithms were set up for the identification of the prevalent therapeutic hypotheses based on the available evidence and for ranking treatments based on the molecular profile of individual patients. In this essay we describe the principles and computational algorithms of an original method developed to fully exploit the available knowledge on cancer biology with the ultimate goal of fruitfully driving both preclinical and clinical research on anticancer targeted therapy. In the light of its theoretical nature, the prediction performance of this model must be validated before it can be implemented in the clinical setting. PMID:20706624

Targeted Therapy Database (TTD): a model to match patient's molecular profile with current knowledge on cancer biology.

PubMed

Mocellin, Simone; Shrager, Jeff; Scolyer, Richard; Pasquali, Sandro; Verdi, Daunia; Marincola, Francesco M; Briarava, Marta; Gobbel, Randy; Rossi, Carlo; Nitti, Donato

2010-08-10

The efficacy of current anticancer treatments is far from satisfactory and many patients still die of their disease. A general agreement exists on the urgency of developing molecularly targeted therapies, although their implementation in the clinical setting is in its infancy. In fact, despite the wealth of preclinical studies addressing these issues, the difficulty of testing each targeted therapy hypothesis in the clinical arena represents an intrinsic obstacle. As a consequence, we are witnessing a paradoxical situation where most hypotheses about the molecular and cellular biology of cancer remain clinically untested and therefore do not translate into a therapeutic benefit for patients. To present a computational method aimed to comprehensively exploit the scientific knowledge in order to foster the development of personalized cancer treatment by matching the patient's molecular profile with the available evidence on targeted therapy. To this aim we focused on melanoma, an increasingly diagnosed malignancy for which the need for novel therapeutic approaches is paradigmatic since no effective treatment is available in the advanced setting. Relevant data were manually extracted from peer-reviewed full-text original articles describing any type of anti-melanoma targeted therapy tested in any type of experimental or clinical model. To this purpose, Medline, Embase, Cancerlit and the Cochrane databases were searched. We created a manually annotated database (Targeted Therapy Database, TTD) where the relevant data are gathered in a formal representation that can be computationally analyzed. Dedicated algorithms were set up for the identification of the prevalent therapeutic hypotheses based on the available evidence and for ranking treatments based on the molecular profile of individual patients. In this essay we describe the principles and computational algorithms of an original method developed to fully exploit the available knowledge on cancer biology with the ultimate goal of fruitfully driving both preclinical and clinical research on anticancer targeted therapy. In the light of its theoretical nature, the prediction performance of this model must be validated before it can be implemented in the clinical setting.

Moving beyond a descriptive aquatic toxicology: the value of biological process and trait information.

PubMed

Segner, Helmut

2011-10-01

In order to improve the ability to link chemical exposure to toxicological and ecological effects, aquatic toxicology will have to move from observing what chemical concentrations induce adverse effects to more explanatory approaches, that are concepts which build on knowledge of biological processes and pathways leading from exposure to adverse effects, as well as on knowledge on stressor vulnerability as given by the genetic, physiological and ecological (e.g., life history) traits of biota. Developing aquatic toxicology in this direction faces a number of challenges, including (i) taking into account species differences in toxicant responses on the basis of the evolutionarily developed diversity of phenotypic vulnerability to environmental stressors, (ii) utilizing diversified biological response profiles to serve as biological read across for prioritizing chemicals, categorizing them according to modes of action, and for guiding targeted toxicity evaluation; (iii) prediction of ecological consequences of toxic exposure from knowledge of how biological processes and phenotypic traits lead to effect propagation across the levels of biological hierarchy; and (iv) the search for concepts to assess the cumulative impact of multiple stressors. An underlying theme in these challenges is that, in addition to the question of what the chemical does to the biological receptor, we should give increasing emphasis to the question how the biological receptor handles the chemicals, i.e., through which pathways the initial chemical-biological interaction extends to the adverse effects, how this extension is modulated by adaptive or compensatory processes as well as by phenotypic traits of the biological receptor. 2011 Elsevier B.V. All rights reserved.

KaBOB: ontology-based semantic integration of biomedical databases.

PubMed

Livingston, Kevin M; Bada, Michael; Baumgartner, William A; Hunter, Lawrence E

2015-04-23

The ability to query many independent biological databases using a common ontology-based semantic model would facilitate deeper integration and more effective utilization of these diverse and rapidly growing resources. Despite ongoing work moving toward shared data formats and linked identifiers, significant problems persist in semantic data integration in order to establish shared identity and shared meaning across heterogeneous biomedical data sources. We present five processes for semantic data integration that, when applied collectively, solve seven key problems. These processes include making explicit the differences between biomedical concepts and database records, aggregating sets of identifiers denoting the same biomedical concepts across data sources, and using declaratively represented forward-chaining rules to take information that is variably represented in source databases and integrating it into a consistent biomedical representation. We demonstrate these processes and solutions by presenting KaBOB (the Knowledge Base Of Biomedicine), a knowledge base of semantically integrated data from 18 prominent biomedical databases using common representations grounded in Open Biomedical Ontologies. An instance of KaBOB with data about humans and seven major model organisms can be built using on the order of 500 million RDF triples. All source code for building KaBOB is available under an open-source license. KaBOB is an integrated knowledge base of biomedical data representationally based in prominent, actively maintained Open Biomedical Ontologies, thus enabling queries of the underlying data in terms of biomedical concepts (e.g., genes and gene products, interactions and processes) rather than features of source-specific data schemas or file formats. KaBOB resolves many of the issues that routinely plague biomedical researchers intending to work with data from multiple data sources and provides a platform for ongoing data integration and development and for formal reasoning over a wealth of integrated biomedical data.

Mapping out the Integration of the Components of Pedagogical Content Knowledge (PCK): Examples from High School Biology Classrooms

ERIC Educational Resources Information Center

Park, Soonhye; Chen, Ying-Chih

2012-01-01

This study explored the nature of the integration of the five components of pedagogical content knowledge (PCK): (a) Orientations toward Teaching Science, (b) Knowledge of Student Understanding, (c) Knowledge of Instructional Strategies and Representations, (d) Knowledge of Science Curriculum, and (e) Knowledge of Assessment of Science Learning.…

[Evolutionary medicine: A new look on health and disease].

PubMed

Bauduer, F

2017-03-01

Evolutionary medicine represents an innovative approach deriving from evolutionary biology. It includes the initial Darwin's view, its actualization in the light of progresses in genetics and also dissident theories (i.e. non gene-based) particularly epigenetics. This approach enables us to reconsider the pathophysiology of numerous diseases, as for instance, infection, and our so-called diseases of civilization especially obesity, type 2 diabetes, allergy or cancer. Evolutionary medicine may also improve our knowledge regarding inter-individual variation in susceptibility to disease or drugs. Furthermore, it points out the impact of our behaviors and environment on the genesis of a series of diseases. Copyright © 2016 Société Nationale Française de Médecine Interne (SNFMI). Published by Elsevier SAS. All rights reserved.

Colloidal stability of superparamagnetic iron oxide nanoparticles in the central nervous system: a review.

PubMed

Champagne, Pierre-Olivier; Westwick, Harrison; Bouthillier, Alain; Sawan, Mohamad

2018-06-01

Superparamagnetic iron oxide nanoparticles (SPIONs) consist of nanosized metallic-based particles with unique magnetic properties. Their potential in both diagnostic and therapeutic applications in the CNS is at the source of an expanding body of the literature in recent years. Colloidal stability of nanoparticles represents their ability to resist aggregation and is a central aspect for the use of SPION in biological environment such as the CNS. This review gives a comprehensive update of the recent developments and knowledge on the determinants of colloidal stability of SPIONs in the CNS. Factors leading to aggregate formation and the repercussions of colloidal instability of SPION are reviewed in detail pertaining to their use in the CNS.

Occurrence and Biosynthesis of Alkyl Hydroxycinnamates in Plant Lipid Barriers

PubMed Central

Domergue, Frédéric; Kosma, Dylan K.

2017-01-01

The plant lipid barriers cuticle and suberin represent one of the largest biological interfaces on the planet. They are comprised of an insoluble polymeric domain with associated organic solvent-soluble waxes. Suberin-associated and plant cuticular waxes contain mixtures of aliphatic components that may include alkyl hydroxycinnamates (AHCs). The canonical alkyl hydroxycinnamates are comprised of phenylpropanoids, typically coumaric, ferulic, or caffeic acids, esterified with long chain to very long chain fatty alcohols. However, many related structures are also present in the plant kingdom. Although their functions remain elusive, much progress has been made on understanding the distribution, biosynthesis, and deposition of AHCs. Herein a summary of the current state of knowledge on plant AHCs is provided. PMID:28665304

Nematode taxonomy: from morphology to metabarcoding

NASA Astrophysics Data System (ADS)

Ahmed, M.; Sapp, M.; Prior, T.; Karssen, G.; Back, M.

2015-11-01

Nematodes represent a species rich and morphologically diverse group of metazoans inhabiting both aquatic and terrestrial environments. Their role as biological indicators and as key players in nutrient cycling has been well documented. Some groups of nematodes are also known to cause significant losses to crop production. In spite of this, knowledge of their diversity is still limited due to the difficulty in achieving species identification using morphological characters. Molecular methodology has provided very useful means of circumventing the numerous limitations associated with classical morphology based identification. We discuss herein the history and the progress made within the field of nematode systematics, the limitations of classical taxonomy and how the advent of high throughput sequencing is facilitating advanced ecological and molecular studies.

The future of neuropathology in childhood.

PubMed

Rorke, L B

2000-11-01

The current state of knowledge of pediatric neuropathology is based upon a rich historical heritage dating back many centuries and representing the genius of many people, although, relatively speaking, little specific attention was paid to the unique issues relating to infants and children. Aside from descriptions of morphological features of disease (including tumors), advances in understanding basic pathogenetic mechanisms have flowered only in the recent past. Most exciting has been the progress in molecular biology and genetics, which has yielded a phenomenal bank of information in a short time, uncovering details of genes involved in development of the nervous system and specifically associated with various types of tumors. The future of pediatric neuropathology requires partnership with molecular geneticists whose studies hold promise of defining morphology.

Considerations of multicultural science and curriculum reform: A content analysis of state-adopted biology textbooks in Florida

NASA Astrophysics Data System (ADS)

Delgato, Margaret H.

The purpose of this investigation was to determine the extent to which multicultural science education, including indigenous knowledge representations, had been infused within the content of high school biology textbooks. The study evaluated the textbook as an instructional tool and framework for multicultural science education instruction by comparing the mainstream content to indigenous knowledge perspectives portrayed in the student and teacher editions of 34 textbooks adopted in Florida within the last four adoption cycles occurring from 1990 to 2006. The investigation involved a content analysis framed from a mixed methods approach. Emphasis was placed, in consideration of the research questions and practicality of interpreting text with the potential for multiple meanings, within qualitative methods. The investigation incorporated five strategies to assess the extent of multicultural content: (1) calculation of frequency of indigenous representations through the use of a tally; (2) assessment of content in the teacher editions by coding the degree of incorporation of multicultural content; (3) development of an archaeology of statements to determine the ways in which indigenous representations were incorporated into the content; (4) use of the Evaluation Coefficient Analysis (ECO) to determine extent of multicultural terminologies within content; and (5) analysis of visuals and illustrations to gauge percentages of depictions of minority groups. Results indicated no solid trend in an increase of inclusion of multicultural content over the last four adoption cycles. Efforts at most reduced the inclusion of indigenous representations and other multicultural content to the level of the teacher edition distributed among the teacher-interleafed pages or as annotations in the margins. Degree of support of multicultural content to the specific goals and objectives remained limited across all four of the adoption cycles represented in the study. Emphasis on standardized testing appeared in the six textbooks representing the most recent adoption cycle. Recommendations included increased efforts to identify quality of content by including input from scholars in the field of multicultural education as well as indigenous peoples in the creation of textbook content. Recommendations also included further clarification of the definition of science within multicultural science education frameworks, indigenous knowledge as compared to Western science and pseudoscienc e, and scientific literacy as a central focus to a multicultural science education meant to address the needs of an increasingly diverse student population and prime-age workforce.

Tell Me a Story: How Children's Developing Domain Knowledge Affects Their Story Construction

ERIC Educational Resources Information Center

Sobel, David M.; Weisberg, Deena Skolnick

2014-01-01

Young children distinguish between the physical and biological domains of knowledge. The current study examines how this distinction is expressed in a story construction task. Three- and 4-year-olds were shown pairs of pictures, one that depicted a normal event and one that depicted an event that violated either physical or biological causal…

"You Can Exercise Your Way out of HIV" and Other Stories: The Role of Biological Knowledge in Adolescents' Evaluation of Myths

ERIC Educational Resources Information Center

Keselman, Alla; Kaufman, David R.; Patel, Vimla L.

2004-01-01

A primary objective for science education is to impart robust knowledge that has applicability to real-world problems. This article presents research investigating the relationship between adolescents' conceptual understanding of the biological basis of HIV and critical reasoning. Middle and high school students were interviewed about their…

Using Multiple Lenses to Examine the Development of Beginning Biology Teachers' Pedagogical Content Knowledge for Teaching Natural Selection Simulations

ERIC Educational Resources Information Center

Sickel, Aaron J.; Friedrichsen, Patricia

2018-01-01

Pedagogical content knowledge (PCK) has become a useful construct to examine science teacher learning. Yet, researchers conceptualize PCK development in different ways. The purpose of this longitudinal study was to use three analytic lenses to understand the development of three beginning biology teachers' PCK for teaching natural selection…

A Diagrammatic Language for Biochemical Networks

NASA Astrophysics Data System (ADS)

Maimon, Ron

2002-03-01

I present a diagrammatic language for representing the structure of biochemical networks. The language is designed to represent modular structure in a computational fasion, with composition of reactions replacing functional composition. This notation is used to represent arbitrarily large networks efficiently. The notation finds its most natural use in representing biological interaction networks, but it is a general computing language appropriate to any naturally occuring computation. Unlike lambda-calculus, or text-derived languages, it does not impose a tree-structure on the diagrams, and so is more effective at representing biological fucntion than competing notations.

Directed evolution and synthetic biology applications to microbial systems.

PubMed

Bassalo, Marcelo C; Liu, Rongming; Gill, Ryan T

2016-06-01

Biotechnology applications require engineering complex multi-genic traits. The lack of knowledge on the genetic basis of complex phenotypes restricts our ability to rationally engineer them. However, complex phenotypes can be engineered at the systems level, utilizing directed evolution strategies that drive whole biological systems toward desired phenotypes without requiring prior knowledge of the genetic basis of the targeted trait. Recent developments in the synthetic biology field accelerates the directed evolution cycle, facilitating engineering of increasingly complex traits in biological systems. In this review, we summarize some of the most recent advances in directed evolution and synthetic biology that allows engineering of complex traits in microbial systems. Then, we discuss applications that can be achieved through engineering at the systems level. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Representation of Object-Directed Action and Function Knowledge in the Human Brain.

PubMed

Chen, Quanjing; Garcea, Frank E; Mahon, Bradford Z

2016-04-01

The appropriate use of everyday objects requires the integration of action and function knowledge. Previous research suggests that action knowledge is represented in frontoparietal areas while function knowledge is represented in temporal lobe regions. Here we used multivoxel pattern analysis to investigate the representation of object-directed action and function knowledge while participants executed pantomimes of familiar tool actions. A novel approach for decoding object knowledge was used in which classifiers were trained on one pair of objects and then tested on a distinct pair; this permitted a measurement of classification accuracy over and above object-specific information. Region of interest (ROI) analyses showed that object-directed actions could be decoded in tool-preferring regions of both parietal and temporal cortex, while no independently defined tool-preferring ROI showed successful decoding of object function. However, a whole-brain searchlight analysis revealed that while frontoparietal motor and peri-motor regions are engaged in the representation of object-directed actions, medial temporal lobe areas in the left hemisphere are involved in the representation of function knowledge. These results indicate that both action and function knowledge are represented in a topographically coherent manner that is amenable to study with multivariate approaches, and that the left medial temporal cortex represents knowledge of object function. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The impact of ecolabel knowledge to purchase decision of green producton biology students

NASA Astrophysics Data System (ADS)

Sigit, Diana Vivanti; Fauziah, Rizky; Heryanti, Erna

2017-08-01

The world needs real solutions to reduce the impact of environmental damages. Students as agents of changes have a role to overcome these problems. One of the important solution is to be a critical consumer who has purchase decisions in a green product. To show the quality of an environmental friendly product, it is then required an ecolabel on the green product which indicates that the product has been through the production processed and come from environmental friendly substances. The research aimed at finding out whether there was an impact of ecolabel knowledge with purchase decision of green product on biology students. This research was conducted in Biology Department. This research used a survey descriptive method. The population used was biology students of Universitas Negeri Jakarta while the sampling technique was done through simple random sampling technique with 147 respondents. Instrument used were ecolabel knowledge test and a questionnaire of green product purchase decision. The result of prerequisite test showed that the data was normally distributed and homogenous variance. The regression model obtained was Ŷ=77.083+ 0.370X. Meanwhile, the determinant coefficient (r2) obtained was 0.047 or 4.7% that mean ecolabel knowledge just contributed 4,71% to the green product purchase decision. These implied that many factors contributed in the purchase decision of green product instead of ecolabel knowledge.

Why do we need theories?

PubMed Central

Longo, Giuseppe; Soto, Ana M.

2017-01-01

Theories organize knowledge and construct objectivity by framing observations and experiments. The elaboration of theoretical principles is examined in the light of the rich interactions between physics and mathematics. These two disciplines share common principles of construction of concepts and of the proper objects of inquiry. Theory construction in physics relies on mathematical symmetries that preserve the key invariants observed and proposed by such theory; these invariants buttress the idea that the objects of physics are generic and thus interchangeable and they move along specific trajectories which are uniquely determined, in classical and relativistic physics. In contrast to physics, biology is a historical science that centers on the changes that organisms experience while undergoing ontogenesis and phylogenesis. Biological objects, namely organisms, are not generic but specific; they are individuals. The incessant changes they undergo represent the breaking of symmetries, and thus the opposite of symmetry conservation, a central component of physical theories. This instability corresponds to the changes of the environment and the phenotypes. Inspired by Galileo’s principle of inertia, the “default state” of inert matter, we propose a “default state” for biological dynamics following Darwin’s first principle, “descent with modification” that we transform into “proliferation with variation and motility” as a property that spans life, including cells in an organism. These dissimilarities between theories of the inert and of biology also apply to causality: biological causality is to be understood in relation to the distinctive role that constraints assume in this discipline. Consequently, the notion of cause will be reframed in a context where constraints to activity are seen as the core component of biological analyses. Finally, we assert that the radical materiality of life rules out distinctions such as “software vs. hardware.” PMID:27390105

Why do we need theories?

PubMed

Longo, Giuseppe; Soto, Ana M

2016-10-01

Theories organize knowledge and construct objectivity by framing observations and experiments. The elaboration of theoretical principles is examined in the light of the rich interactions between physics and mathematics. These two disciplines share common principles of construction of concepts and of the proper objects of inquiry. Theory construction in physics relies on mathematical symmetries that preserve the key invariants observed and proposed by such theory; these invariants buttress the idea that the objects of physics are generic and thus interchangeable and they move along specific trajectories which are uniquely determined, in classical and relativistic physics. In contrast to physics, biology is a historical science that centers on the changes that organisms experience while undergoing ontogenesis and phylogenesis. Biological objects, namely organisms, are not generic but specific; they are individuals. The incessant changes they undergo represent the breaking of symmetries, and thus the opposite of symmetry conservation, a central component of physical theories. This instability corresponds to the changes of the environment and the phenotypes. Inspired by Galileo's principle of inertia, the "default state" of inert matter, we propose a "default state" for biological dynamics following Darwin's first principle, "descent with modification" that we transform into "proliferation with variation and motility" as a property that spans life, including cells in an organism. These dissimilarities between theories of the inert and of biology also apply to causality: biological causality is to be understood in relation to the distinctive role that constraints assume in this discipline. Consequently, the notion of cause will be reframed in a context where constraints to activity are seen as the core component of biological analyses. Finally, we assert that the radical materiality of life rules out distinctions such as "software vs. hardware." Copyright © 2016 Elsevier Ltd. All rights reserved.

Soluble microbial products (SMPs) release in activated sludge systems: a review

PubMed Central

2012-01-01

This review discusses the characterization, production and implications of soluble microbial products (SMPs) in biological wastewater treatment. The precise definition of SMPs is open to talk about, but is currently regarded as “the pool of organic compounds that are released into solution from substrate metabolism and biomass decay”'. Some of the SMPs have been identified as humic acids, polysaccharides, proteins, amino acids, antibiotics, extracellular enzymes and structural components of cells and products of energy metabolism. They adversely affect the kinetic activity, flocculating and settling properties of sludge. This review outlines some important findings with regard to biodegradability and treatability of SMPs and also the effect of process parameters on their production. As SMPs are produced during biological treatment process, their trace amounts normally remain in the effluent that defines the highest COD removal efficiency. Their presence in effluent represents a high potential risk of toxic by-product formation during chlorine disinfection. Studies have indicated that among all wastewater post-treatment processes, the adsorption by granular activated carbon combined with biologically induced degradation is the most effective method for removal of SMPs. However, it may be concludes that the knowledge regarding SMPs is still under progress and more work is required to fully understand their contribution to the treatment process. PMID:23369231

Large Mammalian Animal Models of Heart Disease

PubMed Central

Camacho, Paula; Fan, Huimin; Liu, Zhongmin; He, Jia-Qiang

2016-01-01

Due to the biological complexity of the cardiovascular system, the animal model is an urgent pre-clinical need to advance our knowledge of cardiovascular disease and to explore new drugs to repair the damaged heart. Ideally, a model system should be inexpensive, easily manipulated, reproducible, a biological representative of human disease, and ethically sound. Although a larger animal model is more expensive and difficult to manipulate, its genetic, structural, functional, and even disease similarities to humans make it an ideal model to first consider. This review presents the commonly-used large animals—dog, sheep, pig, and non-human primates—while the less-used other large animals—cows, horses—are excluded. The review attempts to introduce unique points for each species regarding its biological property, degrees of susceptibility to develop certain types of heart diseases, and methodology of induced conditions. For example, dogs barely develop myocardial infarction, while dilated cardiomyopathy is developed quite often. Based on the similarities of each species to the human, the model selection may first consider non-human primates—pig, sheep, then dog—but it also depends on other factors, for example, purposes, funding, ethics, and policy. We hope this review can serve as a basic outline of large animal models for cardiovascular researchers and clinicians. PMID:29367573

On the Materials Science of Nature's Arms Race.

PubMed

Liu, Zengqian; Zhang, Zhefeng; Ritchie, Robert O

2018-06-05

Biological material systems have evolved unique combinations of mechanical properties to fulfill their specific function through a series of ingenious designs. Seeking lessons from Nature by replicating the underlying principles of such biological materials offers new promise for creating unique combinations of properties in man-made systems. One case in point is Nature's means of attack and defense. During the long-term evolutionary "arms race," naturally evolved weapons have achieved exceptional mechanical efficiency with a synergy of effective offense and persistence-two characteristics that often tend to be mutually exclusive in many synthetic systems-which may present a notable source of new materials science knowledge and inspiration. This review categorizes Nature's weapons into ten distinct groups, and discusses the unique structural and mechanical designs of each group by taking representative systems as examples. The approach described is to extract the common principles underlying such designs that could be translated into man-made materials. Further, recent advances in replicating the design principles of natural weapons at differing lengthscales in artificial materials, devices and tools to tackle practical problems are revisited, and the challenges associated with biological and bioinspired materials research in terms of both processing and properties are discussed. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Gravity-Responsive Time-Keeping Protein of the Plant and Animal Cell Surface

NASA Technical Reports Server (NTRS)

Morre, D. James

2003-01-01

The hypothesis under investigation was that a ubiquinol (NADH) oxidase protein of the cell surface with protein disulfide-thiol interchange activity (= NOX protein) is a plant and animal time-keeping ultradian (period of less than 24 h) driver of both cell enlargement and the biological clock that responds to gravity. Despite considerable work in a large number of laboratories spanning several decades, this is, to my knowledge, our work is the first demonstration of a time-keeping biochemical reaction that is both gravity-responsive and growth-related and that has been shown to determine circadian periodicity. As such, the NOX protein may represent both the long-sought biological gravity receptor and the core oscillator of the cellular biological clock. Completed studies have resulted in 12 publications and two issued NASA-owned patents of the clock activity. The gravity response and autoentrainment were characterized in cultured mammalian cells and in two plant systems together with entrainment by light and small molecules (melatonin). The molecular basis of the oscillatory behavior was investigated using spectroscopic methods (Fourier transform infrared and circular dichroism) and high resolution electron microscopy. We have also applied these findings to an understanding of the response to hypergravity. Statistical methods for analysis of time series phenomena were developed (Foster et al., 2003).

Exploring autophagy with Gene Ontology

PubMed Central

2018-01-01

ABSTRACT Autophagy is a fundamental cellular process that is well conserved among eukaryotes. It is one of the strategies that cells use to catabolize substances in a controlled way. Autophagy is used for recycling cellular components, responding to cellular stresses and ridding cells of foreign material. Perturbations in autophagy have been implicated in a number of pathological conditions such as neurodegeneration, cardiac disease and cancer. The growing knowledge about autophagic mechanisms needs to be collected in a computable and shareable format to allow its use in data representation and interpretation. The Gene Ontology (GO) is a freely available resource that describes how and where gene products function in biological systems. It consists of 3 interrelated structured vocabularies that outline what gene products do at the biochemical level, where they act in a cell and the overall biological objectives to which their actions contribute. It also consists of ‘annotations’ that associate gene products with the terms. Here we describe how we represent autophagy in GO, how we create and define terms relevant to autophagy researchers and how we interrelate those terms to generate a coherent view of the process, therefore allowing an interoperable description of its biological aspects. We also describe how annotation of gene products with GO terms improves data analysis and interpretation, hence bringing a significant benefit to this field of study. PMID:29455577

Soluble microbial products (SMPs) release in activated sludge systems: a review.

PubMed

Azami, Hamed; Sarrafzadeh, Mohammad Hossein; Mehrnia, Mohammad Reza

2012-12-18

This review discusses the characterization, production and implications of soluble microbial products (SMPs) in biological wastewater treatment. The precise definition of SMPs is open to talk about, but is currently regarded as "the pool of organic compounds that are released into solution from substrate metabolism and biomass decay"'. Some of the SMPs have been identified as humic acids, polysaccharides, proteins, amino acids, antibiotics, extracellular enzymes and structural components of cells and products of energy metabolism. They adversely affect the kinetic activity, flocculating and settling properties of sludge. This review outlines some important findings with regard to biodegradability and treatability of SMPs and also the effect of process parameters on their production. As SMPs are produced during biological treatment process, their trace amounts normally remain in the effluent that defines the highest COD removal efficiency. Their presence in effluent represents a high potential risk of toxic by-product formation during chlorine disinfection. Studies have indicated that among all wastewater post-treatment processes, the adsorption by granular activated carbon combined with biologically induced degradation is the most effective method for removal of SMPs. However, it may be concludes that the knowledge regarding SMPs is still under progress and more work is required to fully understand their contribution to the treatment process.

Sparse network modeling and metscape-based visualization methods for the analysis of large-scale metabolomics data.

PubMed

Basu, Sumanta; Duren, William; Evans, Charles R; Burant, Charles F; Michailidis, George; Karnovsky, Alla

2017-05-15

Recent technological advances in mass spectrometry, development of richer mass spectral libraries and data processing tools have enabled large scale metabolic profiling. Biological interpretation of metabolomics studies heavily relies on knowledge-based tools that contain information about metabolic pathways. Incomplete coverage of different areas of metabolism and lack of information about non-canonical connections between metabolites limits the scope of applications of such tools. Furthermore, the presence of a large number of unknown features, which cannot be readily identified, but nonetheless can represent bona fide compounds, also considerably complicates biological interpretation of the data. Leveraging recent developments in the statistical analysis of high-dimensional data, we developed a new Debiased Sparse Partial Correlation algorithm (DSPC) for estimating partial correlation networks and implemented it as a Java-based CorrelationCalculator program. We also introduce a new version of our previously developed tool Metscape that enables building and visualization of correlation networks. We demonstrate the utility of these tools by constructing biologically relevant networks and in aiding identification of unknown compounds. http://metscape.med.umich.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Phylogenetic Diversity and Biological Activity of Actinobacteria Isolated from the Chukchi Shelf Marine Sediments in the Arctic Ocean

PubMed Central

Yuan, Meng; Yu, Yong; Li, Hui-Rong; Dong, Ning; Zhang, Xiao-Hua

2014-01-01

Marine environments are a rich source of Actinobacteria and have the potential to produce a wide variety of biologically active secondary metabolites. In this study, we used four selective isolation media to culture Actinobacteria from the sediments collected from the Chukchi Shelf in the Arctic Ocean. A total of 73 actinobacterial strains were isolated. Based on repetitive DNA fingerprinting analysis, we selected 30 representatives for partial characterization according to their phylogenetic diversity, antimicrobial activities and secondary-metabolite biosynthesis genes. Results from the 16S rRNA gene sequence analysis indicated that the 30 strains could be sorted into 18 phylotypes belonging to 14 different genera: Agrococcus, Arsenicicoccus, Arthrobacter, Brevibacterium, Citricoccus, Janibacter, Kocuria, Microbacterium, Microlunatus, Nocardioides, Nocardiopsis, Saccharopolyspora, Salinibacterium and Streptomyces. To our knowledge, this paper is the first report on the isolation of Microlunatus genus members from marine habitats. Of the 30 isolates, 11 strains exhibited antibacterial and/or antifungal activity, seven of which have activities against Bacillus subtilis and Candida albicans. All 30 strains have at least two biosynthetic genes, one-third of which possess more than four biosynthetic genes. This study demonstrates the significant diversity of Actinobacteria in the Chukchi Shelf sediment and their potential for producing biologically active compounds and novel material for genetic manipulation or combinatorial biosynthesis. PMID:24663116

Chemical and Biochemical Approaches in the Study of Histone Methylation and Demethylation

PubMed Central

Li, Keqin Kathy; Luo, Cheng; Wang, Dongxia; Jiang, Hualiang; Zheng, Y. George

2014-01-01

Histone methylation represents one of the most critical epigenetic events in DNA function regulation in eukaryotic organisms. Classic molecular biology and genetics tools provide significant knowledge about mechanisms and physiological roles of histone methyltransferases and demethylases in various cellular processes. In addition to this stream line, development and application of chemistry and chemistry-related techniques are increasingly involved in biological study, and provide information otherwise difficulty to obtain by standard molecular biology methods. Herein, we review recent achievements and progress in developing and applying chemical and biochemical approaches in the study of histone methylation, including chromatin immunoprecipitation (ChIP), chemical ligation, mass spectrometry (MS), biochemical assays, and inhibitor development. These technological advances allow histone methylation to be studied from genome-wide level to molecular and atomic levels. With ChIP technology, information can be obtained about precise mapping of histone methylation patterns at specific promoters, genes or other genomic regions. MS is particularly useful in detecting and analyzing methylation marks in histone and nonhistone protein substrates. Chemical approaches that permit site-specific incorporation of methyl groups into histone proteins greatly facilitate the investigation of the biological impacts of methylation at individual modification sites. Discovery and design of selective organic inhibitors of histone methyltransferases and demethylases provide chemical probes to interrogate methylation-mediated cellular pathways. Overall, these chemistry-related technological advances have greatly improved our understanding of the biological functions of histone methylation in normal physiology and diseased states, and also are of great potential to translate basic epigenetics research into diagnostic and therapeutic application in the clinic. PMID:22777714

Ontology based molecular signatures for immune cell types via gene expression analysis

PubMed Central

2013-01-01

Background New technologies are focusing on characterizing cell types to better understand their heterogeneity. With large volumes of cellular data being generated, innovative methods are needed to structure the resulting data analyses. Here, we describe an ‘Ontologically BAsed Molecular Signature’ (OBAMS) method that identifies novel cellular biomarkers and infers biological functions as characteristics of particular cell types. This method finds molecular signatures for immune cell types based on mapping biological samples to the Cell Ontology (CL) and navigating the space of all possible pairwise comparisons between cell types to find genes whose expression is core to a particular cell type’s identity. Results We illustrate this ontological approach by evaluating expression data available from the Immunological Genome project (IGP) to identify unique biomarkers of mature B cell subtypes. We find that using OBAMS, candidate biomarkers can be identified at every strata of cellular identity from broad classifications to very granular. Furthermore, we show that Gene Ontology can be used to cluster cell types by shared biological processes in order to find candidate genes responsible for somatic hypermutation in germinal center B cells. Moreover, through in silico experiments based on this approach, we have identified genes sets that represent genes overexpressed in germinal center B cells and identify genes uniquely expressed in these B cells compared to other B cell types. Conclusions This work demonstrates the utility of incorporating structured ontological knowledge into biological data analysis – providing a new method for defining novel biomarkers and providing an opportunity for new biological insights. PMID:24004649

How biological background assumptions influence scientific risk evaluation of stacked genetically modified plants: an analysis of research hypotheses and argumentations.

PubMed

Rocca, Elena; Andersen, Fredrik

2017-08-14

Scientific risk evaluations are constructed by specific evidence, value judgements and biological background assumptions. The latter are the framework-setting suppositions we apply in order to understand some new phenomenon. That background assumptions co-determine choice of methodology, data interpretation, and choice of relevant evidence is an uncontroversial claim in modern basic science. Furthermore, it is commonly accepted that, unless explicated, disagreements in background assumptions can lead to misunderstanding as well as miscommunication. Here, we extend the discussion on background assumptions from basic science to the debate over genetically modified (GM) plants risk assessment. In this realm, while the different political, social and economic values are often mentioned, the identity and role of background assumptions at play are rarely examined. We use an example from the debate over risk assessment of stacked genetically modified plants (GM stacks), obtained by applying conventional breeding techniques to GM plants. There are two main regulatory practices of GM stacks: (i) regulate as conventional hybrids and (ii) regulate as new GM plants. We analyzed eight papers representative of these positions and found that, in all cases, additional premises are needed to reach the stated conclusions. We suggest that these premises play the role of biological background assumptions and argue that the most effective way toward a unified framework for risk analysis and regulation of GM stacks is by explicating and examining the biological background assumptions of each position. Once explicated, it is possible to either evaluate which background assumptions best reflect contemporary biological knowledge, or to apply Douglas' 'inductive risk' argument.

Measurement of the 100 MHz EMF radiation in vivo effects on zebrafish D. rerio embryonic development: A multidisciplinary study.

PubMed

Piccinetti, Chiara Carla; De Leo, Alfredo; Cosoli, Gloria; Scalise, Lorenzo; Randazzo, Basilio; Cerri, Graziano; Olivotto, Ike

2018-06-15

The augmented exposure of both environment and human being to electromagnetic waves and the concomitant lack of an unequivocal knowledge about biological consequences of these radiations, raised public interest on electromagnetic pollution. In this context, the present study aims to evaluate the biological effects on zebrafish (ZF) embryos of 100 MHz radiofrequency electromagnetic field (RF-EMF) exposure through a multidisciplinary protocol. Because of the shared synteny between human and ZF genomes that validated its use in biomedical research, toxicology and developmental biology studies, ZF was here selected as experimental model and a measurement protocol and biological analyses have been set up to clearly discriminate between RF-EMF biological and thermal effects. The results showed that a 100 MHz EMF was able to affect ZF embryonic development, from 24 to 72 h post fertilization (hpf) in all the analyzed pathways. Particularly, at the 48 hpf stage, a reduced growth, an increased transcription of oxidative stress genes, the onset of apoptotic/autophagic processes and a modification in cholesterol metabolism were detected. ZF embryos faced stress induced by EMF radiation by triggering detoxification mechanisms and at 72 hpf they partially recovered from stress reaching the hatching time in a comparable way respect to the control group. Data here obtained showed unequivocally the in vivo effects of RF-EMF on an animal model, excluding thermal outcomes and thus represents the starting point for more comprehensive studies on dose response effects of electromagnetic fields radiations consequences. Copyright © 2018 Elsevier Inc. All rights reserved.