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

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.

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.

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.

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.

The Effectiveness of an Online Curriculum on High School Students' Understanding of Biological Evolution

NASA Astrophysics Data System (ADS)

Marsteller, Robert B.; Bodzin, Alec M.

2015-12-01

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 analysis of discussion forum posts, and a post-implementation perceptions and attitudes questionnaire. BEAM posttest scores were significantly higher than the pretest scores. However, the findings revealed that the students required additional support to develop evidentiary reasoning. Many students perceived that the Web-based curriculum would have been enhanced by increased immediate interaction and feedback. Students required greater scaffolding to support complex, process-oriented tasks. Implications for designing Web-based science instruction with curriculum materials to support students' acquisition of content knowledge and science process skills in a Web-based setting are discussed.

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.

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.

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.

Knowledge-driven genomic interactions: an application in ovarian cancer.

PubMed

Kim, Dokyoon; Li, Ruowang; Dudek, Scott M; Frase, Alex T; Pendergrass, Sarah A; Ritchie, Marylyn D

2014-01-01

Effective cancer clinical outcome prediction for understanding of the mechanism of various types of cancer has been pursued using molecular-based data such as gene expression profiles, an approach that has promise for providing better diagnostics and supporting further therapies. However, clinical outcome prediction based on gene expression profiles varies between independent data sets. Further, single-gene expression outcome prediction is limited for cancer evaluation since genes do not act in isolation, but rather interact with other genes in complex signaling or regulatory networks. In addition, since pathways are more likely to co-operate together, it would be desirable to incorporate expert knowledge to combine pathways in a useful and informative manner. Thus, we propose a novel approach for identifying knowledge-driven genomic interactions and applying it to discover models associated with cancer clinical phenotypes using grammatical evolution neural networks (GENN). In order to demonstrate the utility of the proposed approach, an ovarian cancer data from the Cancer Genome Atlas (TCGA) was used for predicting clinical stage as a pilot project. We identified knowledge-driven genomic interactions associated with cancer stage from single knowledge bases such as sources of pathway-pathway interaction, but also knowledge-driven genomic interactions across different sets of knowledge bases such as pathway-protein family interactions by integrating different types of information. Notably, an integration model from different sources of biological knowledge achieved 78.82% balanced accuracy and outperformed the top models with gene expression or single knowledge-based data types alone. Furthermore, the results from the models are more interpretable because they are framed in the context of specific biological pathways or other expert knowledge. The success of the pilot study we have presented herein will allow us to pursue further identification of models predictive of clinical cancer survival and recurrence. Understanding the underlying tumorigenesis and progression in ovarian cancer through the global view of interactions within/between different biological knowledge sources has the potential for providing more effective screening strategies and therapeutic targets for many types of cancer.

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.

A Theme-Based Approach to Teaching Nonmajors Biology: Helping Students Connect Biology to Their Lives

ERIC Educational Resources Information Center

Chaplin, Susan B.; Manske, Jill M.

2005-01-01

This article describes the curriculum for a highly student-centered human biology course constructed around a series of themes that enables the integration of the same basic paradigms found in a traditional survey lecture course without sacrificing essential content. The theme-based model enhances student interest, ability to integrate knowledge,…

Developing Guided Inquiry-Based Student Lab Worksheet for Laboratory Knowledge Course

NASA Astrophysics Data System (ADS)

Rahmi, Y. L.; Novriyanti, E.; Ardi, A.; Rifandi, R.

2018-04-01

The course of laboratory knowledge is an introductory course for biology students to follow various lectures practicing in the biology laboratory. Learning activities of laboratory knowledge course at this time in the Biology Department, Universitas Negeri Padang has not been completed by supporting learning media such as student lab worksheet. Guided inquiry learning model is one of the learning models that can be integrated into laboratory activity. The study aimed to produce student lab worksheet based on guided inquiry for laboratory knowledge course and to determine the validity of lab worksheet. The research was conducted using research and developmet (R&D) model. The instruments used in data collection in this research were questionnaire for student needed analysis and questionnaire to measure the student lab worksheet validity. The data obtained was quantitative from several validators. The validators consist of three lecturers. The percentage of a student lab worksheet validity was 94.18 which can be categorized was very good.

Biology in Context: Teachers' Professional Development in Learning Communities

ERIC Educational Resources Information Center

Elster, Doris

2009-01-01

Biology in Context ("bik") is a project that aims to improve biology teaching in lower secondary schools in Germany. Based on a theoretical framework derived from the National Educational Standards, four competence areas should be fostered in biology education: subject knowledge; inquiry acquisition; subject-related communication; and…

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

[Biologic therapy in idiopathic inflammatory myopathy].

PubMed

Selva-O'Callaghan, Albert; Ramos Casals, Manel; Grau Junyent, Josep M

2014-09-15

The aim of this article is to study the evidence-based knowledge related to the use of biological therapies in patients diagnosed with idiopathic inflammatory myopathy (dermatomyositis, polymyositis and inclusion body myositis). In this review the leading published studies related to the use of biological therapy in patients with myositis are analysed; mainly those with high methodological standards, that means randomized and controlled studies. Methodological drawbacks due to the rarity and heterogeneity of these complex diseases are also addressed. Up to now is not possible to ascertain the biologics as a recommended therapy in patients with myositis, at least based in the current evidence-based knowledge, although it can not be neglected as a therapeutic option in some clinical situations, taking into account the scarce of effective treatments in those patients, especially in refractory myositis. Future studies probably will help to better define the role of biological therapies in patients with idiopathic inflammatory myopathy. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.

Virtual Tissues and Developmental Systems Biology (book chapter)

EPA Science Inventory

Virtual tissue (VT) models provide an in silico environment to simulate cross-scale properties in specific tissues or organs based on knowledge of the underlying biological networks. These integrative models capture the fundamental interactions in a biological system and enable ...

Gene network biological validity based on gene-gene interaction relevance.

PubMed

Gómez-Vela, Francisco; Díaz-Díaz, Norberto

2014-01-01

In recent years, gene networks have become one of the most useful tools for modeling biological processes. Many inference gene network algorithms have been developed as techniques for extracting knowledge from gene expression data. Ensuring the reliability of the inferred gene relationships is a crucial task in any study in order to prove that the algorithms used are precise. Usually, this validation process can be carried out using prior biological knowledge. The metabolic pathways stored in KEGG are one of the most widely used knowledgeable sources for analyzing relationships between genes. This paper introduces a new methodology, GeneNetVal, to assess the biological validity of gene networks based on the relevance of the gene-gene interactions stored in KEGG metabolic pathways. Hence, a complete KEGG pathway conversion into a gene association network and a new matching distance based on gene-gene interaction relevance are proposed. The performance of GeneNetVal was established with three different experiments. Firstly, our proposal is tested in a comparative ROC analysis. Secondly, a randomness study is presented to show the behavior of GeneNetVal when the noise is increased in the input network. Finally, the ability of GeneNetVal to detect biological functionality of the network is shown.

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.

Novel nonlinear knowledge-based mean force potentials based on machine learning.

PubMed

Dong, Qiwen; Zhou, Shuigeng

2011-01-01

The prediction of 3D structures of proteins from amino acid sequences is one of the most challenging problems in molecular biology. An essential task for solving this problem with coarse-grained models is to deduce effective interaction potentials. The development and evaluation of new energy functions is critical to accurately modeling the properties of biological macromolecules. Knowledge-based mean force potentials are derived from statistical analysis of proteins of known structures. Current knowledge-based potentials are almost in the form of weighted linear sum of interaction pairs. In this study, a class of novel nonlinear knowledge-based mean force potentials is presented. The potential parameters are obtained by nonlinear classifiers, instead of relative frequencies of interaction pairs against a reference state or linear classifiers. The support vector machine is used to derive the potential parameters on data sets that contain both native structures and decoy structures. Five knowledge-based mean force Boltzmann-based or linear potentials are introduced and their corresponding nonlinear potentials are implemented. They are the DIH potential (single-body residue-level Boltzmann-based potential), the DFIRE-SCM potential (two-body residue-level Boltzmann-based potential), the FS potential (two-body atom-level Boltzmann-based potential), the HR potential (two-body residue-level linear potential), and the T32S3 potential (two-body atom-level linear potential). Experiments are performed on well-established decoy sets, including the LKF data set, the CASP7 data set, and the Decoys “R”Us data set. The evaluation metrics include the energy Z score and the ability of each potential to discriminate native structures from a set of decoy structures. Experimental results show that all nonlinear potentials significantly outperform the corresponding Boltzmann-based or linear potentials, and the proposed discriminative framework is effective in developing knowledge-based mean force potentials. The nonlinear potentials can be widely used for ab initio protein structure prediction, model quality assessment, protein docking, and other challenging problems in computational biology.

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

Genetic and molecular bases of yield-associated traits: a translational biology approach between rice and wheat.

PubMed

Valluru, Ravi; Reynolds, Matthew P; Salse, Jerome

2014-07-01

Transferring the knowledge bases between related species may assist in enlarging the yield potential of crop plants. Being cereals, rice and wheat share a high level of gene conservation; however, they differ at metabolic levels as a part of the environmental adaptation resulting in different yield capacities. This review focuses on the current understanding of genetic and molecular regulation of yield-associated traits in both crop species, highlights the similarities and differences and presents the putative knowledge gaps. We focus on the traits associated with phenology, photosynthesis, and assimilate partitioning and lodging resistance; the most important drivers of yield potential. Currently, there are large knowledge gaps in the genetic and molecular control of such major biological processes that can be filled in a translational biology approach in transferring genomics and genetics informations between rice and wheat.

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.

Margin based ontology sparse vector learning algorithm and applied in biology science.

PubMed

Gao, Wei; Qudair Baig, Abdul; Ali, Haidar; Sajjad, Wasim; Reza Farahani, Mohammad

2017-01-01

In biology field, the ontology application relates to a large amount of genetic information and chemical information of molecular structure, which makes knowledge of ontology concepts convey much information. Therefore, in mathematical notation, the dimension of vector which corresponds to the ontology concept is often very large, and thus improves the higher requirements of ontology algorithm. Under this background, we consider the designing of ontology sparse vector algorithm and application in biology. In this paper, using knowledge of marginal likelihood and marginal distribution, the optimized strategy of marginal based ontology sparse vector learning algorithm is presented. Finally, the new algorithm is applied to gene ontology and plant ontology to verify its efficiency.

Long-Term Conceptual Retrieval by College Biology Majors Following Model-Based Instruction

ERIC Educational Resources Information Center

Dauer, Joseph T.; Long, Tammy M.

2015-01-01

One of the goals of college-level introductory biology is to establish a foundation of knowledge and skills that can be built upon throughout a biology curriculum. In a reformed introductory biology course, we used iterative model construction as a pedagogical tool to promote students' understanding about conceptual connections, particularly those…

Structural and Network-based Methods for Knowledge-Based Systems

DTIC Science & Technology

2011-12-01

depth) provide important information about knowledge gaps in the KB. For example, if SuccessEstimate (causes-EventEvent, Typhoid - Fever , 1, 3) is...equal to 0, it points toward lack of biological knowledge about Typhoid - Fever in our KB. Similar information can also be obtained from the...position of the consequent. ⋃ ( ( ) ) Therefore, if Q does not contain Typhoid - Fever , then obtaining

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.

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.

Survey of local and global biological network alignment: the need to reconcile the two sides of the same coin.

PubMed

Guzzi, Pietro Hiram; Milenkovic, Tijana

2018-05-01

Analogous to genomic sequence alignment that allows for across-species transfer of biological knowledge between conserved sequence regions, biological network alignment can be used to guide the knowledge transfer between conserved regions of molecular networks of different species. Hence, biological network alignment can be used to redefine the traditional notion of a sequence-based homology to a new notion of network-based homology. Analogous to genomic sequence alignment, there exist local and global biological network alignments. Here, we survey prominent and recent computational approaches of each network alignment type and discuss their (dis)advantages. Then, as it was recently shown that the two approach types are complementary, in the sense that they capture different slices of cellular functioning, we discuss the need to reconcile the two network alignment types and present a recent first step in this direction. We conclude with some open research problems on this topic and comment on the usefulness of network alignment in other domains besides computational biology.

“Shrink Wrapping” Lectures: Teaching Cell and Molecular Biology within the Context of Human Pathologies

PubMed Central

2005-01-01

Students are most motivated and learn best when they are immersed in an environment that causes them to realize why they should learn. Perhaps nowhere is this truer than when teaching the biological sciences to engineers. Transitioning from a traditionally mathematics-based to a traditionally knowledge-based pedagogical style can challenge student learning and engagement. To address this, human pathologies were used as a problem-based context for teaching knowledge-based cell biological mechanisms. Lectures were divided into four modules. First, a disease was presented from clinical, economic, and etiological standpoints. Second, fundamental concepts of cell and molecular biology were taught that were directly relevant to that disease. Finally, we discussed the cellular and molecular basis of the disease based on these fundamental concepts, together with current clinical approaches to the disease. The basic science is thus presented within a “shrink wrap” of disease application. Evaluation of this contextual technique suggests that it is very useful in improving undergraduate student focus and motivation, and offers many advantages to the instructor as well. PMID:15917872

Inference of Gene Regulatory Networks Incorporating Multi-Source Biological Knowledge via a State Space Model with L1 Regularization

PubMed Central

Hasegawa, Takanori; Yamaguchi, Rui; Nagasaki, Masao; Miyano, Satoru; Imoto, Seiya

2014-01-01

Comprehensive understanding of gene regulatory networks (GRNs) is a major challenge in the field of systems biology. Currently, there are two main approaches in GRN analysis using time-course observation data, namely an ordinary differential equation (ODE)-based approach and a statistical model-based approach. The ODE-based approach can generate complex dynamics of GRNs according to biologically validated nonlinear models. However, it cannot be applied to ten or more genes to simultaneously estimate system dynamics and regulatory relationships due to the computational difficulties. The statistical model-based approach uses highly abstract models to simply describe biological systems and to infer relationships among several hundreds of genes from the data. However, the high abstraction generates false regulations that are not permitted biologically. Thus, when dealing with several tens of genes of which the relationships are partially known, a method that can infer regulatory relationships based on a model with low abstraction and that can emulate the dynamics of ODE-based models while incorporating prior knowledge is urgently required. To accomplish this, we propose a method for inference of GRNs using a state space representation of a vector auto-regressive (VAR) model with L1 regularization. This method can estimate the dynamic behavior of genes based on linear time-series modeling constructed from an ODE-based model and can infer the regulatory structure among several tens of genes maximizing prediction ability for the observational data. Furthermore, the method is capable of incorporating various types of existing biological knowledge, e.g., drug kinetics and literature-recorded pathways. The effectiveness of the proposed method is shown through a comparison of simulation studies with several previous methods. For an application example, we evaluated mRNA expression profiles over time upon corticosteroid stimulation in rats, thus incorporating corticosteroid kinetics/dynamics, literature-recorded pathways and transcription factor (TF) information. PMID:25162401

Teaching a Biotechnology Curriculum Based on Adapted Primary Literature

ERIC Educational Resources Information Center

Falk, Hedda; Brill, Gilat; Yarden, Anat

2008-01-01

Adapted primary literature (APL) refers to an educational genre specifically designed to enable the use of research articles for learning biology in high school. The present investigation focuses on the pedagogical content knowledge (PCK) of four high-school biology teachers who enacted an APL-based curriculum in biotechnology. Using a…

The Learning Processes of Two High-School Biology Students when Reading Primary Literature. Research Report

ERIC Educational Resources Information Center

Brill, Gilat; Falk, Hedda; Yarden, Anat

2004-01-01

Biology education, like education in any other discipline, strives to make students familiar with the knowledge, activities, and ways of thinking of the community of biologists. We produced a curriculum in developmental biology based on learning through primary literature, in an attempt to develop biological literacy among highschool students.…

Knowledge management for systems biology a general and visually driven framework applied to translational medicine.

PubMed

Maier, Dieter; Kalus, Wenzel; Wolff, Martin; Kalko, Susana G; Roca, Josep; Marin de Mas, Igor; Turan, Nil; Cascante, Marta; Falciani, Francesco; Hernandez, Miguel; Villà-Freixa, Jordi; Losko, Sascha

2011-03-05

To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype-phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene--disease and gene--compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.

Knowledge management for systems biology a general and visually driven framework applied to translational medicine

PubMed Central

2011-01-01

Background To enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory. Results To address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data. Conclusions We generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development. PMID:21375767

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

USDA-ARS?s Scientific Manuscript database

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...

Discipline-Based Education Research: Understanding and Improving Learning in Undergraduate Science and Engineering

ERIC Educational Resources Information Center

Singer, Susan R.; Nielsen, Natalie R.; Schweingruber, Heidi A.

2012-01-01

The National Science Foundation funded a synthesis study on the status, contributions, and future direction of discipline-based education research (DBER) in physics, biological sciences, geosciences, and chemistry. DBER combines knowledge of teaching and learning with deep knowledge of discipline-specific science content. It describes the…

Conceptual Model-Based Systems Biology: Mapping Knowledge and Discovering Gaps in the mRNA Transcription Cycle

PubMed Central

Somekh, Judith; Choder, Mordechai; Dori, Dov

2012-01-01

We propose a Conceptual Model-based Systems Biology framework for qualitative modeling, executing, and eliciting knowledge gaps in molecular biology systems. The framework is an adaptation of Object-Process Methodology (OPM), a graphical and textual executable modeling language. OPM enables concurrent representation of the system's structure—the objects that comprise the system, and behavior—how processes transform objects over time. Applying a top-down approach of recursively zooming into processes, we model a case in point—the mRNA transcription cycle. Starting with this high level cell function, we model increasingly detailed processes along with participating objects. Our modeling approach is capable of modeling molecular processes such as complex formation, localization and trafficking, molecular binding, enzymatic stimulation, and environmental intervention. At the lowest level, similar to the Gene Ontology, all biological processes boil down to three basic molecular functions: catalysis, binding/dissociation, and transporting. During modeling and execution of the mRNA transcription model, we discovered knowledge gaps, which we present and classify into various types. We also show how model execution enhances a coherent model construction. Identification and pinpointing knowledge gaps is an important feature of the framework, as it suggests where research should focus and whether conjectures about uncertain mechanisms fit into the already verified model. PMID:23308089

[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.

Reinvigorating Introductory Biology: A Theme-based, Investigative Approach To Teaching Biology Majors.

ERIC Educational Resources Information Center

Norton, Cynthia G.; Gildensoph, Lynne H.; Phillips, Martha M.; Wygal, Deborah D.; Olson, Kurt H.; Pellegrini, John J.; Tweeten, Kathleen A.

1997-01-01

Describes the reform of an introductory biology curriculum to reverse high attrition rates. Objectives include fostering self-directed learning, emphasizing process over content, and offering laboratory experiences that model the way to acquire scientific knowledge. Teaching methods include discussion, group mentoring, laboratory sections, and…

A Contribution of the Computer to Biology Education at the University.

ERIC Educational Resources Information Center

Anxolabehere, D.; And Others

1980-01-01

Described is part of the O.P.E. laboratory computer-based biology program designed for undergraduate medical and biology students. Described is an embryology dialogue in which the student proceeds through three stages in the knowledge and understanding of the concept of competence. (Author/DS)

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.

PANDORA: keyword-based analysis of protein sets by integration of annotation sources.

PubMed

Kaplan, Noam; Vaaknin, Avishay; Linial, Michal

2003-10-01

Recent advances in high-throughput methods and the application of computational tools for automatic classification of proteins have made it possible to carry out large-scale proteomic analyses. Biological analysis and interpretation of sets of proteins is a time-consuming undertaking carried out manually by experts. We have developed PANDORA (Protein ANnotation Diagram ORiented Analysis), a web-based tool that provides an automatic representation of the biological knowledge associated with any set of proteins. PANDORA uses a unique approach of keyword-based graphical analysis that focuses on detecting subsets of proteins that share unique biological properties and the intersections of such sets. PANDORA currently supports SwissProt keywords, NCBI Taxonomy, InterPro entries and the hierarchical classification terms from ENZYME, SCOP and GO databases. The integrated study of several annotation sources simultaneously allows a representation of biological relations of structure, function, cellular location, taxonomy, domains and motifs. PANDORA is also integrated into the ProtoNet system, thus allowing testing thousands of automatically generated clusters. We illustrate how PANDORA enhances the biological understanding of large, non-uniform sets of proteins originating from experimental and computational sources, without the need for prior biological knowledge on individual proteins.

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

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

Biology Factual Knowledge at Eleventh Grade of Senior High School Students in Pacitan based on Favorite Schools

NASA Astrophysics Data System (ADS)

Yustiana, I. A.; Paidi; Mercuriani, I. S.

2018-03-01

This study aimed to determine the Biology factual knowledge at eleventh grade of senior high school students in Pacitan based on favorite schools. This research was a descriptive research by using survey method. The population in this study was all of senior high school students in Pacitan. The sampling technique used purposive sampling technique and obtained 3 favorite schools and 3 non-favorite schools. The technique of collecting data used test form which was as the instrument of the research. Data analysis technique used Mann-Whitney U test. Based on the test, it was obtained p = 0,000 (p <0,05) so there was a significant difference between the factual knowledge of the students in the favorite schools and non-favorite schools in Pacitan. The factual knowledge of students in favorite schools was higher with an average of 5.32 while non-favorite schools were obtained an average of 4.36.

SNAD: Sequence Name Annotation-based Designer.

PubMed

Sidorov, Igor A; Reshetov, Denis A; Gorbalenya, Alexander E

2009-08-14

A growing diversity of biological data is tagged with unique identifiers (UIDs) associated with polynucleotides and proteins to ensure efficient computer-mediated data storage, maintenance, and processing. These identifiers, which are not informative for most people, are often substituted by biologically meaningful names in various presentations to facilitate utilization and dissemination of sequence-based knowledge. This substitution is commonly done manually that may be a tedious exercise prone to mistakes and omissions. Here we introduce SNAD (Sequence Name Annotation-based Designer) that mediates automatic conversion of sequence UIDs (associated with multiple alignment or phylogenetic tree, or supplied as plain text list) into biologically meaningful names and acronyms. This conversion is directed by precompiled or user-defined templates that exploit wealth of annotation available in cognate entries of external databases. Using examples, we demonstrate how this tool can be used to generate names for practical purposes, particularly in virology. A tool for controllable annotation-based conversion of sequence UIDs into biologically meaningful names and acronyms has been developed and placed into service, fostering links between quality of sequence annotation, and efficiency of communication and knowledge dissemination among researchers.

[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.

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.

Participation in introductory biology laboratories: An integrated assessment based on surveys, behavioral observations, and qualitative interviews

NASA Astrophysics Data System (ADS)

Russell, Connie Adelle

Scope and method of study. The purpose of this study was to evaluate the effect of gender, major, and prior knowledge of and attitude toward biology on participation in introductory biology laboratories. Subjects for this study were 3,527 students enrolled in college-level introductory biology courses. During the study, three introductory courses were replaced with one mixed-majors course. The new course adopted a different pedagological approach from the previous courses in that an inquiry-based approach was used in lectures and laboratories. All subjects completed a survey that measured content knowledge using the NABT/NSTA High School Biology Examination Version 1990 and attitude using Russell and Hollander's Biology Attitude Scale. I used and discuss the merits of using ethological methods and data collection software, EthoScribeTM (Tima Scientific) to collect behavioral data from 145 students. I also evaluated participation using qualitative interviews of 30 students. I analyzed content knowledge and attitude data using ANOVA and Pearson correlation, and behavioral data using Contingency Table Analysis. I analyzed interviews following methods outlined by Rubin and Rubin. Findings. Course style and gender were the most useful variables in distinguishing differences among groups of students with regard to attitude, content knowledge, and participation in laboratories. Attitude toward biology and achievement measured by the surveys were found to be positively correlated; however, gender, major, class standing, course style and interactions between these variables also had effects on these variables. I found a positive association among attitude, achievement and participation in hands-on activities in laboratories. Differences in participation also were associated group type. In a traditional introductory biology course, females in single-gender groups, gender-equal, or groups in which females were the majority spent more time performing hands-on science-related activities than did females in groups in which they were the minority. Conversely, males in mixed-gender groups spent more time performing hands-on activities than did males in single-gender groups. Both sexes participated equally in laboratories taught in an inquiry-based style.

From Gene to Protein: A 3-Week Intensive Course in Molecular Biology for Physical Scientists

ERIC Educational Resources Information Center

Nadeau, Jay L.

2009-01-01

This article describes a 3-week intensive molecular biology methods course based upon fluorescent proteins, which is successfully taught at the McGill University to advanced undergraduates and graduates in physics, chemical engineering, biomedical engineering, and medicine. No previous knowledge of biological terminology or methods is expected, so…

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

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.

"Shrink Wrapping" Lectures: Teaching Cell and Molecular Biology within the Context of Human Pathologies

ERIC Educational Resources Information Center

Guilford, William H.

2005-01-01

Students are most motivated and learn best when they are immersed in an environment that causes them to realize why they should learn. Perhaps nowhere is this truer than when teaching the biological sciences to engineers. Transitioning from a traditionally mathematics-based to a traditionally knowledge-based pedagogical style can challenge student…

CBB Portal @ PNNL

Science.gov Websites

Search PNNL Home About Research Publications Jobs News Contacts Computational Biology and Bioinformatics , and engineering to transform the data into knowledge. This new quantitative, predictive biology is to empirical modeling and physics-based simulations. CBB research seeks to: Understand. Understanding

Promoting knowledge integration of scientific principles and environmental stewardship: Assessing an issue-based approach to teaching evolution and marine conservation

NASA Astrophysics Data System (ADS)

Zimmerman, Timothy David

2005-11-01

Students and citizens need to apply science to important issues every day. Yet the design of science curricula that foster integration of science and everyday decisions is not well understood. For example, can curricula be designed that help learners apply scientific reasons for choosing only environmentally sustainable seafood for dinner? Learners must develop integrated understandings of scientific principles, prior experiences, and current decisions in order to comprehend how everyday decisions impact environmental resources. In order to investigate how such integrated understandings can be promoted within school science classes, research was conducted with an inquiry-oriented curriculum that utilizes technology and a visit to an informal learning environment (aquarium) to promote the integration of scientific principles (adaptation) with environmental stewardship. This research used a knowledge integration approach to teaching and learning that provided a framework for promoting the application of science to environmental issues. Marine biology, often forsaken in classrooms for terrestrial biology, served as the scientific context for the curriculum. The curriculum design incorporated a three-phase pedagogical strategy and new technology tools to help students integrate knowledge and experiences across the classroom and aquarium learning environments. The research design and assessment protocols included comparisons among and within student populations using two versions of the curriculum: an issue-based version and a principle-based version. These inquiry curricula were tested with sophomore biology students attending a marine-focused academy within a coastal California high school. Pretest-posttest outcomes were compared between and within the curricular treatments. Additionally, comparisons were made between the inquiry groups and seniors in an Advanced Placement biology course who attend the same high school. Results indicate that the inquiry curricula enabled students to integrate and apply knowledge of evolutionary biology to real-world environmental stewardship issues. Over the course of the curriculum, students' ideas became more scientifically normative and tended to focus around concepts of natural selection. Students using the inquiry curricula outperformed the Advanced Placement biology students on several measures, including knowledge of evolutionary biology. These results have implications for designing science curricula that seek to promote the application of science to environmental stewardship and integrate formal and informal learning environments.

Who knows? Local non-timber forest product knowledge and stewardship practices in northern Michigan

Treesearch

Marla R. Emery

2001-01-01

Non-timber forest product (NTFP) literature frequently laments the absence of an information base for policy and management decisions. While formal scientific data on the biological and social ecologies of most NTFPs are limited to nonexistent, long-time gatherers often have extensive experiential knowledge bases. Researchers and managers may overlook this expertise...

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.

Computational biology for cardiovascular biomarker discovery.

PubMed

Azuaje, Francisco; Devaux, Yvan; Wagner, Daniel

2009-07-01

Computational biology is essential in the process of translating biological knowledge into clinical practice, as well as in the understanding of biological phenomena based on the resources and technologies originating from the clinical environment. One such key contribution of computational biology is the discovery of biomarkers for predicting clinical outcomes using 'omic' information. This process involves the predictive modelling and integration of different types of data and knowledge for screening, diagnostic or prognostic purposes. Moreover, this requires the design and combination of different methodologies based on statistical analysis and machine learning. This article introduces key computational approaches and applications to biomarker discovery based on different types of 'omic' data. Although we emphasize applications in cardiovascular research, the computational requirements and advances discussed here are also relevant to other domains. We will start by introducing some of the contributions of computational biology to translational research, followed by an overview of methods and technologies used for the identification of biomarkers with predictive or classification value. The main types of 'omic' approaches to biomarker discovery will be presented with specific examples from cardiovascular research. This will include a review of computational methodologies for single-source and integrative data applications. Major computational methods for model evaluation will be described together with recommendations for reporting models and results. We will present recent advances in cardiovascular biomarker discovery based on the combination of gene expression and functional network analyses. The review will conclude with a discussion of key challenges for computational biology, including perspectives from the biosciences and clinical areas.

A Conflict in Your Head: An Exploration of Trainee Science Teachers' Subject Matter Knowledge Development and Its Impact on Teacher Self-Confidence

ERIC Educational Resources Information Center

Kind, Vanessa

2009-01-01

Teachers' subject matter knowledge (SMK) is one factor contributing to teaching 'successfully', as this provides a basis from which pedagogical content knowledge develops. UK-based trainee science teachers teach all sciences to age 14 and often up to age 16. Trainees have specialist science knowledge in chemistry, physics, or biology from their…

New applications in EPA’s ECOTOX Knowledge System: Assimilating relative potencies of metals across chemical and biological species from literature-based toxicity effects data.

EPA Science Inventory

Toxicity of metals in field settings can vary widely among ionic chemical species and across biological receptors. Thus, a challenge often found in developing TRVs for the risk assessment of metals is identifying the most appropriate metal and biological species combinations for...

Revisiting Preschoolers' Living Things Concept: A Microgenetic Analysis of Conceptual Change in Basic Biology

ERIC Educational Resources Information Center

Opfer, John E.; Siegler, Robert S.

2004-01-01

Many preschoolers know that plants and animals share basic biological properties, but this knowledge does not usually lead them to conclude that plants, like animals, are living things. To resolve this seeming paradox, we hypothesized that preschoolers largely base their judgments of life status on a biological property, capacity for teleological…

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.

Comparing Two Forms of Concept Map Critique Activities to Facilitate Knowledge Integration Processes in Evolution Education

ERIC Educational Resources Information Center

Schwendimann, Beat A.; Linn, Marcia C.

2016-01-01

Concept map activities often lack a subsequent revision step that facilitates knowledge integration. This study compares two collaborative critique activities using a Knowledge Integration Map (KIM), a form of concept map. Four classes of high school biology students (n?=?81) using an online inquiry-based learning unit on evolution were assigned…

"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.

Integrating biological knowledge into variable selection: an empirical Bayes approach with an application in cancer biology

PubMed Central

2012-01-01

Background An important question in the analysis of biochemical data is that of identifying subsets of molecular variables that may jointly influence a biological response. Statistical variable selection methods have been widely used for this purpose. In many settings, it may be important to incorporate ancillary biological information concerning the variables of interest. Pathway and network maps are one example of a source of such information. However, although ancillary information is increasingly available, it is not always clear how it should be used nor how it should be weighted in relation to primary data. Results We put forward an approach in which biological knowledge is incorporated using informative prior distributions over variable subsets, with prior information selected and weighted in an automated, objective manner using an empirical Bayes formulation. We employ continuous, linear models with interaction terms and exploit biochemically-motivated sparsity constraints to permit exact inference. We show an example of priors for pathway- and network-based information and illustrate our proposed method on both synthetic response data and by an application to cancer drug response data. Comparisons are also made to alternative Bayesian and frequentist penalised-likelihood methods for incorporating network-based information. Conclusions The empirical Bayes method proposed here can aid prior elicitation for Bayesian variable selection studies and help to guard against mis-specification of priors. Empirical Bayes, together with the proposed pathway-based priors, results in an approach with a competitive variable selection performance. In addition, the overall procedure is fast, deterministic, and has very few user-set parameters, yet is capable of capturing interplay between molecular players. The approach presented is general and readily applicable in any setting with multiple sources of biological prior knowledge. PMID:22578440

Biological cycling of atmospheric trace gases

NASA Technical Reports Server (NTRS)

Hitchcock, D. R.; Wechsler, A. E.

1972-01-01

A detailed critical review was conducted of present knowledge of the influence of biological processes on the cycling of selected atmospheric gas constituents--methane, carbon monoxide, and gaseous compounds of nitrogen (nitrous oxide, ammonia, nitric oxide, and nitrogen dioxide) and sulfur (hydrogen sulfide and sulfur dioxide). The identification was included of biological and other sources of each gas, a survey of abundance measurements reported in the literature, and a review of the atmospheric fate of each contituent. Information is provided on which to base conclusions regarding the importance of biological processes on the atmospheric distribution and surface-atmosphere exchange of each constituent, and a basis for estimating the adequacy of present knowledge of these factors. A preliminary analysis was conducted of the feasibility of monitoring the biologically influenced temporal and spatial variations in abundance of these gases in the atmosphere from satellites.

Automated quantitative assessment of proteins' biological function in protein knowledge bases.

PubMed

Mayr, Gabriele; Lepperdinger, Günter; Lackner, Peter

2008-01-01

Primary protein sequence data are archived in databases together with information regarding corresponding biological functions. In this respect, UniProt/Swiss-Prot is currently the most comprehensive collection and it is routinely cross-examined when trying to unravel the biological role of hypothetical proteins. Bioscientists frequently extract single entries and further evaluate those on a subjective basis. In lieu of a standardized procedure for scoring the existing knowledge regarding individual proteins, we here report about a computer-assisted method, which we applied to score the present knowledge about any given Swiss-Prot entry. Applying this quantitative score allows the comparison of proteins with respect to their sequence yet highlights the comprehension of functional data. pfs analysis may be also applied for quality control of individual entries or for database management in order to rank entry listings.

Identifying biological concepts from a protein-related corpus with a probabilistic topic model

PubMed Central

Zheng, Bin; McLean, David C; Lu, Xinghua

2006-01-01

Background Biomedical literature, e.g., MEDLINE, contains a wealth of knowledge regarding functions of proteins. Major recurring biological concepts within such text corpora represent the domains of this body of knowledge. The goal of this research is to identify the major biological topics/concepts from a corpus of protein-related MEDLINE© titles and abstracts by applying a probabilistic topic model. Results The latent Dirichlet allocation (LDA) model was applied to the corpus. Based on the Bayesian model selection, 300 major topics were extracted from the corpus. The majority of identified topics/concepts was found to be semantically coherent and most represented biological objects or concepts. The identified topics/concepts were further mapped to the controlled vocabulary of the Gene Ontology (GO) terms based on mutual information. Conclusion The major and recurring biological concepts within a collection of MEDLINE documents can be extracted by the LDA model. The identified topics/concepts provide parsimonious and semantically-enriched representation of the texts in a semantic space with reduced dimensionality and can be used to index text. PMID:16466569

The Androgen Receptor and Its Use in Biological Assays: Looking Toward Effect-Based Testing and Its Applications

PubMed Central

Cadwallader, Amy B.; Lim, Carol S.; Rollins, Douglas E.; Botrè, Francesco

2015-01-01

Steroid abuse is a growing problem among amateur and professional athletes. Because of an inundation of newly and illegally synthesized steroids with minor structural modifications and other designer steroid receptor modulators, there is a need to develop new methods of detection which do not require prior knowledge of the abused steroid structure. The number of designer steroids currently being abused is unknown because detection methods in general are only identifying substances with a known structure. The detection of doping is moving away from merely checking for exposure to prohibited substance toward detecting an effect of prohibited substances, as biological assays can do. Cell-based biological assays are the next generation of assays which should be utilized by antidoping laboratories; they can detect androgenic anabolic steroid and other human androgen receptor (hAR) ligand presence without knowledge of their structure and assess the relative biological activity of these compounds. This review summarizes the hAR and its action and discusses its relevance to sports doping and its use in biological assays. PMID:22080898

Biology Procedural Knowledge at Eleventh Grade of Senior High School in West Lampung Based on Curriculum

NASA Astrophysics Data System (ADS)

Sari, T. M.; Paidi; Mercuriani, I. S.

2018-03-01

This study was aim to determine Biology procedural knowledge of senior high school in West Lampung based on curriculum at 11th grade in even semester. This research was descriptive research. The population was all students of senior high school in West Lampung. The sampling technique in this research used purposive sampling technique, so the researcher obtained 3 schools using K13 and 3 schools using KTSP. Data collecting technique used instrument test. Data analysis technique used U-Mann Whitney test. The result showed that p=0.028 (p<0.05), so there was significant differences between school using K13 and KTSP. The procedural knowledge of schools which using K13 is higher than school which using KTSP, with the mean score K13=4.35 and KTSP=4.00

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

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

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

Cocaine Use among the College Age Group: Biological and Psychological Effects--Clinical and Laboratory Research Findings.

ERIC Educational Resources Information Center

Nicholi, Armand M., Jr.

1984-01-01

Knowledge about cocaine's effect on the human mind and body is limited and not clearly documented. This article discusses various biological and psychological effects of the drug based on clinical and laboratory studies of man. (Author/DF)

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.

Using a Module-Based Laboratory to Incorporate Inquiry into a Large Cell Biology Course

ERIC Educational Resources Information Center

Howard, David R.; Miskowski, Jennifer A.

2005-01-01

Because cell biology has rapidly increased in breadth and depth, instructors are challenged not only to provide undergraduate science students with a strong, up-to-date foundation of knowledge, but also to engage them in the scientific process. To these ends, revision of the Cell Biology Lab course at the University of Wisconsin-La Crosse was…

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

Perceptions of Prospective Biology Teachers on Scientific Argumentation in Microbiology Inquiry Lab Activities

NASA Astrophysics Data System (ADS)

Roviati, E.; Widodo, A.; Purwianingsih, W.; Riandi, R.

2017-09-01

Inquiry laboratory activity and scientific argumentation in science education should be promoted and explicitly experienced by prospective biology teacher students in classes, including in microbiology courses. The goal of this study is to get information about perceptions of prospective biology teachers on scientific argumentation in microbiology inquiry lab activities. This study reported the result of a survey research to prospective biology teachers about how their perception about microbiology lab classes and their perception about inquiry and argumentation in microbiology lab activities should be. The participants of this study were 100 students of biology education department from an institute in Cirebon, West Java taking microbiology lecture during the fifth semester. The data were collected using questionnaire to explore the perceptions and knowledge of prospective biology teachers about microbiology, inquiry lab activities and argumentation. The result showed that students thought that the difficulties of microbiology as a subject were the lack of references and the way lecturer teaching. The students’ perception was that argumentation and inquiry should be implemented in microbiology courses and lab activities. Based on the data from questionnaire, It showed that prospective biology teacher students had very little knowledge about scientific argumentation and its implementation in science education. When the participants made arguments based on the problems given, they showed low quality of arguments.

Biological Nature of Knowledge in the Learning Organisation

ERIC Educational Resources Information Center

Hall, William P.

2005-01-01

Purpose: To develop a biological approach to the analysis of learning organisations based on complexity theory, autopoiesis, and evolutionary epistemology. Design/methodology/approach: This paper synthesises ideas from disciplines ranging from physics, epistemology and philosophy of science to military affairs, to sketch a scientific framework in…

An analysis of learning in an online biology course for teachers and teacher candidates: A mixed methods approach

NASA Astrophysics Data System (ADS)

Lebec, Michael Thomas

Due to discipline specific shortages, web-based learning has been proposed as a convenient way to upgrade the content knowledge of instructors interested in learning to teach science. Despite quantitative evidence that web-based instruction is equivalent to traditional methods, questions remain regarding its use. The efficiency and practicality of this approach with teachers in particular has not been extensively studied. This investigation examines learning in an online biology course designed to help teachers prepare for science certification exams. Research questions concern flow teachers learn biology in the online environment and how this setting influences the learning process. Quantitative and qualitative methodologies are employed in an attempt to provide a more complete perspective than typical studies of online learning. Concept maps, tests, and online discussion transcripts are compared as measures of assimilated knowledge, while interviews reflect participants' views on the course. Findings indicate that participants experienced gains in declarative knowledge, but little improvement with respect to conditional knowledge. Qualitative examination of concept maps demonstrates gaps in participants' understandings of key course ideas. Engagement in the use of online resources varied according to participants' attitudes towards online learning. Subjects also reported a lack of motivation to fully engage in the course due to busy teaching schedules and the absence of accountability.

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…

Factors Affecting Participation in Traditional and Inquiry-based Laboratories.

ERIC Educational Resources Information Center

Russell, Connie P.; French, Donald P.

2002-01-01

Reports on a study of participation, achievement, and attitude in cookbook and inquiry-based introductory biology laboratories through observations, interviews, and attitude/knowledge surveys. Participation differences between men and women disappeared in the inquiry-based laboratory. (Author/MM)

Global trends of local ecological knowledge and future implications

PubMed Central

Lemahieu, Anne; Sauer, Warwick H. H.

2018-01-01

Local and indigenous knowledge is being transformed globally, particularly being eroded when pertaining to ecology. In many parts of the world, rural and indigenous communities are facing tremendous cultural, economic and environmental changes, which contribute to weaken their local knowledge base. In the face of profound and ongoing environmental changes, both cultural and biological diversity are likely to be severely impacted as well as local resilience capacities from this loss. In this global literature review, we analyse the drivers of various types of local and indigenous ecological knowledge transformation and assess the directionality of the reported change. Results of this analysis show a global impoverishment of local and indigenous knowledge with 77% of papers reporting the loss of knowledge driven by globalization, modernization, and market integration. The recording of this loss, however, is not symmetrical, with losses being recorded more strongly in medicinal and ethnobotanical knowledge. Persistence of knowledge (15% of the studies) occurred in studies where traditional practices were being maintained consiously and where hybrid knowledge was being produced as a resut of certain types of incentives created by economic development. This review provides some insights into local and indigenous ecological knowledge change, its causes and implications, and recommends venues for the development of replicable and comparative research. The larger implication of these results is that because of the interconnection between cultural and biological diversity, the loss of local and indigenous knowledge is likely to critically threaten effective conservation of biodiversity, particularly in community-based conservation local efforts. PMID:29621311

Use of prior knowledge for the analysis of high-throughput transcriptomics and metabolomics data

PubMed Central

2014-01-01

Background High-throughput omics technologies have enabled the measurement of many genes or metabolites simultaneously. The resulting high dimensional experimental data poses significant challenges to transcriptomics and metabolomics data analysis methods, which may lead to spurious instead of biologically relevant results. One strategy to improve the results is the incorporation of prior biological knowledge in the analysis. This strategy is used to reduce the solution space and/or to focus the analysis on biological meaningful regions. In this article, we review a selection of these methods used in transcriptomics and metabolomics. We combine the reviewed methods in three groups based on the underlying mathematical model: exploratory methods, supervised methods and estimation of the covariance matrix. We discuss which prior knowledge has been used, how it is incorporated and how it modifies the mathematical properties of the underlying methods. PMID:25033193

Hypoxia-based strategies for regenerative dentistry-Views from the different dental fields.

PubMed

Müller, Anna Sonja; Janjić, Klara; Lilaj, Bledar; Edelmayer, Michael; Agis, Hermann

2017-09-01

The understanding of the cell biological processes underlying development and regeneration of oral tissues leads to novel regenerative approaches. Over the past years, knowledge on key roles of the hypoxia-based response has become more profound. Based on these findings, novel regenerative approaches for dentistry are emerging, which target cellular oxygen sensors. These approaches include hypoxia pre-conditioning and pharmacologically simulated hypoxia. The increase in studies on hypoxia and hypoxia-based strategies in regenerative dentistry highlights the growing attention to hypoxia's role in regeneration and its underlying biology, as well as its application in a therapeutic setting. In this narrative review, we present the current knowledge on the role of hypoxia in oral tissues and review the proposed hypoxia-based approaches in different fields of dentistry, including endodontics, orthodontics, periodontics, and oral surgery. Copyright © 2017 Elsevier Ltd. All rights reserved.

Understanding Pictorial Information in Biology: Students' Cognitive Activities and Visual Reading Strategies

ERIC Educational Resources Information Center

Brandstetter, Miriam; Sandmann, Angela; Florian, Christine

2017-01-01

In classroom, scientific contents are increasingly communicated through visual forms of representations. Students' learning outcomes rely on their ability to read and understand pictorial information. Understanding pictorial information in biology requires cognitive effort and can be challenging to students. Yet evidence-based knowledge about…

Biological Bases for Radiation Adaptive Responses in the Lung

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

Scott, Bobby R.; Lin, Yong; Wilder, Julie

2015-03-01

Our main research objective was to determine the biological bases for low-dose, radiation-induced adaptive responses in the lung, and use the knowledge gained to produce an improved risk model for radiation-induced lung cancer that accounts for activated natural protection, genetic influences, and the role of epigenetic regulation (epiregulation). Currently, low-dose radiation risk assessment is based on the linear-no-threshold hypothesis, which now is known to be unsupported by a large volume of data.

Enhancing Conceptual Knowledge of Energy in Biology with Incorrect Representations

ERIC Educational Resources Information Center

Wernecke, Ulrike; Schütte, Kerstin; Schwanewedel, Julia; Harms, Ute

2018-01-01

Energy is an important concept in all natural sciences, and a challenging one for school science education. Students' conceptual knowledge of energy is often low, and they entertain misconceptions. Educational research in science and mathematics suggests that learning through depictive representations and learning from errors, based on the theory…

Student Identity Considerations and Implications Associated with Socioscientific Issues Instruction

ERIC Educational Resources Information Center

Ruzek, Mitchel James

2014-01-01

The purpose of this investigation was to explore how aspects of identity, perceived levels of controversy, and the strength of a student's attachment to their controversial identity relate to conceptual understanding and knowledge acquisition during socioscientific issues (SSI) based instruction in a biology classroom. The knowledge gained from…

Development of Items for a Pedagogical Content Knowledge Test Based on Empirical Analysis of Pupils' Errors

ERIC Educational Resources Information Center

Juttner, Melanie; Neuhaus, Birgit J.

2012-01-01

In view of the lack of instruments for measuring biology teachers' pedagogical content knowledge (PCK), this article reports on a study about the development of PCK items for measuring teachers' knowledge of pupils' errors and ways for dealing with them. This study investigated 9th and 10th grade German pupils' (n = 461) drawings in an achievement…

Developing integrated crop knowledge networks to advance candidate gene discovery.

PubMed

Hassani-Pak, Keywan; Castellote, Martin; Esch, Maria; Hindle, Matthew; Lysenko, Artem; Taubert, Jan; Rawlings, Christopher

2016-12-01

The chances of raising crop productivity to enhance global food security would be greatly improved if we had a complete understanding of all the biological mechanisms that underpinned traits such as crop yield, disease resistance or nutrient and water use efficiency. With more crop genomes emerging all the time, we are nearer having the basic information, at the gene-level, to begin assembling crop gene catalogues and using data from other plant species to understand how the genes function and how their interactions govern crop development and physiology. Unfortunately, the task of creating such a complete knowledge base of gene functions, interaction networks and trait biology is technically challenging because the relevant data are dispersed in myriad databases in a variety of data formats with variable quality and coverage. In this paper we present a general approach for building genome-scale knowledge networks that provide a unified representation of heterogeneous but interconnected datasets to enable effective knowledge mining and gene discovery. We describe the datasets and outline the methods, workflows and tools that we have developed for creating and visualising these networks for the major crop species, wheat and barley. We present the global characteristics of such knowledge networks and with an example linking a seed size phenotype to a barley WRKY transcription factor orthologous to TTG2 from Arabidopsis, we illustrate the value of integrated data in biological knowledge discovery. The software we have developed (www.ondex.org) and the knowledge resources (http://knetminer.rothamsted.ac.uk) we have created are all open-source and provide a first step towards systematic and evidence-based gene discovery in order to facilitate crop improvement.

Developing a kidney and urinary pathway knowledge base

PubMed Central

2011-01-01

Background Chronic renal disease is a global health problem. The identification of suitable biomarkers could facilitate early detection and diagnosis and allow better understanding of the underlying pathology. One of the challenges in meeting this goal is the necessary integration of experimental results from multiple biological levels for further analysis by data mining. Data integration in the life science is still a struggle, and many groups are looking to the benefits promised by the Semantic Web for data integration. Results We present a Semantic Web approach to developing a knowledge base that integrates data from high-throughput experiments on kidney and urine. A specialised KUP ontology is used to tie the various layers together, whilst background knowledge from external databases is incorporated by conversion into RDF. Using SPARQL as a query mechanism, we are able to query for proteins expressed in urine and place these back into the context of genes expressed in regions of the kidney. Conclusions The KUPKB gives KUP biologists the means to ask queries across many resources in order to aggregate knowledge that is necessary for answering biological questions. The Semantic Web technologies we use, together with the background knowledge from the domain’s ontologies, allows both rapid conversion and integration of this knowledge base. The KUPKB is still relatively small, but questions remain about scalability, maintenance and availability of the knowledge itself. Availability The KUPKB may be accessed via http://www.e-lico.eu/kupkb. PMID:21624162

Promoting Self-Directed Learning in Developing or Poorly Defined Subject Areas: A Problem-Based Course in Molecular Biology, Genetics, and Cancer.

ERIC Educational Resources Information Center

Edmondson, Katherine M.

A new problem-based course in molecular biology, genetics, and cancer for first-year veterinary students was developed at the College of Veterinary Medicine at Cornell University (New York). The course was developed out of a desire to foster student-centered and lifelong learning and to integrate basic and clinical science knowledge despite a lack…

Extracting rate changes in transcriptional regulation from MEDLINE abstracts.

PubMed

Liu, Wenting; Miao, Kui; Li, Guangxia; Chang, Kuiyu; Zheng, Jie; Rajapakse, Jagath C

2014-01-01

Time delays are important factors that are often neglected in gene regulatory network (GRN) inference models. Validating time delays from knowledge bases is a challenge since the vast majority of biological databases do not record temporal information of gene regulations. Biological knowledge and facts on gene regulations are typically extracted from bio-literature with specialized methods that depend on the regulation task. In this paper, we mine evidences for time delays related to the transcriptional regulation of yeast from the PubMed abstracts. Since the vast majority of abstracts lack quantitative time information, we can only collect qualitative evidences of time delays. Specifically, the speed-up or delay in transcriptional regulation rate can provide evidences for time delays (shorter or longer) in GRN. Thus, we focus on deriving events related to rate changes in transcriptional regulation. A corpus of yeast regulation related abstracts was manually labeled with such events. In order to capture these events automatically, we create an ontology of sub-processes that are likely to result in transcription rate changes by combining textual patterns and biological knowledge. We also propose effective feature extraction methods based on the created ontology to identify the direct evidences with specific details of these events. Our ontologies outperform existing state-of-the-art gene regulation ontologies in the automatic rule learning method applied to our corpus. The proposed deterministic ontology rule-based method can achieve comparable performance to the automatic rule learning method based on decision trees. This demonstrates the effectiveness of our ontology in identifying rate-changing events. We also tested the effectiveness of the proposed feature mining methods on detecting direct evidence of events. Experimental results show that the machine learning method on these features achieves an F1-score of 71.43%. The manually labeled corpus of events relating to rate changes in transcriptional regulation for yeast is available in https://sites.google.com/site/wentingntu/data. The created ontologies summarized both biological causes of rate changes in transcriptional regulation and corresponding positive and negative textual patterns from the corpus. They are demonstrated to be effective in identifying rate-changing events, which shows the benefits of combining textual patterns and biological knowledge on extracting complex biological events.

Quantitative imaging biomarker ontology (QIBO) for knowledge representation of biomedical imaging biomarkers.

PubMed

Buckler, Andrew J; Liu, Tiffany Ting; Savig, Erica; Suzek, Baris E; Ouellette, M; Danagoulian, J; Wernsing, G; Rubin, Daniel L; Paik, David

2013-08-01

A widening array of novel imaging biomarkers is being developed using ever more powerful clinical and preclinical imaging modalities. These biomarkers have demonstrated effectiveness in quantifying biological processes as they occur in vivo and in the early prediction of therapeutic outcomes. However, quantitative imaging biomarker data and knowledge are not standardized, representing a critical barrier to accumulating medical knowledge based on quantitative imaging data. We use an ontology to represent, integrate, and harmonize heterogeneous knowledge across the domain of imaging biomarkers. This advances the goal of developing applications to (1) improve precision and recall of storage and retrieval of quantitative imaging-related data using standardized terminology; (2) streamline the discovery and development of novel imaging biomarkers by normalizing knowledge across heterogeneous resources; (3) effectively annotate imaging experiments thus aiding comprehension, re-use, and reproducibility; and (4) provide validation frameworks through rigorous specification as a basis for testable hypotheses and compliance tests. We have developed the Quantitative Imaging Biomarker Ontology (QIBO), which currently consists of 488 terms spanning the following upper classes: experimental subject, biological intervention, imaging agent, imaging instrument, image post-processing algorithm, biological target, indicated biology, and biomarker application. We have demonstrated that QIBO can be used to annotate imaging experiments with standardized terms in the ontology and to generate hypotheses for novel imaging biomarker-disease associations. Our results established the utility of QIBO in enabling integrated analysis of quantitative imaging data.

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.

The biomedical disciplines and the structure of biomedical and clinical knowledge.

PubMed

Nederbragt, H

2000-11-01

The relation between biomedical knowledge and clinical knowledge is discussed by comparing their respective structures. The knowledge of a disease as a biological phenomenon is constructed by the interaction of facts and theories from the main biomedical disciplines: epidemiology, diagnostics, clinical trial, therapy development and pathogenesis. Although these facts and theories are based on probabilities and extrapolations, the interaction provides a reliable and coherent structure, comparable to a Kuhnian paradigma. In the structure of clinical knowledge, i.e. knowledge of the patient with the disease, not only biomedical knowledge contributes to the structure but also economic and social relations, ethics and personal experience. However, the interaction between each of the participating "knowledges" in clinical knowledge is not based on mutual dependency and accumulation of different arguments from each, as in biomedical knowledge, but on competition and partial exclusion. Therefore, the structure of biomedical knowledge is different from that of clinical knowledge. This difference is used as the basis for a discussion in which the place of technology, evidence-based medicine and the gap between scientific and clinical knowledge are evaluated.

Agent-based models in translational systems biology

PubMed Central

An, Gary; Mi, Qi; Dutta-Moscato, Joyeeta; Vodovotz, Yoram

2013-01-01

Effective translational methodologies for knowledge representation are needed in order to make strides against the constellation of diseases that affect the world today. These diseases are defined by their mechanistic complexity, redundancy, and nonlinearity. Translational systems biology aims to harness the power of computational simulation to streamline drug/device design, simulate clinical trials, and eventually to predict the effects of drugs on individuals. The ability of agent-based modeling to encompass multiple scales of biological process as well as spatial considerations, coupled with an intuitive modeling paradigm, suggests that this modeling framework is well suited for translational systems biology. This review describes agent-based modeling and gives examples of its translational applications in the context of acute inflammation and wound healing. PMID:20835989

A Biochemistry and Molecular Biology Experiment and Evaluation System for Biotechnology Specialty Students: An Effective Evaluation System to Improve the Biochemistry and Molecular Biology Experiment Teaching

ERIC Educational Resources Information Center

Li, Suxia; Wu, Haizhen; Zhao, Jian; Ou, Ling; Zhang, Yuanxing

2010-01-01

In an effort to achieve high success in knowledge and technique acquisition as a whole, a biochemistry and molecular biology experiment was established for high-grade biotechnology specialty students after they had studied essential theory and received proper technique training. The experiment was based on cloning and expression of alkaline…

Assigned and unassigned distance geometry: applications to biological molecules and nanostructures

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

Billinge, Simon J. L.; Duxbury, Phillip M.; Gonçalves, Douglas S.

2016-04-04

Here, considering geometry based on the concept of distance, the results found by Menger and Blumenthal originated a body of knowledge called distance geometry. This survey covers some recent developments for assigned and unassigned distance geometry and focuses on two main applications: determination of three-dimensional conformations of biological molecules and nanostructures.

Selection platforms for directed evolution in synthetic biology

PubMed Central

Tizei, Pedro A.G.; Csibra, Eszter; Torres, Leticia; Pinheiro, Vitor B.

2016-01-01

Life on Earth is incredibly diverse. Yet, underneath that diversity, there are a number of constants and highly conserved processes: all life is based on DNA and RNA; the genetic code is universal; biology is limited to a small subset of potential chemistries. A vast amount of knowledge has been accrued through describing and characterizing enzymes, biological processes and organisms. Nevertheless, much remains to be understood about the natural world. One of the goals in Synthetic Biology is to recapitulate biological complexity from simple systems made from biological molecules–gaining a deeper understanding of life in the process. Directed evolution is a powerful tool in Synthetic Biology, able to bypass gaps in knowledge and capable of engineering even the most highly conserved biological processes. It encompasses a range of methodologies to create variation in a population and to select individual variants with the desired function–be it a ligand, enzyme, pathway or even whole organisms. Here, we present some of the basic frameworks that underpin all evolution platforms and review some of the recent contributions from directed evolution to synthetic biology, in particular methods that have been used to engineer the Central Dogma and the genetic code. PMID:27528765

Selection platforms for directed evolution in synthetic biology.

PubMed

Tizei, Pedro A G; Csibra, Eszter; Torres, Leticia; Pinheiro, Vitor B

2016-08-15

Life on Earth is incredibly diverse. Yet, underneath that diversity, there are a number of constants and highly conserved processes: all life is based on DNA and RNA; the genetic code is universal; biology is limited to a small subset of potential chemistries. A vast amount of knowledge has been accrued through describing and characterizing enzymes, biological processes and organisms. Nevertheless, much remains to be understood about the natural world. One of the goals in Synthetic Biology is to recapitulate biological complexity from simple systems made from biological molecules-gaining a deeper understanding of life in the process. Directed evolution is a powerful tool in Synthetic Biology, able to bypass gaps in knowledge and capable of engineering even the most highly conserved biological processes. It encompasses a range of methodologies to create variation in a population and to select individual variants with the desired function-be it a ligand, enzyme, pathway or even whole organisms. Here, we present some of the basic frameworks that underpin all evolution platforms and review some of the recent contributions from directed evolution to synthetic biology, in particular methods that have been used to engineer the Central Dogma and the genetic code. © 2016 The Author(s).

A novel knowledge-based potential for RNA 3D structure evaluation

NASA Astrophysics Data System (ADS)

Yang, Yi; Gu, Qi; Zhang, Ben-Gong; Shi, Ya-Zhou; Shao, Zhi-Gang

2018-03-01

Ribonucleic acids (RNAs) play a vital role in biology, and knowledge of their three-dimensional (3D) structure is required to understand their biological functions. Recently structural prediction methods have been developed to address this issue, but a series of RNA 3D structures are generally predicted by most existing methods. Therefore, the evaluation of the predicted structures is generally indispensable. Although several methods have been proposed to assess RNA 3D structures, the existing methods are not precise enough. In this work, a new all-atom knowledge-based potential is developed for more accurately evaluating RNA 3D structures. The potential not only includes local and nonlocal interactions but also fully considers the specificity of each RNA by introducing a retraining mechanism. Based on extensive test sets generated from independent methods, the proposed potential correctly distinguished the native state and ranked near-native conformations to effectively select the best. Furthermore, the proposed potential precisely captured RNA structural features such as base-stacking and base-pairing. Comparisons with existing potential methods show that the proposed potential is very reliable and accurate in RNA 3D structure evaluation. Project supported by the National Science Foundation of China (Grants Nos. 11605125, 11105054, 11274124, and 11401448).

On Crowd-verification of Biological Networks

PubMed Central

Ansari, Sam; Binder, Jean; Boue, Stephanie; Di Fabio, Anselmo; Hayes, William; Hoeng, Julia; Iskandar, Anita; Kleiman, Robin; Norel, Raquel; O’Neel, Bruce; Peitsch, Manuel C.; Poussin, Carine; Pratt, Dexter; Rhrissorrakrai, Kahn; Schlage, Walter K.; Stolovitzky, Gustavo; Talikka, Marja

2013-01-01

Biological networks with a structured syntax are a powerful way of representing biological information generated from high density data; however, they can become unwieldy to manage as their size and complexity increase. This article presents a crowd-verification approach for the visualization and expansion of biological networks. Web-based graphical interfaces allow visualization of causal and correlative biological relationships represented using Biological Expression Language (BEL). Crowdsourcing principles enable participants to communally annotate these relationships based on literature evidences. Gamification principles are incorporated to further engage domain experts throughout biology to gather robust peer-reviewed information from which relationships can be identified and verified. The resulting network models will represent the current status of biological knowledge within the defined boundaries, here processes related to human lung disease. These models are amenable to computational analysis. For some period following conclusion of the challenge, the published models will remain available for continuous use and expansion by the scientific community. PMID:24151423

An instructional design process based on expert knowledge for teaching students how mechanisms are explained.

PubMed

Trujillo, Caleb M; Anderson, Trevor R; Pelaez, Nancy J

2016-06-01

In biology and physiology courses, students face many difficulties when learning to explain mechanisms, a topic that is demanding due to the immense complexity and abstract nature of molecular and cellular mechanisms. To overcome these difficulties, we asked the following question: how does an instructor transform their understanding of biological mechanisms and other difficult-to-learn topics so that students can comprehend them? To address this question, we first reviewed a model of the components used by biologists to explain molecular and cellular mechanisms: the MACH model, with the components of methods (M), analogies (A), context (C), and how (H). Next, instructional materials were developed and the teaching activities were piloted with a physical MACH model. Students who used the MACH model to guide their explanations of mechanisms exhibited both improvements and some new difficulties. Third, a series of design-based research cycles was applied to bring the activities with an improved physical MACH model into biology and biochemistry courses. Finally, a useful rubric was developed to address prevalent student difficulties. Here, we present, for physiology and biology instructors, the knowledge and resources for explaining molecular and cellular mechanisms in undergraduate courses with an instructional design process aimed at realizing pedagogical content knowledge for teaching. Our four-stage process could be adapted to advance instruction with a range of models in the life sciences. Copyright © 2016 The American Physiological Society.

An instructional design process based on expert knowledge for teaching students how mechanisms are explained

PubMed Central

Anderson, Trevor R.; Pelaez, Nancy J.

2016-01-01

In biology and physiology courses, students face many difficulties when learning to explain mechanisms, a topic that is demanding due to the immense complexity and abstract nature of molecular and cellular mechanisms. To overcome these difficulties, we asked the following question: how does an instructor transform their understanding of biological mechanisms and other difficult-to-learn topics so that students can comprehend them? To address this question, we first reviewed a model of the components used by biologists to explain molecular and cellular mechanisms: the MACH model, with the components of methods (M), analogies (A), context (C), and how (H). Next, instructional materials were developed and the teaching activities were piloted with a physical MACH model. Students who used the MACH model to guide their explanations of mechanisms exhibited both improvements and some new difficulties. Third, a series of design-based research cycles was applied to bring the activities with an improved physical MACH model into biology and biochemistry courses. Finally, a useful rubric was developed to address prevalent student difficulties. Here, we present, for physiology and biology instructors, the knowledge and resources for explaining molecular and cellular mechanisms in undergraduate courses with an instructional design process aimed at realizing pedagogical content knowledge for teaching. Our four-stage process could be adapted to advance instruction with a range of models in the life sciences. PMID:27231262

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.

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.

Physics. 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 36 physics investigations found in the student manual. These investigations focus on concepts related to:…

Physics. 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 36 physics investigations which focus on concepts related to: movement; vectors; falling objects; force and acceleration; a…

Chemistry. 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 19 chemistry investigations found in the student manual. These investigations focus on concepts related to:…

Chemistry. 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 19 chemistry investigations. These investigations focus on concepts related to: interactions with water; salt and calcium;…

The Development of Biology Teaching Material Based on the Local Wisdom of Timorese to Improve Students Knowledge and Attitude of Environment in Caring the Preservation of Environment

ERIC Educational Resources Information Center

Ardan, Andam S.

2016-01-01

The purposes of this study were (1) to describe the biology learning such as lesson plans, teaching materials, media and worksheets for the tenth grade of High School on the topic of Biodiversity and Basic Classification, Ecosystems and Environment Issues based on local wisdom of Timorese; (2) to analyze the improvement of the environmental…

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…

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.

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.

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.

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.

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…

Influence of Previous Knowledge, Language Skills and Domain-Specific Interest on Observation Competency

ERIC Educational Resources Information Center

Kohlhauf, Lucia; Rutke, Ulrike; Neuhaus, Birgit

2011-01-01

Many epoch-making biological discoveries (e.g. Darwinian Theory) were based upon observations. Nevertheless, observation is often regarded as "just looking" rather than a basic scientific skill. As observation is one of the main research methods in biological sciences, it must be considered as an independent research method and systematic practice…

In silico model-based inference: a contemporary approach for hypothesis testing in network biology

PubMed Central

Klinke, David J.

2014-01-01

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model-based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900’s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model-based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics. PMID:25139179

In silico model-based inference: a contemporary approach for hypothesis testing in network biology.

PubMed

Klinke, David J

2014-01-01

Inductive inference plays a central role in the study of biological systems where one aims to increase their understanding of the system by reasoning backwards from uncertain observations to identify causal relationships among components of the system. These causal relationships are postulated from prior knowledge as a hypothesis or simply a model. Experiments are designed to test the model. Inferential statistics are used to establish a level of confidence in how well our postulated model explains the acquired data. This iterative process, commonly referred to as the scientific method, either improves our confidence in a model or suggests that we revisit our prior knowledge to develop a new model. Advances in technology impact how we use prior knowledge and data to formulate models of biological networks and how we observe cellular behavior. However, the approach for model-based inference has remained largely unchanged since Fisher, Neyman and Pearson developed the ideas in the early 1900s that gave rise to what is now known as classical statistical hypothesis (model) testing. Here, I will summarize conventional methods for model-based inference and suggest a contemporary approach to aid in our quest to discover how cells dynamically interpret and transmit information for therapeutic aims that integrates ideas drawn from high performance computing, Bayesian statistics, and chemical kinetics. © 2014 American Institute of Chemical Engineers.

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.

On the optimal design of molecular sensing interfaces with lipid bilayer assemblies - A knowledge based approach

NASA Astrophysics Data System (ADS)

Siontorou, Christina G.

2012-12-01

Biosensors are analytic devices that incorporate a biochemical recognition system (biological, biologicalderived or biomimic: enzyme, antibody, DNA, receptor, etc.) in close contact with a physicochemical transducer (electrochemical, optical, piezoelectric, conductimetric, etc.) that converts the biochemical information, produced by the specific biological recognition reaction (analyte-biomolecule binding), into a chemical or physical output signal, related to the concentration of the analyte in the measuring sample. The biosensing concept is based on natural chemoreception mechanisms, which are feasible over/within/by means of a biological membrane, i.e., a structured lipid bilayer, incorporating or attached to proteinaceous moieties that regulate molecular recognition events which trigger ion flux changes (facilitated or passive) through the bilayer. The creation of functional structures that are similar to natural signal transduction systems, correlating and interrelating compatibly and successfully the physicochemical transducer with the lipid film that is self-assembled on its surface while embedding the reconstituted biological recognition system, and at the same time manage to satisfy the basic conditions for measuring device development (simplicity, easy handling, ease of fabrication) is far from trivial. The aim of the present work is to present a methodological framework for designing such molecular sensing interfaces, functioning within a knowledge-based system built on an ontological platform for supplying sub-systems options, compatibilities, and optimization parameters.

Ground-based research with heavy ions for space radiation protection

NASA Astrophysics Data System (ADS)

Durante, M.; Kronenberg, A.

Human exposure to ionizing radiation is one of the acknowledged potential showstoppers for long duration manned interplanetary missions. Human exploratory missions cannot be safely performed without a substantial reduction of the uncertainties associated with different space radiation health risks, and the development of effective countermeasures. Most of our knowledge of the biological effects of heavy charged particles comes from accelerator-based experiments. During the 35th COSPAR meeting, recent ground-based experiments with high-energy iron ions were discussed, and these results are briefly summarised in this paper. High-quality accelerator-based research with heavy ions will continue to be the main source of knowledge of space radiation health effects and will lead to reductions of the uncertainties in predictions of human health risks. Efforts in materials science, nutrition and pharmaceutical sciences and their rigorous evaluation with biological model systems in ground-based accelerator experiments will lead to the development of safe and effective countermeasures to permit human exploration of the Solar System.

Dichotomous Identification Keys: A Ladder to Higher Order Knowledge about the Human Body

ERIC Educational Resources Information Center

Sorgo, Andrej

2006-01-01

We tried to enrich teaching human anatomy in high school biology lessons. Students construct dichotomous identification keys to the cells, tissues, organs, or body parts. By doing this, students have achieved higher-order cognitive levels of knowledge because construction of such keys is based on analysis, synthesis, and evaluation. Students found…

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…

Prior knowledge driven Granger causality analysis on gene regulatory network discovery

DOE PAGES

Yao, Shun; Yoo, Shinjae; Yu, Dantong

2015-08-28

Our study focuses on discovering gene regulatory networks from time series gene expression data using the Granger causality (GC) model. However, the number of available time points (T) usually is much smaller than the number of target genes (n) in biological datasets. The widely applied pairwise GC model (PGC) and other regularization strategies can lead to a significant number of false identifications when n>>T. In this study, we proposed a new method, viz., CGC-2SPR (CGC using two-step prior Ridge regularization) to resolve the problem by incorporating prior biological knowledge about a target gene data set. In our simulation experiments, themore » propose new methodology CGC-2SPR showed significant performance improvement in terms of accuracy over other widely used GC modeling (PGC, Ridge and Lasso) and MI-based (MRNET and ARACNE) methods. In addition, we applied CGC-2SPR to a real biological dataset, i.e., the yeast metabolic cycle, and discovered more true positive edges with CGC-2SPR than with the other existing methods. In our research, we noticed a “ 1+1>2” effect when we combined prior knowledge and gene expression data to discover regulatory networks. Based on causality networks, we made a functional prediction that the Abm1 gene (its functions previously were unknown) might be related to the yeast’s responses to different levels of glucose. In conclusion, our research improves causality modeling by combining heterogeneous knowledge, which is well aligned with the future direction in system biology. Furthermore, we proposed a method of Monte Carlo significance estimation (MCSE) to calculate the edge significances which provide statistical meanings to the discovered causality networks. All of our data and source codes will be available under the link https://bitbucket.org/dtyu/granger-causality/wiki/Home.« less

Effectiveness of false correction strategy on science reading comprehension

NASA Astrophysics Data System (ADS)

Ghent, Cynthia Anne

False-correction reading strategy theoretically prompted college students to activate their prior knowledge when provided false statements linked to a portion of their biology textbook. This strategy is based in elaborative interrogation theory, which suggests that prompting readers to answer interrogatives about text students are reading increases their comprehension of that text. These interrogatives always asked "why" statements pulled from a text, one sentence in length, were "true." True statements in this study based on a text were converted by the experimenter into false statements, one sentence in length. Students were requested to rewrite each statement (n=12) on average every 200 words in a text as they were reading, converting each false statement into a true statement. These students outperformed other students requested to reread the same biology text twice (an established placebo-control strategy). These students, in turn, outperformed still other students reading an unrelated control text taken from the same textbook used only to establish a prior knowledge baseline for all students included in this study. Students participating in this study were enrolled students in an undergraduate introductory general biology course designed for non-majors. A three-group, posttest-only, randomized experimental control-group design was used to prevent pretest activation of students' prior knowledge thus increasing chances of producing evidence of false-correction effectiveness and to begin augmenting potential generalizability to science classrooms. Students' (n=357) general biology knowledge, verbal ability, and attempts to use the false correction strategy were collected and analyzed. Eight of the participants were interviewed by the researcher in a first attempt in this domain to collect data on participants' points of view about the strategy. The results of this study are not yet recommended for use in authentic school settings as further research is indicated.

Supporting High School Student Accomplishment of Biology Content Using Interactive Computer-Based Curricular Case Studies

NASA Astrophysics Data System (ADS)

Oliver, Joseph Steve; Hodges, Georgia W.; Moore, James N.; Cohen, Allan; Jang, Yoonsun; Brown, Scott A.; Kwon, Kyung A.; Jeong, Sophia; Raven, Sara P.; Jurkiewicz, Melissa; Robertson, Tom P.

2017-11-01

Research into the efficacy of modules featuring dynamic visualizations, case studies, and interactive learning environments is reported here. This quasi-experimental 2-year study examined the implementation of three interactive computer-based instructional modules within a curricular unit covering cellular biology concepts in an introductory high school biology course. The modules featured dynamic visualizations and focused on three processes that underlie much of cellular biology: diffusion, osmosis, and filtration. Pre-tests and post-tests were used to assess knowledge growth across the unit. A mixture Rasch model analysis of the post-test data revealed two groups of students. In both years of the study, a large proportion of the students were classified as low-achieving based on their pre-test scores. The use of the modules in the Cell Unit in year 2 was associated with a much larger proportion of the students having transitioned to the high-achieving group than in year 1. In year 2, the same teachers taught the same concepts as year 1 but incorporated the interactive computer-based modules into the cell biology unit of the curriculum. In year 2, 67% of students initially classified as low-achieving were classified as high-achieving at the end of the unit. Examination of responses to assessments embedded within the modules as well as post-test items linked transition to the high-achieving group with correct responses to items that both referenced the visualization and the contextualization of that visualization within the module. This study points to the importance of dynamic visualization within contextualized case studies as a means to support student knowledge acquisition in biology.

Virtual Transgenics: Using a Molecular Biology Simulation to Impact Student Academic Achievement and Attitudes

NASA Astrophysics Data System (ADS)

Shegog, Ross; Lazarus, Melanie M.; Murray, Nancy G.; Diamond, Pamela M.; Sessions, Nathalie; Zsigmond, Eva

2012-10-01

The transgenic mouse model is useful for studying the causes and potential cures for human genetic diseases. Exposing high school biology students to laboratory experience in developing transgenic animal models is logistically prohibitive. Computer-based simulation, however, offers this potential in addition to advantages of fidelity and reach. This study describes and evaluates a computer-based simulation to train advanced placement high school science students in laboratory protocols, a transgenic mouse model was produced. A simulation module on preparing a gene construct in the molecular biology lab was evaluated using a randomized clinical control design with advanced placement high school biology students in Mercedes, Texas ( n = 44). Pre-post tests assessed procedural and declarative knowledge, time on task, attitudes toward computers for learning and towards science careers. Students who used the simulation increased their procedural and declarative knowledge regarding molecular biology compared to those in the control condition (both p < 0.005). Significant increases continued to occur with additional use of the simulation ( p < 0.001). Students in the treatment group became more positive toward using computers for learning ( p < 0.001). The simulation did not significantly affect attitudes toward science in general. Computer simulation of complex transgenic protocols have potential to provide a "virtual" laboratory experience as an adjunct to conventional educational approaches.

Novel approaches to effects-based monitoring: 21st century tools for bio-effects prediction and surveillance

EPA Science Inventory

Effects-based monitoring (EBM) has been employed as a complement to chemical monitoring to help address knowledge gaps between chemical occurrence and biological effects. We have piloted several pathway-based approaches to EBM, that utilize modern bioinformatic and high throughpu...

Gap analysis on the biology of Mediterranean marine fishes

PubMed Central

Dimarchopoulou, Donna; Stergiou, Konstantinos I.

2017-01-01

We estimated the current level of knowledge concerning several biological characteristics of the Mediterranean marine fishes by carrying out a gap analysis based on information extracted from the literature, aiming to identify research trends and future needs in the field of Mediterranean fish biology that can be used in stock assessments, ecosystem modeling and fisheries management. Based on the datasets that emerged from the literature review, there is no information on any biological characteristic for 43% (n = 310) of the Mediterranean fish species, whereas for an additional 15% (n = 109) of them there is information about just one characteristic. The gap between current and desired knowledge (defined here as having information on most biological characteristics for at least half of the Mediterranean marine fishes) is smaller in length-weight relationships, which have been studied for 43% of the species, followed by spawning (39%), diet (29%), growth (25%), maturity (24%), lifespan (19%) and fecundity (17%). The gap is larger in natural mortality for which information is very scarce (8%). European hake (Merluccius merluccius), red mullet (Mullus barbatus), annular seabream (Diplodus annularis), common pandora (Pagellus erythrinus), European anchovy (Engraulis encrasicolus), European pilchard (Sardina pilchardus) and bogue (Boops boops) were the most studied species, while sharks and rays were among the least studied ones. Only 25 species were fully studied, i.e. there was available information on all their biological characteristics. The knowledge gaps per characteristic varied among the western, central and eastern Mediterranean subregions. The number of available records per species was positively related to total landings, while no relationship emerged with its maximum reported length, trophic level and commercial value. Future research priorities that should be focused on less studied species (e.g. sharks and rays) and mortality/fecundity instead of length-weight relationships, as well as the economy of scientific sampling (using the entire catch to acquire data on as many biological characteristics as possible) are discussed. PMID:28407022

Gap analysis on the biology of Mediterranean marine fishes.

PubMed

Dimarchopoulou, Donna; Stergiou, Konstantinos I; Tsikliras, Athanassios C

2017-01-01

We estimated the current level of knowledge concerning several biological characteristics of the Mediterranean marine fishes by carrying out a gap analysis based on information extracted from the literature, aiming to identify research trends and future needs in the field of Mediterranean fish biology that can be used in stock assessments, ecosystem modeling and fisheries management. Based on the datasets that emerged from the literature review, there is no information on any biological characteristic for 43% (n = 310) of the Mediterranean fish species, whereas for an additional 15% (n = 109) of them there is information about just one characteristic. The gap between current and desired knowledge (defined here as having information on most biological characteristics for at least half of the Mediterranean marine fishes) is smaller in length-weight relationships, which have been studied for 43% of the species, followed by spawning (39%), diet (29%), growth (25%), maturity (24%), lifespan (19%) and fecundity (17%). The gap is larger in natural mortality for which information is very scarce (8%). European hake (Merluccius merluccius), red mullet (Mullus barbatus), annular seabream (Diplodus annularis), common pandora (Pagellus erythrinus), European anchovy (Engraulis encrasicolus), European pilchard (Sardina pilchardus) and bogue (Boops boops) were the most studied species, while sharks and rays were among the least studied ones. Only 25 species were fully studied, i.e. there was available information on all their biological characteristics. The knowledge gaps per characteristic varied among the western, central and eastern Mediterranean subregions. The number of available records per species was positively related to total landings, while no relationship emerged with its maximum reported length, trophic level and commercial value. Future research priorities that should be focused on less studied species (e.g. sharks and rays) and mortality/fecundity instead of length-weight relationships, as well as the economy of scientific sampling (using the entire catch to acquire data on as many biological characteristics as possible) are discussed.

An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework.

PubMed

Chen, Yi-An; Tripathi, Lokesh P; Mizuguchi, Kenji

2016-01-01

Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org. © The Author(s) 2016. Published by Oxford University Press.

An integrative data analysis platform for gene set analysis and knowledge discovery in a data warehouse framework

PubMed Central

Chen, Yi-An; Tripathi, Lokesh P.; Mizuguchi, Kenji

2016-01-01

Data analysis is one of the most critical and challenging steps in drug discovery and disease biology. A user-friendly resource to visualize and analyse high-throughput data provides a powerful medium for both experimental and computational biologists to understand vastly different biological data types and obtain a concise, simplified and meaningful output for better knowledge discovery. We have previously developed TargetMine, an integrated data warehouse optimized for target prioritization. Here we describe how upgraded and newly modelled data types in TargetMine can now survey the wider biological and chemical data space, relevant to drug discovery and development. To enhance the scope of TargetMine from target prioritization to broad-based knowledge discovery, we have also developed a new auxiliary toolkit to assist with data analysis and visualization in TargetMine. This toolkit features interactive data analysis tools to query and analyse the biological data compiled within the TargetMine data warehouse. The enhanced system enables users to discover new hypotheses interactively by performing complicated searches with no programming and obtaining the results in an easy to comprehend output format. Database URL: http://targetmine.mizuguchilab.org PMID:26989145

Development and Validation of a Rubric for Diagnosing Students’ Experimental Design Knowledge and Difficulties

PubMed Central

Dasgupta, Annwesa P.; Anderson, Trevor R.

2014-01-01

It is essential to teach students about experimental design, as this facilitates their deeper understanding of how most biological knowledge was generated and gives them tools to perform their own investigations. Despite the importance of this area, surprisingly little is known about what students actually learn from designing biological experiments. In this paper, we describe a rubric for experimental design (RED) that can be used to measure knowledge of and diagnose difficulties with experimental design. The development and validation of the RED was informed by a literature review and empirical analysis of undergraduate biology students’ responses to three published assessments. Five areas of difficulty with experimental design were identified: the variable properties of an experimental subject; the manipulated variables; measurement of outcomes; accounting for variability; and the scope of inference appropriate for experimental findings. Our findings revealed that some difficulties, documented some 50 yr ago, still exist among our undergraduate students, while others remain poorly investigated. The RED shows great promise for diagnosing students’ experimental design knowledge in lecture settings, laboratory courses, research internships, and course-based undergraduate research experiences. It also shows potential for guiding the development and selection of assessment and instructional activities that foster experimental design. PMID:26086658

Semantic memory impairment for biological and man-made objects in individuals with amnestic mild cognitive impairment or late-life depression.

PubMed

Callahan, Brandy L; Joubert, Sven; Tremblay, Marie-Pier; Macoir, Joël; Belleville, Sylvie; Rousseau, François; Bouchard, Rémi W; Verret, Louis; Hudon, Carol

2015-06-01

Amnestic mild cognitive impairment (aMCI) and late-life depression (LLD) both increase the risk of developing Alzheimer disease (AD). Very little is known about the similarities and differences between these syndromes. The present study addresses this issue by examining the nature of semantic memory impairment (more precisely, object-based knowledge) in patients at risk of developing AD. Participants were 17 elderly patients with aMCI, 18 patients with aMCI plus depressive symptoms (aMCI/D+), 15 patients with LLD, and 29 healthy controls. All participants were aged 55 years or older and were administered a semantic battery designed to assess semantic knowledge for 16 biological and 16 man-made items. Overall performance of aMCI/D+ participants was significantly worse than the 3 other groups, and performance for questions assessing knowledge for biological items was poorer than for questions relating to man-made items. This study is the first to show that aMCI/D+ is associated with object-based semantic memory impairment. These results support the view that semantic deficits in aMCI are associated with concomitant depressive symptoms. However, depressive symptoms alone do not account exclusively for semantic impairment, since patients with LLD showed no semantic memory deficit. © The Author(s) 2014.

Developing Year 2 Students' Theory of Biology with Concepts of the Gene and DNA

ERIC Educational Resources Information Center

Venville, Grady; Donovan, Jenny

2007-01-01

This paper presents a case study of a teaching intervention designed to enrich Year 2 students' theory of biology through the introduction of causal mechanisms of inheritance such as the gene and DNA. The researchers worked collaboratively with the classroom teacher to design the intervention based on the students' prior knowledge of living things…

Collaboratively charting the gene-to-phenotype network of human congenital heart defects

PubMed Central

2010-01-01

Background How to efficiently integrate the daily practice of molecular biologists, geneticists, and clinicians with the emerging computational strategies from systems biology is still much of an open question. Description We built on the recent advances in Wiki-based technologies to develop a collaborative knowledge base and gene prioritization portal aimed at mapping genes and genomic regions, and untangling their relations with corresponding human phenotypes, congenital heart defects (CHDs). This portal is not only an evolving community repository of current knowledge on the genetic basis of CHDs, but also a collaborative environment for the study of candidate genes potentially implicated in CHDs - in particular by integrating recent strategies for the statistical prioritization of candidate genes. It thus serves and connects the broad community that is facing CHDs, ranging from the pediatric cardiologist and clinical geneticist to the basic investigator of cardiogenesis. Conclusions This study describes the first specialized portal to collaboratively annotate and analyze gene-phenotype networks. Of broad interest to the biological community, we argue that such portals will play a significant role in systems biology studies of numerous complex biological processes. CHDWiki is accessible at http://www.esat.kuleuven.be/~bioiuser/chdwiki PMID:20193066

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.

Habitat classification modeling with incomplete data: Pushing the habitat envelope

USGS Publications Warehouse

Zarnetske, P.L.; Edwards, T.C.; Moisen, Gretchen G.

2007-01-01

Habitat classification models (HCMs) are invaluable tools for species conservation, land-use planning, reserve design, and metapopulation assessments, particularly at broad spatial scales. However, species occurrence data are often lacking and typically limited to presence points at broad scales. This lack of absence data precludes the use of many statistical techniques for HCMs. One option is to generate pseudo-absence points so that the many available statistical modeling tools can be used. Traditional techniques generate pseudoabsence points at random across broadly defined species ranges, often failing to include biological knowledge concerning the species-habitat relationship. We incorporated biological knowledge of the species-habitat relationship into pseudo-absence points by creating habitat envelopes that constrain the region from which points were randomly selected. We define a habitat envelope as an ecological representation of a species, or species feature's (e.g., nest) observed distribution (i.e., realized niche) based on a single attribute, or the spatial intersection of multiple attributes. We created HCMs for Northern Goshawk (Accipiter gentilis atricapillus) nest habitat during the breeding season across Utah forests with extant nest presence points and ecologically based pseudo-absence points using logistic regression. Predictor variables were derived from 30-m USDA Landfire and 250-m Forest Inventory and Analysis (FIA) map products. These habitat-envelope-based models were then compared to null envelope models which use traditional practices for generating pseudo-absences. Models were assessed for fit and predictive capability using metrics such as kappa, thresholdindependent receiver operating characteristic (ROC) plots, adjusted deviance (Dadj2), and cross-validation, and were also assessed for ecological relevance. For all cases, habitat envelope-based models outperformed null envelope models and were more ecologically relevant, suggesting that incorporating biological knowledge into pseudo-absence point generation is a powerful tool for species habitat assessments. Furthermore, given some a priori knowledge of the species-habitat relationship, ecologically based pseudo-absence points can be applied to any species, ecosystem, data resolution, and spatial extent. ?? 2007 by the Ecological Society of America.

Knowledge, Awareness and Attitude on HPV, HPV Vaccine and Cervical Cancer among the College Students in India

PubMed Central

Rashid, Shazia; Labani, Satyanarayana; Das, Bhudev C.

2016-01-01

Background Infection of specific high risk Human papillomaviruses (HPVs) is known to cause cervical cancer and two prophylactic vaccines have been developed against two major high risk HPV types 16 and 18 for prevention of cervical cancer. Because of societal, religious and ethical issues associated with the vaccination of adolescent girls in India together with lack of awareness about HPV and HPV vaccines, no successful HPV immunization program has been employed in India. Objective To determine knowledge, awareness and attitude of college students on HPV, HPV vaccine and cervical cancer. Method A questionnaire-based survey was conducted in a total of 1580 undergraduate students between the age group 16–26 years comprising 684 girls and 876 boys. Results Out of a total of 1580 students, girls had more knowledge about cervical cancer (82.45%, p<0.001), HPV (45.61%, p<0.001) and HPV vaccines (44%, p<0.001) when compared to those in boys. However, knowledge about the types of HPV and vaccines was poor. Interestingly, students from biology-major had more knowledge and awareness about cervical cancer (81.89%, p<0.001) and HPV (46.58%, <0.001) when compared to non-biology students. Girls from both biology and non-biology group had higher awareness compared to boys. Analysis of odds ratio (ORs) along with 95% CI showed older girls with 1.2 to 3 fold (p<0.05) higher knowledge than boys. All students agreed that girls should get vaccinated against HPV (p<0.001). Conclusion It is suggested that there is a need for educational intervention and awareness campaigns to augment HPV immunization program for control of cervical cancer in India. PMID:27861611

Knowledge, Awareness and Attitude on HPV, HPV Vaccine and Cervical Cancer among the College Students in India.

PubMed

Rashid, Shazia; Labani, Satyanarayana; Das, Bhudev C

2016-01-01

Infection of specific high risk Human papillomaviruses (HPVs) is known to cause cervical cancer and two prophylactic vaccines have been developed against two major high risk HPV types 16 and 18 for prevention of cervical cancer. Because of societal, religious and ethical issues associated with the vaccination of adolescent girls in India together with lack of awareness about HPV and HPV vaccines, no successful HPV immunization program has been employed in India. To determine knowledge, awareness and attitude of college students on HPV, HPV vaccine and cervical cancer. A questionnaire-based survey was conducted in a total of 1580 undergraduate students between the age group 16-26 years comprising 684 girls and 876 boys. Out of a total of 1580 students, girls had more knowledge about cervical cancer (82.45%, p<0.001), HPV (45.61%, p<0.001) and HPV vaccines (44%, p<0.001) when compared to those in boys. However, knowledge about the types of HPV and vaccines was poor. Interestingly, students from biology-major had more knowledge and awareness about cervical cancer (81.89%, p<0.001) and HPV (46.58%, <0.001) when compared to non-biology students. Girls from both biology and non-biology group had higher awareness compared to boys. Analysis of odds ratio (ORs) along with 95% CI showed older girls with 1.2 to 3 fold (p<0.05) higher knowledge than boys. All students agreed that girls should get vaccinated against HPV (p<0.001). It is suggested that there is a need for educational intervention and awareness campaigns to augment HPV immunization program for control of cervical cancer in India.

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…

Transforming schools into communities of thinking and learning about serious matters.

PubMed

Brown, A L

1997-04-01

In this article, a program of research known as Fostering Communities of Learners is described. This program is in place in several schools and classrooms serving inner-city students from 6 to 12 years of age. Based on theoretical advances in cognitive and developmental psychology, the program is successful at improving both literacy skills and domain-area subject matter knowledge (e.g., environmental science and biology). Building on young children's emergent strategic and metacognitive knowledge, together with their skeletal biological theories, the program leads children to discover the deep principles of the domain and to develop flexible learning and inquiry strategies of wide applicability.

Microarray missing data imputation based on a set theoretic framework and biological knowledge.

PubMed

Gan, Xiangchao; Liew, Alan Wee-Chung; Yan, Hong

2006-01-01

Gene expressions measured using microarrays usually suffer from the missing value problem. However, in many data analysis methods, a complete data matrix is required. Although existing missing value imputation algorithms have shown good performance to deal with missing values, they also have their limitations. For example, some algorithms have good performance only when strong local correlation exists in data while some provide the best estimate when data is dominated by global structure. In addition, these algorithms do not take into account any biological constraint in their imputation. In this paper, we propose a set theoretic framework based on projection onto convex sets (POCS) for missing data imputation. POCS allows us to incorporate different types of a priori knowledge about missing values into the estimation process. The main idea of POCS is to formulate every piece of prior knowledge into a corresponding convex set and then use a convergence-guaranteed iterative procedure to obtain a solution in the intersection of all these sets. In this work, we design several convex sets, taking into consideration the biological characteristic of the data: the first set mainly exploit the local correlation structure among genes in microarray data, while the second set captures the global correlation structure among arrays. The third set (actually a series of sets) exploits the biological phenomenon of synchronization loss in microarray experiments. In cyclic systems, synchronization loss is a common phenomenon and we construct a series of sets based on this phenomenon for our POCS imputation algorithm. Experiments show that our algorithm can achieve a significant reduction of error compared to the KNNimpute, SVDimpute and LSimpute methods.

Biologically Inspired Model for Visual Cognition Achieving Unsupervised Episodic and Semantic Feature Learning.

PubMed

Qiao, Hong; Li, Yinlin; Li, Fengfu; Xi, Xuanyang; Wu, Wei

2016-10-01

Recently, many biologically inspired visual computational models have been proposed. The design of these models follows the related biological mechanisms and structures, and these models provide new solutions for visual recognition tasks. In this paper, based on the recent biological evidence, we propose a framework to mimic the active and dynamic learning and recognition process of the primate visual cortex. From principle point of view, the main contributions are that the framework can achieve unsupervised learning of episodic features (including key components and their spatial relations) and semantic features (semantic descriptions of the key components), which support higher level cognition of an object. From performance point of view, the advantages of the framework are as follows: 1) learning episodic features without supervision-for a class of objects without a prior knowledge, the key components, their spatial relations and cover regions can be learned automatically through a deep neural network (DNN); 2) learning semantic features based on episodic features-within the cover regions of the key components, the semantic geometrical values of these components can be computed based on contour detection; 3) forming the general knowledge of a class of objects-the general knowledge of a class of objects can be formed, mainly including the key components, their spatial relations and average semantic values, which is a concise description of the class; and 4) achieving higher level cognition and dynamic updating-for a test image, the model can achieve classification and subclass semantic descriptions. And the test samples with high confidence are selected to dynamically update the whole model. Experiments are conducted on face images, and a good performance is achieved in each layer of the DNN and the semantic description learning process. Furthermore, the model can be generalized to recognition tasks of other objects with learning ability.

What Happens to the Food We Eat? Children's Conceptions of the Structure and Function of the Digestive System.

ERIC Educational Resources Information Center

Teixeira, Francimar Martins

2000-01-01

Describes children's conceptions of the structure and function of the human digestive system based on an investigation carried out with children aged 4-10 (n=45). Finds that children possess biological knowledge as an independent knowledge domain from the age of four. Discusses acquisition of and barriers to scientific concepts related to human…

Secondary School Students' and Their Parents' Knowledge and Interest in Crop Plants: Why Should We Care?

ERIC Educational Resources Information Center

Fritsch, Eva-Maria; Dreesmann, Daniel C.

2015-01-01

While there is increasing world-wide discussion of the importance of renewable biological resources and a bio-based economy, science educators around the world have become aware of a declining general interest in plants and agriculture and of little knowledge of plants among the public. Recently, there have been few systematic investigations on…

"Sharks in Your Hands"--A Case Study on Effects of Teaching Strategies to Change Knowledge and Attitudes towards Sharks

ERIC Educational Resources Information Center

Lee, Hung-Shan; Liu, Shiang-Yao; Yeh, Ting-Kuang

2016-01-01

This study was designed to exemplify how hands-on based teaching strategies enhanced students' knowledge and positive attitudes towards sharks. Hands-on activities for sharks' biological and morphological features were carried out. Eleven elementary school students from a remote area in Taiwan were recruited and assigned to the hands-on condition.…

Recommendation Techniques for Drug-Target Interaction Prediction and Drug Repositioning.

PubMed

Alaimo, Salvatore; Giugno, Rosalba; Pulvirenti, Alfredo

2016-01-01

The usage of computational methods in drug discovery is a common practice. More recently, by exploiting the wealth of biological knowledge bases, a novel approach called drug repositioning has raised. Several computational methods are available, and these try to make a high-level integration of all the knowledge in order to discover unknown mechanisms. In this chapter, we review drug-target interaction prediction methods based on a recommendation system. We also give some extensions which go beyond the bipartite network case.

Modeling science: Supporting a more authentic epistemology of science

NASA Astrophysics Data System (ADS)

Svoboda, Julia Marie

In this dissertation I argue that model-based inquiry has the potential to create experiences for students to consider how scientific knowledge is generated and evaluated - that is, for students to consider the epistemology of science. I also argue that such epistemically rich experiences can lead to shifts in students' conceptions of the nature of scientific knowledge. The context of this work is a yearlong biological modeling traineeship for undergraduate mathematics and biology majors called Collaborative Learning at the Interface of Mathematics and Biology (CLIMB). I used an ethnographically-based approach to collect detailed field notes, video, documents and interviews with faculty and students in CLIMB. The resulting dataset provides a rich description of the CLIMB program as well as students experiences in this program. Analysis of the CLIMB curriculum revealed that the degree to which students were treated as independent scholars and challenged with authentic problems influenced the productivity of their activity. A more detailed analysis of the nature of modeling tasks revealed that only when models were at the center of their activity did students have opportunities to consider epistemic themes relating to how knowledge is created and critiqued in science. Finally, a case study that followed a single student described how rich epistemically rich experiences with modeling have the potential to shift the ways in which students conceive of scientific knowledge and practice. It also provided evidence that supports the theory that students have complex multidimensional epistemic ecologies as opposed to static views about science. As a whole, this dissertation provides a rich description of how model-based inquiry can support learning about the epistemology of science and suggests that scientific modeling should have a more central role in science education.

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…

Reverse engineering systems models of regulation: discovery, prediction and mechanisms.

PubMed

Ashworth, Justin; Wurtmann, Elisabeth J; Baliga, Nitin S

2012-08-01

Biological systems can now be understood in comprehensive and quantitative detail using systems biology approaches. Putative genome-scale models can be built rapidly based upon biological inventories and strategic system-wide molecular measurements. Current models combine statistical associations, causative abstractions, and known molecular mechanisms to explain and predict quantitative and complex phenotypes. This top-down 'reverse engineering' approach generates useful organism-scale models despite noise and incompleteness in data and knowledge. Here we review and discuss the reverse engineering of biological systems using top-down data-driven approaches, in order to improve discovery, hypothesis generation, and the inference of biological properties. Copyright © 2011 Elsevier Ltd. All rights reserved.

Development and Validation of a Rubric for Diagnosing Students' Experimental Design Knowledge and Difficulties.

PubMed

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

2014-01-01

It is essential to teach students about experimental design, as this facilitates their deeper understanding of how most biological knowledge was generated and gives them tools to perform their own investigations. Despite the importance of this area, surprisingly little is known about what students actually learn from designing biological experiments. In this paper, we describe a rubric for experimental design (RED) that can be used to measure knowledge of and diagnose difficulties with experimental design. The development and validation of the RED was informed by a literature review and empirical analysis of undergraduate biology students' responses to three published assessments. Five areas of difficulty with experimental design were identified: the variable properties of an experimental subject; the manipulated variables; measurement of outcomes; accounting for variability; and the scope of inference appropriate for experimental findings. Our findings revealed that some difficulties, documented some 50 yr ago, still exist among our undergraduate students, while others remain poorly investigated. The RED shows great promise for diagnosing students' experimental design knowledge in lecture settings, laboratory courses, research internships, and course-based undergraduate research experiences. It also shows potential for guiding the development and selection of assessment and instructional activities that foster experimental design. © 2014 A. P. Dasgupta et al. 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).

Learning disease relationships from clinical drug trials.

PubMed

Haslam, Bryan; Perez-Breva, Luis

2017-01-01

Our objective is to test the limits of the assumption that better learning from data in medicine requires more granular data. We hypothesize that clinical trial metadata contains latent scientific, clinical, and regulatory expert knowledge that can be accessed to draw conclusions about the underlying biology of diseases. We seek to demonstrate that this latent information can be uncovered from the whole body of clinical trials. We extract free-text metadata from 93 654 clinical drug trials and introduce a representation that allows us to compare different trials. We then construct a network of diseases using only the trial metadata. We view each trial as the summation of expert knowledge of biological mechanisms and medical evidence linking a disease to a drug believed to modulate the pathways of that disease. Our network representation allows us to visualize disease relationships based on this underlying information. Our disease network shows surprising agreement with another disease network based on genetic data and on the Medical Subject Headings (MeSH) taxonomy, yet also contains unique disease similarities. The agreement of our results with other sources indicates that our premise regarding latent expert knowledge holds. The disease relationships unique to our network may be used to generate hypotheses for future biological and clinical research as well as drug repurposing and design. Our results provide an example of using experimental data on humans to generate biologically useful information and point to a set of new and promising strategies to link clinical outcomes data back to biological research. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Semantics-enabled service discovery framework in the SIMDAT pharma grid.

PubMed

Qu, Cangtao; Zimmermann, Falk; Kumpf, Kai; Kamuzinzi, Richard; Ledent, Valérie; Herzog, Robert

2008-03-01

We present the design and implementation of a semantics-enabled service discovery framework in the data Grids for process and product development using numerical simulation and knowledge discovery (SIMDAT) Pharma Grid, an industry-oriented Grid environment for integrating thousands of Grid-enabled biological data services and analysis services. The framework consists of three major components: the Web ontology language (OWL)-description logic (DL)-based biological domain ontology, OWL Web service ontology (OWL-S)-based service annotation, and semantic matchmaker based on the ontology reasoning. Built upon the framework, workflow technologies are extensively exploited in the SIMDAT to assist biologists in (semi)automatically performing in silico experiments. We present a typical usage scenario through the case study of a biological workflow: IXodus.

Effectiveness of a Constructivist-Based Science Camp for Gifted Secondary Students

ERIC Educational Resources Information Center

Wilson, Hope E.; Zoellner, Brian

2016-01-01

Constructivist-based pedagogy is particularly applicable to gifted secondary students in the sciences due to the increased background knowledge of the population and the nature of the study of science. This research was an investigation of the effectiveness of a residential constructivist-based summer learning experience in aquatic biology and…

Bedform development and morphodynamics in mixed cohesive sediment substrates: the importance of winnowing and flocculation

NASA Astrophysics Data System (ADS)

Ye, Leiping; Parsons, Daniel; Manning, Andrew

2016-04-01

There remains a lack of process-based knowledge of sediment dynamics within flows over bedforms generated in complex mixtures of cohesionless sand and biologically-active cohesive muds in natural estuarine flow systems. The work to be presented forms a part of the UK NERC "COHesive BEDforms (COHBED)" project which aims to fill this gap in knowledge. Herein results from a field survey in sub-tidal zone of Dee estuary (NW, England) and a set of large-scale laboratory experiments, conducted using mixtures of non-cohesive sands, cohesive muds and Xanthan gum (as a proxy for the biological stickiness of Extracellular Polymeric Substances (EPS)) will be presented. The results indicate the significance of biological-active cohesive sediments in controlling winnowing rates and flocculation dynamics, which contributes significantly to rates of bedform evolution.

Enzyme Biosensors for Biomedical Applications: Strategies for Safeguarding Analytical Performances in Biological Fluids

PubMed Central

Rocchitta, Gaia; Spanu, Angela; Babudieri, Sergio; Latte, Gavinella; Madeddu, Giordano; Galleri, Grazia; Nuvoli, Susanna; Bagella, Paola; Demartis, Maria Ilaria; Fiore, Vito; Manetti, Roberto; Serra, Pier Andrea

2016-01-01

Enzyme-based chemical biosensors are based on biological recognition. In order to operate, the enzymes must be available to catalyze a specific biochemical reaction and be stable under the normal operating conditions of the biosensor. Design of biosensors is based on knowledge about the target analyte, as well as the complexity of the matrix in which the analyte has to be quantified. This article reviews the problems resulting from the interaction of enzyme-based amperometric biosensors with complex biological matrices containing the target analyte(s). One of the most challenging disadvantages of amperometric enzyme-based biosensor detection is signal reduction from fouling agents and interference from chemicals present in the sample matrix. This article, therefore, investigates the principles of functioning of enzymatic biosensors, their analytical performance over time and the strategies used to optimize their performance. Moreover, the composition of biological fluids as a function of their interaction with biosensing will be presented. PMID:27249001

The Importance of Conducting Life Sciences Experiments on the Deep Space Gateway Platform

NASA Technical Reports Server (NTRS)

Bhattacharya, S.

2018-01-01

Over the last several decades important information has been gathered by conducting life science experiments on the Space Shuttle and on the International Space Station. It is now time to leverage that scientific knowledge, as well as aspects of the hardware that have been developed to support the biological model systems, to NASA's next frontier - the Deep Space Gateway. In order to facilitate long duration deep space exploration for humans, it is critical for NASA to understand the effects of long duration, low dose, deep space radiation on biological systems. While carefully controlled ground experiments on Earth-based radiation facilities have provided valuable preliminary information, we still have a significant knowledge gap on the biological responses of organisms to chronic low doses of the highly ionizing particles encountered beyond low Earth orbit. Furthermore, the combined effects of altered gravity and radiation have the potential to cause greater biological changes than either of these parameters alone. Therefore a thorough investigation of the biological effects of a cis-lunar environment will facilitate long term human exploration of deep space.

Emerging evidence for CHFR as a cancer biomarker: from tumor biology to precision medicine.

PubMed

Derks, Sarah; Cleven, Arjen H G; Melotte, Veerle; Smits, Kim M; Brandes, Johann C; Azad, Nilofer; van Criekinge, Wim; de Bruïne, Adriaan P; Herman, James G; van Engeland, Manon

2014-03-01

Novel insights in the biology of cancer have switched the paradigm of a "one-size-fits-all" cancer treatment to an individualized biology-driven treatment approach. In recent years, a diversity of biomarkers and targeted therapies has been discovered. Although these examples accentuate the promise of personalized cancer treatment, for most cancers and cancer subgroups no biomarkers and effective targeted therapy are available. The great majority of patients still receive unselected standard therapies with no use of their individual molecular characteristics. Better knowledge about the underlying tumor biology will lead the way toward personalized cancer treatment. In this review, we summarize the evidence for a promising cancer biomarker: checkpoint with forkhead and ring finger domains (CHFR). CHFR is a mitotic checkpoint and tumor suppressor gene, which is inactivated in a diverse group of solid malignancies, mostly by promoter CpG island methylation. CHFR inactivation has shown to be an indicator of poor prognosis and sensitivity to taxane-based chemotherapy. Here we summarize the current knowledge of altered CHFR expression in cancer, the impact on tumor biology and implications for personalized cancer treatment.

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

PubMed Central

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh; Webb-Robertson, Bobbie-Jo; Hafen, Ryan; Ramey, John; Rodland, Karin D.

2012-01-01

Introduction The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful molecular signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities for more sophisticated approaches to integrating purely statistical and expert knowledge-based approaches. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges that have been encountered in deriving valid and useful signatures of disease. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to identify predictive signatures of disease are key to future success in the biomarker field. We will describe our recommendations for possible approaches to this problem including metrics for the evaluation of biomarkers. PMID:23335946

Challenges in Biomarker Discovery: Combining Expert Insights with Statistical Analysis of Complex Omics Data

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

McDermott, Jason E.; Wang, Jing; Mitchell, Hugh D.

2013-01-01

The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities both for purely statistical and expert knowledge-based approaches and would benefit from improved integration of the two. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges thatmore » have been encountered. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to biomarker discovery and characterization are key to future success in the biomarker field. We will describe our recommendations of possible approaches to this problem including metrics for the evaluation of biomarkers.« less

Biological diversity, dietary diversity, and eye health in developing country populations: establishing the evidence-base.

PubMed

Bélanger, Julie; Johns, Timothy

2008-09-01

Human and ecosystem health converge around biological diversity issues. Cultivated and wild plants as food and medicine make essential contributions to human health, which in turn provides rationales for conservation. While wild and cultivated plant diversity reasonably facilitates dietary diversity and positive health outcomes, the challenges of demonstrating this relationship limit its impact in concept, policy, and practice. We present a rationale for testing the dietary contribution of biological diversity to improved eye health as a case study based on existing phytochemical, pharmacological, and clinical knowledge. We consider the empirical evidence needed to substantiate, interpret, and apply this relationship at a population and ecosystem level within a unified research framework. Epidemiological data strongly support the prevention of childhood vitamin A deficiency blindness, cataract, and age-related macular degeneration by fruit and vegetable consumption. Phytonutrients, including the carotenoids lutein and zeaxanthin, protect the eye from oxidative stress and harmful light exposure. Laboratory, community, and population level research should prioritize food composition of dietary plants from both agriculture and the wild. Intervention studies, focus groups, and transmission of knowledge of local species and varieties within communities will further interpretation of epidemiological data. Population-based studies combining clinical data and measures of access and consumption of biological diversity are key to demonstrating the important relationships among biodiversity, dietary diversity, and health outcomes.

[Polish forensic entomology--the past, present and future perspectives].

PubMed

Skowronek, Rafał; Chowaniec, Czesław

2010-01-01

Forensic medicine increasingly more often benefits from the achievements of other biological sciences, which may be used in post mortem investigation. One of them is forensic entomology--the science based on the knowledge about biology of insects preying on cadavers. The objective of this article is to present the history of Polish forensic entomology, its present state and possibilities and directions of further development.

Learner-Centered Inquiry in Undergraduate Biology: Positive Relationships with Long-Term Student Achievement

PubMed Central

Ebert-May, Diane

2010-01-01

We determined short- and long-term correlates of a revised introductory biology curriculum on understanding of biology as a process of inquiry and learning of content. In the original curriculum students completed two traditional lecture-based introductory courses. In the revised curriculum students completed two new learner-centered, inquiry-based courses. The new courses differed significantly from those of the original curriculum through emphases on critical thinking, collaborative work, and/or inquiry-based activities. Assessments were administered to compare student understanding of the process of biological science and content knowledge in the two curricula. More seniors who completed the revised curriculum had high-level profiles on the Views About Science Survey for Biology compared with seniors who completed the original curriculum. Also as seniors, students who completed the revised curriculum scored higher on the standardized Biology Field Test. Our results showed that an intense inquiry-based learner-centered learning experience early in the biology curriculum was associated with long-term improvements in learning. We propose that students learned to learn science in the new courses which, in turn, influenced their learning in subsequent courses. Studies that determine causal effects of learner-centered inquiry-based approaches, rather than correlative relationships, are needed to test our proposed explanation. PMID:21123693

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

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…

Effectiveness of Biologic Factors in Shoulder Disorders

PubMed Central

Giotis, Dimitrios; Aryaei, Ashkan; Vasilakakos, Theofanis; Paschos, Nikolaos K.

2017-01-01

Background: Shoulder pathology can cause significant pain, discomfort, and loss of function that all interfere with activities of daily living and may lead to poor quality of life. Primary osteoarthritis and rotator cuff diseases with its sequalae are the main culprits. Management of shoulder disorders using biological factors gained an increasing interest over the last years. This interest reveals the need of effective treatments for shoulder degenerative disorders, and highlights the importance of a comprehensive and detailed understanding of the rapidly increasing knowledge in the field. Methods: This study will describe most of the available biology-based strategies that have been recently developed, focusing on their effectiveness in animal and clinical studies. Results: Data from in vitro work will also be briefly presented; in order to further elucidate newly acquired knowledge regarding mechanisms of tissue degeneration and repair that would probably drive translational work in the next decade. The role of platelet rich-plasma, growth factors, stem cells and other alternative treatments will be described in an evidence-based approach, in an attempt to provide guidelines for their clinical application. Finally, certain challenges that biologic treatments face today will be described as an initiative for future strategies. Conclusion: The application of different growth factors and mesenchymal stem cells appears as promising approaches for enhancing biologic repair. However, data from clinical studies are still limited, and future studies need to improve understanding of the repair process in cellular and molecular level and evaluate the effectiveness of biologic factors in the management of shoulder disorders. PMID:28400884

Alcohol Pharmacology Education Partnership: Using Chemistry and Biology Concepts To Educate High School Students about Alcohol

PubMed Central

2015-01-01

We developed the Alcohol Pharmacology Education Partnership (APEP), a set of modules designed to integrate a topic of interest (alcohol) with concepts in chemistry and biology for high school students. Chemistry and biology teachers (n = 156) were recruited nationally to field-test APEP in a controlled study. Teachers obtained professional development either at a conference-based workshop (NSTA or NCSTA) or via distance learning to learn how to incorporate the APEP modules into their teaching. They field-tested the modules in their classes during the following year. Teacher knowledge of chemistry and biology concepts increased significantly following professional development, and was maintained for at least a year. Their students (n = 14 014) demonstrated significantly higher scores when assessed for knowledge of both basic and advanced chemistry and biology concepts compared to students not using APEP modules in their classes the previous year. Higher scores were achieved as the number of modules used increased. These findings are consistent with our previous studies, demonstrating higher scores in chemistry and biology after students use modules that integrate topics interesting to them, such as drugs (the Pharmacology Education Partnership). PMID:24803686

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

[Students in Training to Become Biology Teachers - a controlled phase II trial (NCT01567267)].

PubMed

Matic-Strametz, Mirjana; Strametz, Reinhard; Bohrt, Kevin; Ochsendorf, Falk; Weberschock, Tobias

2013-01-01

Consumers increasingly demand to take part in healthcare decisions as described by the concept of shared decision making. In order to ensure this happens the patient must be able to critically appraise the healthcare information provided, which is called critical health literacy. Critical health literacy can be taught to patients at the onset of their disease to enable them to obtain information about interventions and alternatives. For the primary prevention of common diseases like hypertension or diabetes mellitus, though, it is necessary to empower consumers to critically appraise medical information since this information is routinely presented in the mass media. This might be achieved through educational intervention programmes at school. The study was designed as a prospective controlled trial with students in training to become biology teachers at Siegen University (Germany). The intervention group received a short-term educational intervention (24 units) in human biology based on the principles of Evidence-based Medicine (EbM) and Good Scientific Practice (GSP) combined with elements of problem-based learning. The control group received a short-term intervention in human biology of equal duration, but without the elements of EbM and GSP. Knowledge and skills were evaluated by validated questionnaires and case studies in a pre-, interim, and post-interventional test in both groups. In addition, biology trainee teachers in the intervention group also planned and conducted a one-hour problem-based learning session with high school students, which was evaluated by video. The increase in knowledge (7.9±3.8 points vs. 2.7±2.5 points, p≤0.001) and appraisal skills (24.1±6.7 points vs. 14.6±6.3, p≤0.001) after the intervention was relevant and significant compared to baseline results and also compared to the control group that did not show any significant progress in knowledge (3.9±2.4 points vs. 2.7±1.7) and appraisal skills (16.2±5.9 points vs. 14.4±5.6). All the participants in the intervention group passed both the preparation and the conduction of their problem-based learning session with high school students with at least 50 % of the maximum number of points. Satisfaction among students in training to become biology teachers (median grade of 2 [good] in the German grading system) and students (89 % of students agreed this to be an interesting method) were high in the intervention group. This preliminary study showed a relevant increase in knowledge about EbM and skills in critically appraising interventional studies. Participating students were able to conduct problem-based learning sessions for high school students about the principles of EbM and GSP. The results justify a larger randomised controlled trial to evaluate both effects and applicability to different school settings. Copyright © 2012. Published by Elsevier GmbH.

Strategic Integration of Multiple Bioinformatics Resources for System Level Analysis of Biological Networks.

PubMed

D'Souza, Mark; Sulakhe, Dinanath; Wang, Sheng; Xie, Bing; Hashemifar, Somaye; Taylor, Andrew; Dubchak, Inna; Conrad Gilliam, T; Maltsev, Natalia

2017-01-01

Recent technological advances in genomics allow the production of biological data at unprecedented tera- and petabyte scales. Efficient mining of these vast and complex datasets for the needs of biomedical research critically depends on a seamless integration of the clinical, genomic, and experimental information with prior knowledge about genotype-phenotype relationships. Such experimental data accumulated in publicly available databases should be accessible to a variety of algorithms and analytical pipelines that drive computational analysis and data mining.We present an integrated computational platform Lynx (Sulakhe et al., Nucleic Acids Res 44:D882-D887, 2016) ( http://lynx.cri.uchicago.edu ), a web-based database and knowledge extraction engine. It provides advanced search capabilities and a variety of algorithms for enrichment analysis and network-based gene prioritization. It gives public access to the Lynx integrated knowledge base (LynxKB) and its analytical tools via user-friendly web services and interfaces. The Lynx service-oriented architecture supports annotation and analysis of high-throughput experimental data. Lynx tools assist the user in extracting meaningful knowledge from LynxKB and experimental data, and in the generation of weighted hypotheses regarding the genes and molecular mechanisms contributing to human phenotypes or conditions of interest. The goal of this integrated platform is to support the end-to-end analytical needs of various translational projects.

A knowledge-driven probabilistic framework for the prediction of protein-protein interaction networks.

PubMed

Browne, Fiona; Wang, Haiying; Zheng, Huiru; Azuaje, Francisco

2010-03-01

This study applied a knowledge-driven data integration framework for the inference of protein-protein interactions (PPI). Evidence from diverse genomic features is integrated using a knowledge-driven Bayesian network (KD-BN). Receiver operating characteristic (ROC) curves may not be the optimal assessment method to evaluate a classifier's performance in PPI prediction as the majority of the area under the curve (AUC) may not represent biologically meaningful results. It may be of benefit to interpret the AUC of a partial ROC curve whereby biologically interesting results are represented. Therefore, the novel application of the assessment method referred to as the partial ROC has been employed in this study to assess predictive performance of PPI predictions along with calculating the True positive/false positive rate and true positive/positive rate. By incorporating domain knowledge into the construction of the KD-BN, we demonstrate improvement in predictive performance compared with previous studies based upon the Naive Bayesian approach. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

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.

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

NASA Astrophysics Data System (ADS)

Mirel, Barbara; Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-02-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students' visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students' successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules.

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

PubMed Central

Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-01-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students’ visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students’ successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules. PMID:26877625

A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data.

PubMed

Kang, Tianyu; Ding, Wei; Zhang, Luoyan; Ziemek, Daniel; Zarringhalam, Kourosh

2017-12-19

Stratification of patient subpopulations that respond favorably to treatment or experience and adverse reaction is an essential step toward development of new personalized therapies and diagnostics. It is currently feasible to generate omic-scale biological measurements for all patients in a study, providing an opportunity for machine learning models to identify molecular markers for disease diagnosis and progression. However, the high variability of genetic background in human populations hampers the reproducibility of omic-scale markers. In this paper, we develop a biological network-based regularized artificial neural network model for prediction of phenotype from transcriptomic measurements in clinical trials. To improve model sparsity and the overall reproducibility of the model, we incorporate regularization for simultaneous shrinkage of gene sets based on active upstream regulatory mechanisms into the model. We benchmark our method against various regression, support vector machines and artificial neural network models and demonstrate the ability of our method in predicting the clinical outcomes using clinical trial data on acute rejection in kidney transplantation and response to Infliximab in ulcerative colitis. We show that integration of prior biological knowledge into the classification as developed in this paper, significantly improves the robustness and generalizability of predictions to independent datasets. We provide a Java code of our algorithm along with a parsed version of the STRING DB database. In summary, we present a method for prediction of clinical phenotypes using baseline genome-wide expression data that makes use of prior biological knowledge on gene-regulatory interactions in order to increase robustness and reproducibility of omic-scale markers. The integrated group-wise regularization methods increases the interpretability of biological signatures and gives stable performance estimates across independent test sets.

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.

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.

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…

Of truth and pathways: chasing bits of information through myriads of articles.

PubMed

Krauthammer, Michael; Kra, Pauline; Iossifov, Ivan; Gomez, Shawn M; Hripcsak, George; Hatzivassiloglou, Vasileios; Friedman, Carol; Rzhetsky, Andrey

2002-01-01

Knowledge on interactions between molecules in living cells is indispensable for theoretical analysis and practical applications in modern genomics and molecular biology. Building such networks relies on the assumption that the correct molecular interactions are known or can be identified by reading a few research articles. However, this assumption does not necessarily hold, as truth is rather an emerging property based on many potentially conflicting facts. This paper explores the processes of knowledge generation and publishing in the molecular biology literature using modelling and analysis of real molecular interaction data. The data analysed in this article were automatically extracted from 50000 research articles in molecular biology using a computer system called GeneWays containing a natural language processing module. The paper indicates that truthfulness of statements is associated in the minds of scientists with the relative importance (connectedness) of substances under study, revealing a potential selection bias in the reporting of research results. Aiming at understanding the statistical properties of the life cycle of biological facts reported in research articles, we formulate a stochastic model describing generation and propagation of knowledge about molecular interactions through scientific publications. We hope that in the future such a model can be useful for automatically producing consensus views of molecular interaction data.

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.…

Light microscopy applications in systems biology: opportunities and challenges

PubMed Central

2013-01-01

Biological systems present multiple scales of complexity, ranging from molecules to entire populations. Light microscopy is one of the least invasive techniques used to access information from various biological scales in living cells. The combination of molecular biology and imaging provides a bottom-up tool for direct insight into how molecular processes work on a cellular scale. However, imaging can also be used as a top-down approach to study the behavior of a system without detailed prior knowledge about its underlying molecular mechanisms. In this review, we highlight the recent developments on microscopy-based systems analyses and discuss the complementary opportunities and different challenges with high-content screening and high-throughput imaging. Furthermore, we provide a comprehensive overview of the available platforms that can be used for image analysis, which enable community-driven efforts in the development of image-based systems biology. PMID:23578051

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

Increased scientific rigor will improve reliability of research and effectiveness of management

USGS Publications Warehouse

Sells, Sarah N.; Bassing, Sarah B.; Barker, Kristin J.; Forshee, Shannon C.; Keever, Allison; Goerz, James W.; Mitchell, Michael S.

2018-01-01

Rigorous science that produces reliable knowledge is critical to wildlife management because it increases accurate understanding of the natural world and informs management decisions effectively. Application of a rigorous scientific method based on hypothesis testing minimizes unreliable knowledge produced by research. To evaluate the prevalence of scientific rigor in wildlife research, we examined 24 issues of the Journal of Wildlife Management from August 2013 through July 2016. We found 43.9% of studies did not state or imply a priori hypotheses, which are necessary to produce reliable knowledge. We posit that this is due, at least in part, to a lack of common understanding of what rigorous science entails, how it produces more reliable knowledge than other forms of interpreting observations, and how research should be designed to maximize inferential strength and usefulness of application. Current primary literature does not provide succinct explanations of the logic behind a rigorous scientific method or readily applicable guidance for employing it, particularly in wildlife biology; we therefore synthesized an overview of the history, philosophy, and logic that define scientific rigor for biological studies. A rigorous scientific method includes 1) generating a research question from theory and prior observations, 2) developing hypotheses (i.e., plausible biological answers to the question), 3) formulating predictions (i.e., facts that must be true if the hypothesis is true), 4) designing and implementing research to collect data potentially consistent with predictions, 5) evaluating whether predictions are consistent with collected data, and 6) drawing inferences based on the evaluation. Explicitly testing a priori hypotheses reduces overall uncertainty by reducing the number of plausible biological explanations to only those that are logically well supported. Such research also draws inferences that are robust to idiosyncratic observations and unavoidable human biases. Offering only post hoc interpretations of statistical patterns (i.e., a posteriorihypotheses) adds to uncertainty because it increases the number of plausible biological explanations without determining which have the greatest support. Further, post hocinterpretations are strongly subject to human biases. Testing hypotheses maximizes the credibility of research findings, makes the strongest contributions to theory and management, and improves reproducibility of research. Management decisions based on rigorous research are most likely to result in effective conservation of wildlife resources. 

A new online computational biology curriculum.

PubMed

Searls, David B

2014-06-01

A recent proliferation of Massive Open Online Courses (MOOCs) and other web-based educational resources has greatly increased the potential for effective self-study in many fields. This article introduces a catalog of several hundred free video courses of potential interest to those wishing to expand their knowledge of bioinformatics and computational biology. The courses are organized into eleven subject areas modeled on university departments and are accompanied by commentary and career advice.

Antibacterial Free Fatty Acids and Monoglycerides: Biological Activities, Experimental Testing, and Therapeutic Applications

PubMed Central

Yoon, Bo Kyeong; Jackman, Joshua A.; Valle-González, Elba R.

2018-01-01

Antimicrobial lipids such as fatty acids and monoglycerides are promising antibacterial agents that destabilize bacterial cell membranes, causing a wide range of direct and indirect inhibitory effects. The goal of this review is to introduce the latest experimental approaches for characterizing how antimicrobial lipids destabilize phospholipid membranes within the broader scope of introducing current knowledge about the biological activities of antimicrobial lipids, testing strategies, and applications for treating bacterial infections. To this end, a general background on antimicrobial lipids, including structural classification, is provided along with a detailed description of their targeting spectrum and currently understood antibacterial mechanisms. Building on this knowledge, different experimental approaches to characterize antimicrobial lipids are presented, including cell-based biological and model membrane-based biophysical measurement techniques. Particular emphasis is placed on drawing out how biological and biophysical approaches complement one another and can yield mechanistic insights into how the physicochemical properties of antimicrobial lipids influence molecular self-assembly and concentration-dependent interactions with model phospholipid and bacterial cell membranes. Examples of possible therapeutic applications are briefly introduced to highlight the potential significance of antimicrobial lipids for human health and medicine, and to motivate the importance of employing orthogonal measurement strategies to characterize the activity profile of antimicrobial lipids. PMID:29642500

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…

Reproductive biology knowledge, and behaviour of teenagers in East, Central and Southern Africa: the Zimbabwe case study.

PubMed

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

1995-11-01

Sexuality in the teenager is often complicated by unplanned/unwanted pregnancy, abortion and the risks of STDs including AIDS. There is therefore a need for improved understanding of factors affecting adolescent sexuality and the implementation of programmes designed to improve their knowledge, risk awareness and subsequent behavioural outcomes. A multicentre study of reproductive health knowledge and behaviour followed by a health education intervention was undertaken amongst teenagers in selected countries of East, Central and Southern Africa. Reported here are findings at baseline derived from the Zimbabwe component on reproductive biology knowledge and behavior. A self-administered questionnaire was used among 1 689 adolescent pupils drawn from rural, urban, co-education, single sex, boarding and day secondary schools in Zimbabwe. Correct knowledge on reproductive biology as measured by the meaning and interpretation of menstruation and wet dreams varied by school from 68 pc to 86 pc, with a significant trend (p < 0,01) based on level of education at baseline. The reported mean age at which menarche took place was 13,5 years +/- 1,3 (mean +/- SD). First coitus was reported to have taken place at the mean age of 12 years for boys and 13,6 years for girls. Seventeen pc of the adolescent pupils reported that they were sexually experienced and 33,2 had relationships. There were misconceptions reported on menstruation with 23 pc reporting that it was an illness. Peers, followed by magazines were the first sources of information on various aspects of reproductive biology, both of which might not provide the correct first information. Among pupils reporting that they were sexually experienced, the largest proportion (56 pc) had unprotected sex. The findings point to the need for targeting the adolescent pupils for information on reproductive biology and increased awareness on the risks of pregnancy, STDs and HIV.

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

Pathway-based analyses.

PubMed

Kent, Jack W

2016-02-03

New technologies for acquisition of genomic data, while offering unprecedented opportunities for genetic discovery, also impose severe burdens of interpretation and penalties for multiple testing. The Pathway-based Analyses Group of the Genetic Analysis Workshop 19 (GAW19) sought reduction of multiple-testing burden through various approaches to aggregation of highdimensional data in pathways informed by prior biological knowledge. Experimental methods testedincluded the use of "synthetic pathways" (random sets of genes) to estimate power and false-positive error rate of methods applied to simulated data; data reduction via independent components analysis, single-nucleotide polymorphism (SNP)-SNP interaction, and use of gene sets to estimate genetic similarity; and general assessment of the efficacy of prior biological knowledge to reduce the dimensionality of complex genomic data. The work of this group explored several promising approaches to managing high-dimensional data, with the caveat that these methods are necessarily constrained by the quality of external bioinformatic annotation.

Planting molecular functions in an ecological context with Arabidopsis thaliana.

PubMed

Krämer, Ute

2015-03-25

The vascular plant Arabidopsis thaliana is a central genetic model and universal reference organism in plant and crop science. The successful integration of different fields of research in the study of A. thaliana has made a large contribution to our molecular understanding of key concepts in biology. The availability and active development of experimental tools and resources, in combination with the accessibility of a wealth of cumulatively acquired knowledge about this plant, support the most advanced systems biology approaches among all land plants. Research in molecular ecology and evolution has also brought the natural history of A. thaliana into the limelight. This article showcases our current knowledge of the natural history of A. thaliana from the perspective of the most closely related plant species, providing an evolutionary framework for interpreting novel findings and for developing new hypotheses based on our knowledge of this plant.

The impact of whole-plant instruction of preservice teachers' understanding of plant science principles

NASA Astrophysics Data System (ADS)

Hypolite, Christine Collins

The purpose of this research was to determine how an inquiry-based, whole-plant instructional strategy would affect preservice elementary teachers' understanding of plant science principles. This study probed: what preservice teachers know about plant biology concepts before and after instruction, their views of the interrelatedness of plant parts and the environment, how growing a plant affects preservice teachers' understanding, and which types of activity-rich plant themes studies, if any, affect preservice elementary teachers' understandings. The participants in the study were enrolled in two elementary science methods class sections at a state university. Each group was administered a preinstructional test at the beginning of the study. The treatment group participated in inquiry-based activities related to the Principles of Plant Biology (American Society of Plant Biologists, 2001), while the comparison group studied those same concepts through traditional instructional methods. A focus group was formed from the treatment group to participate in co-concept mapping sessions. The participants' understandings were assessed through artifacts from activities, a comparison of pre- and postinstructional tests, and the concept maps generated by the focus group. Results of the research indicated that the whole-plant, inquiry-based instructional strategy can be applied to teach preservice elementary teachers plant biology while modeling the human constructivist approach. The results further indicated that this approach enhanced their understanding of plant science content knowledge, as well as pedagogical knowledge. The results also showed that a whole-plant approach to teaching plant science concepts is an instructional strategy that is feasible for the elementary school. The theoretical framework for this study was Human Constructivist learning theory (Mintzes & Wandersee, 1998). The content knowledge and instructional strategy was informed by the Principles of Plant Biology (American Society of Plant Biologists, 2001) and Botany for the Next Millennium (Botanical Society of America, 1995). As a result of this study, a better understanding of the factors that influence preservice elementary teachers' knowledge of plant science principles may benefit elementary science educator in preparing teachers that are "highly qualified."

The conservation and management of tunas and their relatives: setting life history research priorities.

PubMed

Juan-Jordá, Maria José; Mosqueira, Iago; Freire, Juan; Dulvy, Nicholas K

2013-01-01

Scombrids (tunas, bonitos, Spanish mackerels and mackerels) support important fisheries in tropical, subtropical and temperate waters around the world, being one of the most economically- and socially-important marine species globally. Their sustainable exploitation, management and conservation depend on accurate life history information for the development of quantitative fisheries stock assessments, and in the fishery data-poor situations for the identification of vulnerable species. Here, we assemble life history traits (maximum size, growth, longevity, maturity, fecundity, spawning duration and spawning interval) for the 51 species of scombrids globally. We identify major biological gaps in knowledge and prioritize life history research needs in scombrids based on their biological gaps in knowledge, the importance of their fisheries and their current conservation status according to the International Union for Conservation of Nature Red List. We find that the growth and reproductive biology of tunas and mackerel species have been more extensively studied than for Spanish mackerels and bonitos, although there are notable exceptions in all groups. We also reveal that reproductive biology of species, particular fecundity, is the least studied biological aspect in scombrids. We identify two priority groups, including 32 species of scombrids, and several populations of principal market tunas, for which life history research should be prioritized following the species-specific life history gaps identified in this study in the coming decades. By highlighting the important gaps in biological knowledge and providing a priority setting for life history research in scombrid species this study provides guidance for management and conservation and serves as a guide for biologists and resource managers interested in the biology, ecology, and management of scombrid species.

The Conservation and Management of Tunas and Their Relatives: Setting Life History Research Priorities

PubMed Central

Juan-Jordá, Maria José; Mosqueira, Iago; Freire, Juan; Dulvy, Nicholas K.

2013-01-01

Scombrids (tunas, bonitos, Spanish mackerels and mackerels) support important fisheries in tropical, subtropical and temperate waters around the world, being one of the most economically- and socially-important marine species globally. Their sustainable exploitation, management and conservation depend on accurate life history information for the development of quantitative fisheries stock assessments, and in the fishery data-poor situations for the identification of vulnerable species. Here, we assemble life history traits (maximum size, growth, longevity, maturity, fecundity, spawning duration and spawning interval) for the 51 species of scombrids globally. We identify major biological gaps in knowledge and prioritize life history research needs in scombrids based on their biological gaps in knowledge, the importance of their fisheries and their current conservation status according to the International Union for Conservation of Nature Red List. We find that the growth and reproductive biology of tunas and mackerel species have been more extensively studied than for Spanish mackerels and bonitos, although there are notable exceptions in all groups. We also reveal that reproductive biology of species, particular fecundity, is the least studied biological aspect in scombrids. We identify two priority groups, including 32 species of scombrids, and several populations of principal market tunas, for which life history research should be prioritized following the species-specific life history gaps identified in this study in the coming decades. By highlighting the important gaps in biological knowledge and providing a priority setting for life history research in scombrid species this study provides guidance for management and conservation and serves as a guide for biologists and resource managers interested in the biology, ecology, and management of scombrid species. PMID:23950930

"A mission-driven discipline": the growth of conservation biology.

PubMed

Meine, Curt; Soulé, Michael; Noss, Reed E

2006-06-01

Conservation biology emerged in the mid-1980s, drawing on established disciplines and integrating them in pursuit of a coherent goal: the protection and perpetuation of the Earth's biological diversity. Opportunistic in its borrowing and application of knowledge, conservation biology had its roots within the established biological sciences and resource management disciplines but has continually incorporated insights from the empirical experience of resource managers, from the social sciences and humanities, and from diverse cultural sources. The Society for Conservation Biology (SCB) has represented the field's core constituency, while expanding that constituency in keeping with the field's integrative spirit. Conservation Biology has served as SCB's flagship publication, promoting research, dialog, debate, and application of the field's essential concepts. Over the last 20 years the field, SCB, and the journal have evolved to meet changing conservation needs, to explore gaps in our knowledge base, to incorporate new information from related fields, to build professional capacity, and to provide expanded opportunities for international participation. In turn, the field, SCB, and journal have prompted change in related fields, organizations, and publications. In its dedication to advancing the scientific foundations of biodiversity conservation and placing that science at the service of society in a world whose variety, wildness, and beauty we care for conservation biology represents both a continuation and radical reconfiguration of the traditional relationship between science and conservation.

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

PubMed Central

2010-01-01

Background The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. Results In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. Conclusion High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data. PMID:20122245

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

PubMed

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

2010-01-18

The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

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).

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.

Consistent visualizations of changing knowledge

PubMed Central

Tipney, Hannah J.; Schuyler, Ronald P.; Hunter, Lawrence

2009-01-01

Networks are increasingly used in biology to represent complex data in uncomplicated symbolic form. However, as biological knowledge is continually evolving, so must those networks representing this knowledge. Capturing and presenting this type of knowledge change over time is particularly challenging due to the intimate manner in which researchers customize those networks they come into contact with. The effective visualization of this knowledge is important as it creates insight into complex systems and stimulates hypothesis generation and biological discovery. Here we highlight how the retention of user customizations, and the collection and visualization of knowledge associated provenance supports effective and productive network exploration. We also present an extension of the Hanalyzer system, ReOrient, which supports network exploration and analysis in the presence of knowledge change. PMID:21347184

Introduction to biological complexity as a missing link in drug discovery.

PubMed

Gintant, Gary A; George, Christopher H

2018-06-06

Despite a burgeoning knowledge of the intricacies and mechanisms responsible for human disease, technological advances in medicinal chemistry, and more efficient assays used for drug screening, it remains difficult to discover novel and effective pharmacologic therapies. Areas covered: By reference to the primary literature and concepts emerging from academic and industrial drug screening landscapes, the authors propose that this disconnect arises from the inability to scale and integrate responses from simpler model systems to outcomes from more complex and human-based biological systems. Expert opinion: Further collaborative efforts combining target-based and phenotypic-based screening along with systems-based pharmacology and informatics will be necessary to harness the technological breakthroughs of today to derive the novel drug candidates of tomorrow. New questions must be asked of enabling technologies-while recognizing inherent limitations-in a way that moves drug development forward. Attempts to integrate mechanistic and observational information acquired across multiple scales frequently expose the gap between our knowledge and our understanding as the level of complexity increases. We hope that the thoughts and actionable items highlighted will help to inform the directed evolution of the drug discovery process.

Organization and integration of biomedical knowledge with concept maps for key peroxisomal pathways.

PubMed

Willemsen, A M; Jansen, G A; Komen, J C; van Hooff, S; Waterham, H R; Brites, P M T; Wanders, R J A; van Kampen, A H C

2008-08-15

One important area of clinical genomics research involves the elucidation of molecular mechanisms underlying (complex) disorders which eventually may lead to new diagnostic or drug targets. To further advance this area of clinical genomics one of the main challenges is the acquisition and integration of data, information and expert knowledge for specific biomedical domains and diseases. Currently the required information is not very well organized but scattered over biological and biomedical databases, basic text books, scientific literature and experts' minds and may be highly specific, heterogeneous, complex and voluminous. We present a new framework to construct knowledge bases with concept maps for presentation of information and the web ontology language OWL for the representation of information. We demonstrate this framework through the construction of a peroxisomal knowledge base, which focuses on four key peroxisomal pathways and several related genetic disorders. All 155 concept maps in our knowledge base are linked to at least one other concept map, which allows the visualization of one big network of related pieces of information. The peroxisome knowledge base is available from www.bioinformaticslaboratory.nl (Support-->Web applications). Supplementary data is available from www.bioinformaticslaboratory.nl (Research-->Output--> Publications--> KB_SuppInfo)

Improving clustering with metabolic pathway data.

PubMed

Milone, Diego H; Stegmayer, Georgina; López, Mariana; Kamenetzky, Laura; Carrari, Fernando

2014-04-10

It is a common practice in bioinformatics to validate each group returned by a clustering algorithm through manual analysis, according to a-priori biological knowledge. This procedure helps finding functionally related patterns to propose hypotheses for their behavior and the biological processes involved. Therefore, this knowledge is used only as a second step, after data are just clustered according to their expression patterns. Thus, it could be very useful to be able to improve the clustering of biological data by incorporating prior knowledge into the cluster formation itself, in order to enhance the biological value of the clusters. A novel training algorithm for clustering is presented, which evaluates the biological internal connections of the data points while the clusters are being formed. Within this training algorithm, the calculation of distances among data points and neurons centroids includes a new term based on information from well-known metabolic pathways. The standard self-organizing map (SOM) training versus the biologically-inspired SOM (bSOM) training were tested with two real data sets of transcripts and metabolites from Solanum lycopersicum and Arabidopsis thaliana species. Classical data mining validation measures were used to evaluate the clustering solutions obtained by both algorithms. Moreover, a new measure that takes into account the biological connectivity of the clusters was applied. The results of bSOM show important improvements in the convergence and performance for the proposed clustering method in comparison to standard SOM training, in particular, from the application point of view. Analyses of the clusters obtained with bSOM indicate that including biological information during training can certainly increase the biological value of the clusters found with the proposed method. It is worth to highlight that this fact has effectively improved the results, which can simplify their further analysis.The algorithm is available as a web-demo at http://fich.unl.edu.ar/sinc/web-demo/bsom-lite/. The source code and the data sets supporting the results of this article are available at http://sourceforge.net/projects/sourcesinc/files/bsom.

Novel joint TOA/RSSI-based WCE location tracking method without prior knowledge of biological human body tissues.

PubMed

Ito, Takahiro; Anzai, Daisuke; Jianqing Wang

2014-01-01

This paper proposes a novel joint time of arrival (TOA)/received signal strength indicator (RSSI)-based wireless capsule endoscope (WCE) location tracking method without prior knowledge of biological human tissues. Generally, TOA-based localization can achieve much higher localization accuracy than other radio frequency-based localization techniques, whereas wireless signals transmitted from a WCE pass through various kinds of human body tissues, as a result, the propagation velocity inside a human body should be different from one in free space. Because the variation of propagation velocity is mainly affected by the relative permittivity of human body tissues, instead of pre-measurement for the relative permittivity in advance, we simultaneously estimate not only the WCE location but also the relative permittivity information. For this purpose, this paper first derives the relative permittivity estimation model with measured RSSI information. Then, we pay attention to a particle filter algorithm with the TOA-based localization and the RSSI-based relative permittivity estimation. Our computer simulation results demonstrates that the proposed tracking methods with the particle filter can accomplish an excellent localization accuracy of around 2 mm without prior information of the relative permittivity of the human body tissues.

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.

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…

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

NASA Space Biology Plant Research for 2010-2020

NASA Technical Reports Server (NTRS)

Levine, H. G.; Tomko, D. L.; Porterfield, D. M.

2012-01-01

The U.S. National Research Council (NRC) recently published "Recapturing a Future for Space Exploration: Life and Physical Sciences Research for a New Era" (http://www.nap.edu/catalog.php?record id=13048), and NASA completed a Space Biology Science Plan to develop a strategy for implementing its recommendations ( http://www.nasa.gov/exploration/library/esmd documents.html). The most important recommendations of the NRC report on plant biology in space were that NASA should: (1) investigate the roles of microbial-plant systems in long-term bioregenerative life support systems, and (2) establish a robust spaceflight program of research analyzing plant growth and physiological responses to the multiple stimuli encountered in spaceflight environments. These efforts should take advantage of recently emerged analytical technologies (genomics, transcriptomics, proteomics, metabolomics) and apply modern cellular and molecular approaches in the development of a vigorous flight-based and ground-based research program. This talk will describe NASA's strategy and plans for implementing these NRC Plant Space Biology recommendations. New research capabilities for Plant Biology, optimized by providing state-of-the-art automated technology and analytical techniques to maximize scientific return, will be described. Flight experiments will use the most appropriate platform to achieve science results (e.g., ISS, free flyers, sub-orbital flights) and NASA will work closely with its international partners and other U.S. agencies to achieve its objectives. One of NASA's highest priorities in Space Biology is the development research capabilities for use on the International Space Station and other flight platforms for studying multiple generations of large plants. NASA will issue recurring NASA Research Announcements (NRAs) that include a rapid turn-around model to more fully engage the biology community in designing experiments to respond to the NRC recommendations. In doing so, NASA's Space Biology research will optimize ISS research utilization, develop and demonstrate technology and hardware that will enable new science, and contribute to the base of fundamental knowledge that will facilitate development of new tools for human space exploration and Earth applications. By taking these steps, NASA will energize the Space Biology user community and advance our knowledge of the effect of the space flight environment on living systems.

[Application of mtDNA polymorphism in species identification of sarcosaphagous insects].

PubMed

Li, Xiang; Cai, Ji-feng

2011-04-01

Species identification of sarcosaphagous insects is one of the important steps in forensic research based on the knowledge of entomology. Recent studies reveal that the application of molecular biology, especially the mtDNA sequences analysis, works well in the species identification of sarcosaphagous insects. The molecular biology characteristics, structures, polymorphism of mtDNA of sarcosaphagous insects, and the recent studies in species identification of sarcosaphagous insects are reviewed in this article.

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.

Making a protein extract from plant pathogenic fungi for gel- and LC-based proteomics.

PubMed

Fernández, Raquel González; Redondo, Inmaculada; Jorrin-Novo, Jesus V

2014-01-01

Proteomic technologies have become a successful tool to provide relevant information on fungal biology. In the case of plant pathogenic fungi, this approach would allow a deeper knowledge of the interaction and the biological cycle of the pathogen, as well as the identification of pathogenicity and virulence factors. These two elements open up new possibilities for crop disease diagnosis and environment-friendly crop protection. Phytopathogenic fungi, due to its particular cellular characteristics, can be considered as a recalcitrant biological material, which makes it difficult to obtain quality protein samples for proteomic analysis. This chapter focuses on protein extraction for gel- and LC-based proteomics with specific protocols of our current research with Botrytis cinerea.

Functional networks inference from rule-based machine learning models.

PubMed

Lazzarini, Nicola; Widera, Paweł; Williamson, Stuart; Heer, Rakesh; Krasnogor, Natalio; Bacardit, Jaume

2016-01-01

Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes which are expressed at similar levels across different samples. An alternative to this paradigm is the inference of relationships from the structure of machine learning models. These models are able to capture complex relationships between variables, that often are different/complementary to the similarity-based methods. We propose a protocol to infer functional networks from machine learning models, called FuNeL. It assumes, that genes used together within a rule-based machine learning model to classify the samples, might also be functionally related at a biological level. The protocol is first tested on synthetic datasets and then evaluated on a test suite of 8 real-world datasets related to human cancer. The networks inferred from the real-world data are compared against gene co-expression networks of equal size, generated with 3 different methods. The comparison is performed from two different points of view. We analyse the enriched biological terms in the set of network nodes and the relationships between known disease-associated genes in a context of the network topology. The comparison confirms both the biological relevance and the complementary character of the knowledge captured by the FuNeL networks in relation to similarity-based methods and demonstrates its potential to identify known disease associations as core elements of the network. Finally, using a prostate cancer dataset as a case study, we confirm that the biological knowledge captured by our method is relevant to the disease and consistent with the specialised literature and with an independent dataset not used in the inference process. The implementation of our network inference protocol is available at: http://ico2s.org/software/funel.html.

IntegromeDB: an integrated system and biological search engine.

PubMed

Baitaluk, Michael; Kozhenkov, Sergey; Dubinina, Yulia; Ponomarenko, Julia

2012-01-19

With the growth of biological data in volume and heterogeneity, web search engines become key tools for researchers. However, general-purpose search engines are not specialized for the search of biological data. Here, we present an approach at developing a biological web search engine based on the Semantic Web technologies and demonstrate its implementation for retrieving gene- and protein-centered knowledge. The engine is available at http://www.integromedb.org. The IntegromeDB search engine allows scanning data on gene regulation, gene expression, protein-protein interactions, pathways, metagenomics, mutations, diseases, and other gene- and protein-related data that are automatically retrieved from publicly available databases and web pages using biological ontologies. To perfect the resource design and usability, we welcome and encourage community feedback.

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

A year (2014-2015) of plants in Proteomics journal. Progress in wet and dry methodologies, moving from protein catalogs, and the view of classic plant biochemists.

PubMed

Sanchez-Lucas, Rosa; Mehta, Angela; Valledor, Luis; Cabello-Hurtado, Francisco; Romero-Rodrıguez, M Cristina; Simova-Stoilova, Lyudmila; Demir, Sekvan; Rodriguez-de-Francisco, Luis E; Maldonado-Alconada, Ana M; Jorrin-Prieto, Ana L; Jorrín-Novo, Jesus V

2016-03-01

The present review is an update of the previous one published in Proteomics 2015 Reviews special issue [Jorrin-Novo, J. V. et al., Proteomics 2015, 15, 1089-1112] covering the July 2014-2015 period. It has been written on the bases of the publications that appeared in Proteomics journal during that period and the most relevant ones that have been published in other high-impact journals. Methodological advances and the contribution of the field to the knowledge of plant biology processes and its translation to agroforestry and environmental sectors will be discussed. This review has been organized in four blocks, with a starting general introduction (literature survey) followed by sections focusing on the methodology (in vitro, in vivo, wet, and dry), proteomics integration with other approaches (systems biology and proteogenomics), biological information, and knowledge (cell communication, receptors, and signaling), ending with a brief mention of some other biological and translational topics to which proteomics has made some contribution. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The micronutrient genomics project: a community-driven knowledge base for micronutrient research

USDA-ARS?s Scientific Manuscript database

Micronutrients influence multiple metabolic pathways including oxidative and inflammatory processes. Optimum micronutrient supply is important for the maintenance of homeostasis in metabolism and, ultimately, for maintaining good health. With advances in systems biology and genomics technologies, it...

Workflow based framework for life science informatics.

PubMed

Tiwari, Abhishek; Sekhar, Arvind K T

2007-10-01

Workflow technology is a generic mechanism to integrate diverse types of available resources (databases, servers, software applications and different services) which facilitate knowledge exchange within traditionally divergent fields such as molecular biology, clinical research, computational science, physics, chemistry and statistics. Researchers can easily incorporate and access diverse, distributed tools and data to develop their own research protocols for scientific analysis. Application of workflow technology has been reported in areas like drug discovery, genomics, large-scale gene expression analysis, proteomics, and system biology. In this article, we have discussed the existing workflow systems and the trends in applications of workflow based systems.

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…

Noun and knowledge retrieval for biological and non-biological entities following right occipitotemporal lesions.

PubMed

Bruffaerts, Rose; De Weer, An-Sofie; De Grauwe, Sophie; Thys, Miek; Dries, Eva; Thijs, Vincent; Sunaert, Stefan; Vandenbulcke, Mathieu; De Deyne, Simon; Storms, Gerrit; Vandenberghe, Rik

2014-09-01

We investigated the critical contribution of right ventral occipitotemporal cortex to knowledge of visual and functional-associative attributes of biological and non-biological entities and how this relates to category-specificity during confrontation naming. In a consecutive series of 7 patients with lesions confined to right ventral occipitotemporal cortex, we conducted an extensive assessment of oral generation of visual-sensory and functional-associative features in response to the names of biological and nonbiological entities. Subjects also performed a confrontation naming task for these categories. Our main novel finding related to a unique case with a small lesion confined to right medial fusiform gyrus who showed disproportionate naming impairment for nonbiological versus biological entities, specifically for tools. Generation of visual and functional-associative features was preserved for biological and non-biological entities. In two other cases, who had a relatively small posterior lesion restricted to primary visual and posterior fusiform cortex, retrieval of visual attributes was disproportionately impaired compared to functional-associative attributes, in particular for biological entities. However, these cases did not show a category-specific naming deficit. Two final cases with the largest lesions showed a classical dissociation between biological versus nonbiological entities during naming, with normal feature generation performance. This is the first lesion-based evidence of a critical contribution of the right medial fusiform cortex to tool naming. Second, dissociations along the dimension of attribute type during feature generation do not co-occur with category-specificity during naming in the current patient sample. Copyright © 2014 Elsevier Ltd. All rights reserved.

Experiential-Based Climate Change Education: Fostering Students' Knowledge and Motivation towards the Environment

ERIC Educational Resources Information Center

Karpudewan, Mageswary; Mohd Ali Khan, Nur Sabrina

2017-01-01

Climate change is one of the most important environmental issues affecting our society today and we need to educate the citizens about the impact on human lives. An attempt was made to integrate experiential-based climate change education into the teaching and learning of secondary school Biology lessons on the topic of "Endangered…

The Impact of a Web-Based Research Simulation in Bioinformatics on Students' Understanding of Genetics

ERIC Educational Resources Information Center

Gelbart, Hadas; Brill, Gilat; Yarden, Anat

2009-01-01

Providing learners with opportunities to engage in activities similar to those carried out by scientists was addressed in a web-based research simulation in genetics developed for high school biology students. The research simulation enables learners to apply their genetics knowledge while giving them an opportunity to participate in an authentic…

Scaffolding Middle School Students' Construction of Scientific Explanations: Comparing a Cognitive versus a Metacognitive Evaluation Approach

ERIC Educational Resources Information Center

Wang, Chia-Yu

2015-01-01

This study investigated the effects of scaffolds as cognitive prompts and as metacognitive evaluation on seventh-grade students' growth of content knowledge and construction of scientific explanations in five inquiry-based biology activities. Students' scores on multiple-choice pretest and posttest and worksheets for five inquiry-based activities…

Artificial intelligence in hematology.

PubMed

Zini, Gina

2005-10-01

Artificial intelligence (AI) is a computer based science which aims to simulate human brain faculties using a computational system. A brief history of this new science goes from the creation of the first artificial neuron in 1943 to the first artificial neural network application to genetic algorithms. The potential for a similar technology in medicine has immediately been identified by scientists and researchers. The possibility to store and process all medical knowledge has made this technology very attractive to assist or even surpass clinicians in reaching a diagnosis. Applications of AI in medicine include devices applied to clinical diagnosis in neurology and cardiopulmonary diseases, as well as the use of expert or knowledge-based systems in routine clinical use for diagnosis, therapeutic management and for prognostic evaluation. Biological applications include genome sequencing or DNA gene expression microarrays, modeling gene networks, analysis and clustering of gene expression data, pattern recognition in DNA and proteins, protein structure prediction. In the field of hematology the first devices based on AI have been applied to the routine laboratory data management. New tools concern the differential diagnosis in specific diseases such as anemias, thalassemias and leukemias, based on neural networks trained with data from peripheral blood analysis. A revolution in cancer diagnosis, including the diagnosis of hematological malignancies, has been the introduction of the first microarray based and bioinformatic approach for molecular diagnosis: a systematic approach based on the monitoring of simultaneous expression of thousands of genes using DNA microarray, independently of previous biological knowledge, analysed using AI devices. Using gene profiling, the traditional diagnostic pathways move from clinical to molecular based diagnostic systems.

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)

[The etiology of caries: the construction of a thought-style].

PubMed

Gomes, Doris; Da Ros, Marco Aurélio

2008-01-01

This study deals with the construction of the Odontological Thought Style about the etiology of caries. As a reference we use the theory of Ludwik Fleck (1896 -1961) maintaining that knowledge is a result of social activity and that each individual with certain knowledge belongs to a certain cultural environment, a thought-collective sharing the same thought-style. The sources used for studying the transformations in the theory were classic literature and a universe of 161 articles published between 1980 and 2001, selected from the Medline/Pubmed base using the key words dental caries/etiology/theoretical. Based on the analysis of these articles and books we identified a macro style of thinking characterized as multicausal-biologicist transforming the etiological knowledge mainly since the mid 90s. In this stage, in which the period of classicism of the theory does not respond any more to the reality of the disease revealed in epidemiological studies, five distinct trends could be identified: the biological; the clinical-biological; the clinical-epidemiological; the biopsychosocial and the social. Thus, one of the challenges posed to odontology today is to transform its thought-style adapting it to the new social reality of the disease.

Boolean network inference from time series data incorporating prior biological knowledge.

PubMed

Haider, Saad; Pal, Ranadip

2012-01-01

Numerous approaches exist for modeling of genetic regulatory networks (GRNs) but the low sampling rates often employed in biological studies prevents the inference of detailed models from experimental data. In this paper, we analyze the issues involved in estimating a model of a GRN from single cell line time series data with limited time points. We present an inference approach for a Boolean Network (BN) model of a GRN from limited transcriptomic or proteomic time series data based on prior biological knowledge of connectivity, constraints on attractor structure and robust design. We applied our inference approach to 6 time point transcriptomic data on Human Mammary Epithelial Cell line (HMEC) after application of Epidermal Growth Factor (EGF) and generated a BN with a plausible biological structure satisfying the data. We further defined and applied a similarity measure to compare synthetic BNs and BNs generated through the proposed approach constructed from transitions of various paths of the synthetic BNs. We have also compared the performance of our algorithm with two existing BN inference algorithms. Through theoretical analysis and simulations, we showed the rarity of arriving at a BN from limited time series data with plausible biological structure using random connectivity and absence of structure in data. The framework when applied to experimental data and data generated from synthetic BNs were able to estimate BNs with high similarity scores. Comparison with existing BN inference algorithms showed the better performance of our proposed algorithm for limited time series data. The proposed framework can also be applied to optimize the connectivity of a GRN from experimental data when the prior biological knowledge on regulators is limited or not unique.

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.

Prototype Biology-Based Radiation Risk Module Project

NASA Technical Reports Server (NTRS)

Terrier, Douglas; Clayton, Ronald G.; Patel, Zarana; Hu, Shaowen; Huff, Janice

2015-01-01

Biological effects of space radiation and risk mitigation are strategic knowledge gaps for the Evolvable Mars Campaign. The current epidemiology-based NASA Space Cancer Risk (NSCR) model contains large uncertainties (HAT #6.5a) due to lack of information on the radiobiology of galactic cosmic rays (GCR) and lack of human data. The use of experimental models that most accurately replicate the response of human tissues is critical for precision in risk projections. Our proposed study will compare DNA damage, histological, and cell kinetic parameters after irradiation in normal 2D human cells versus 3D tissue models, and it will use a multi-scale computational model (CHASTE) to investigate various biological processes that may contribute to carcinogenesis, including radiation-induced cellular signaling pathways. This cross-disciplinary work, with biological validation of an evolvable mathematical computational model, will help reduce uncertainties within NSCR and aid risk mitigation for radiation-induced carcinogenesis.

Wet Lab Accelerator: A Web-Based Application Democratizing Laboratory Automation for Synthetic Biology.

PubMed

Bates, Maxwell; Berliner, Aaron J; Lachoff, Joe; Jaschke, Paul R; Groban, Eli S

2017-01-20

Wet Lab Accelerator (WLA) is a cloud-based tool that allows a scientist to conduct biology via robotic control without the need for any programming knowledge. A drag and drop interface provides a convenient and user-friendly method of generating biological protocols. Graphically developed protocols are turned into programmatic instruction lists required to conduct experiments at the cloud laboratory Transcriptic. Prior to the development of WLA, biologists were required to write in a programming language called "Autoprotocol" in order to work with Transcriptic. WLA relies on a new abstraction layer we call "Omniprotocol" to convert the graphical experimental description into lower level Autoprotocol language, which then directs robots at Transcriptic. While WLA has only been tested at Transcriptic, the conversion of graphically laid out experimental steps into Autoprotocol is generic, allowing extension of WLA into other cloud laboratories in the future. WLA hopes to democratize biology by bringing automation to general biologists.

[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 boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction

PubMed Central

Kim, Dokyoon; Joung, Je-Gun; Sohn, Kyung-Ah; Shin, Hyunjung; Park, Yu Rang; Ritchie, Marylyn D; Kim, Ju Han

2015-01-01

Objective Cancer can involve gene dysregulation via multiple mechanisms, so no single level of genomic data fully elucidates tumor behavior due to the presence of numerous genomic variations within or between levels in a biological system. We have previously proposed a graph-based integration approach that combines multi-omics data including copy number alteration, methylation, miRNA, and gene expression data for predicting clinical outcome in cancer. However, genomic features likely interact with other genomic features in complex signaling or regulatory networks, since cancer is caused by alterations in pathways or complete processes. Methods Here we propose a new graph-based framework for integrating multi-omics data and genomic knowledge to improve power in predicting clinical outcomes and elucidate interplay between different levels. To highlight the validity of our proposed framework, we used an ovarian cancer dataset from The Cancer Genome Atlas for predicting stage, grade, and survival outcomes. Results Integrating multi-omics data with genomic knowledge to construct pre-defined features resulted in higher performance in clinical outcome prediction and higher stability. For the grade outcome, the model with gene expression data produced an area under the receiver operating characteristic curve (AUC) of 0.7866. However, models of the integration with pathway, Gene Ontology, chromosomal gene set, and motif gene set consistently outperformed the model with genomic data only, attaining AUCs of 0.7873, 0.8433, 0.8254, and 0.8179, respectively. Conclusions Integrating multi-omics data and genomic knowledge to improve understanding of molecular pathogenesis and underlying biology in cancer should improve diagnostic and prognostic indicators and the effectiveness of therapies. PMID:25002459

Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction.

PubMed

Kim, Dokyoon; Joung, Je-Gun; Sohn, Kyung-Ah; Shin, Hyunjung; Park, Yu Rang; Ritchie, Marylyn D; Kim, Ju Han

2015-01-01

Cancer can involve gene dysregulation via multiple mechanisms, so no single level of genomic data fully elucidates tumor behavior due to the presence of numerous genomic variations within or between levels in a biological system. We have previously proposed a graph-based integration approach that combines multi-omics data including copy number alteration, methylation, miRNA, and gene expression data for predicting clinical outcome in cancer. However, genomic features likely interact with other genomic features in complex signaling or regulatory networks, since cancer is caused by alterations in pathways or complete processes. Here we propose a new graph-based framework for integrating multi-omics data and genomic knowledge to improve power in predicting clinical outcomes and elucidate interplay between different levels. To highlight the validity of our proposed framework, we used an ovarian cancer dataset from The Cancer Genome Atlas for predicting stage, grade, and survival outcomes. Integrating multi-omics data with genomic knowledge to construct pre-defined features resulted in higher performance in clinical outcome prediction and higher stability. For the grade outcome, the model with gene expression data produced an area under the receiver operating characteristic curve (AUC) of 0.7866. However, models of the integration with pathway, Gene Ontology, chromosomal gene set, and motif gene set consistently outperformed the model with genomic data only, attaining AUCs of 0.7873, 0.8433, 0.8254, and 0.8179, respectively. Integrating multi-omics data and genomic knowledge to improve understanding of molecular pathogenesis and underlying biology in cancer should improve diagnostic and prognostic indicators and the effectiveness of therapies. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association.

[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…

75 FR 81618 - Request for Notification From Consumer Organizations Interested in Participating in the Selection...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-12-28

.... Knowledgeable in the areas of dental implants, dental materials, periodontology, tissue engineering, and dental... and tissue based products, regenerative medicine and combination products. Blood Products..., immunology, blood banking, surgery, internal medicine, biochemistry, engineering, biological and physical...

36 CFR 220.3 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... practices based on clearly identified intended outcomes and monitoring to determine if management actions... those outcomes are met or re-evaluated. Adaptive management stems from the recognition that knowledge... the least harm to the biological and physical environment; it also is the alternative which best...

36 CFR 220.3 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... practices based on clearly identified intended outcomes and monitoring to determine if management actions... those outcomes are met or re-evaluated. Adaptive management stems from the recognition that knowledge... the least harm to the biological and physical environment; it also is the alternative which best...

36 CFR 220.3 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... practices based on clearly identified intended outcomes and monitoring to determine if management actions... those outcomes are met or re-evaluated. Adaptive management stems from the recognition that knowledge... the least harm to the biological and physical environment; it also is the alternative which best...

36 CFR 220.3 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... practices based on clearly identified intended outcomes and monitoring to determine if management actions... those outcomes are met or re-evaluated. Adaptive management stems from the recognition that knowledge... the least harm to the biological and physical environment; it also is the alternative which best...

Seahorses in focus: local ecological knowledge of seahorse-watching operators in a tropical estuary.

PubMed

Ternes, Maria L F; Gerhardinger, Leopoldo C; Schiavetti, Alexandre

2016-11-08

Seahorses are endangered teleost fishes under increasing human pressures worldwide. In Brazil, marine conservationists and policy-makers are thus often skeptical about the viability of sustainable human-seahorse interactions. This study focuses on local ecological knowledge on seahorses and the implications of their non-lethal touristic use by a coastal community in northeastern Brazil. Community-based seahorse-watching activities have been carried out in Maracaípe village since 1999, but remained uninvestigated until the present study. Our goal is to provide ethnoecological understanding on this non-extractive use to support seahorse conservation and management. We interviewed 32 informants through semi-structured questionnaires to assess their socioeconomic profile, their knowledge on seahorse natural history traits, human uses, threats and abundance trends. Seahorse-watching has high socioeconomic relevance, being the primary income source for all respondents. Interviewees elicited a body of knowledge on seahorse biology largely consistent with up-to-date research literature. Most informants (65.5 %) perceived no change in seahorse abundance. Their empirical knowledge often surpassed scientific reports, i.e. through remarks on trophic ecology; reproductive aspects, such as, behavior and breeding season; spatial and temporal distribution, suggesting seahorse migration related to environmental parameters. Seahorse-watching operators were aware of seahorse biological and ecological aspects. Despite the gaps remaining on biological data about certain seahorse traits, the respondents provided reliable information on all questions, adding ethnoecological remarks not yet assessed by conventional scientific surveys. We provide novel ethnobiological insight on non-extractive modes of human-seahorse interaction, eliciting environmental policies to integrate seahorse conservation with local ecological knowledge and innovative ideas for seahorse sustainable use. Our study resonates with calls for more active engagement with communities and their local ecologies if marine conservation and development are to be reconciled.

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.

Development of Korean Rare Disease Knowledge Base

PubMed Central

Seo, Heewon; Kim, Dokyoon; Chae, Jong-Hee; Kang, Hee Gyung; Lim, Byung Chan; Cheong, Hae Il

2012-01-01

Objectives Rare disease research requires a broad range of disease-related information for the discovery of causes of genetic disorders that are maladies caused by abnormalities in genes or chromosomes. A rarity in cases makes it difficult for researchers to elucidate definite inception. This knowledge base will be a major resource not only for clinicians, but also for the general public, who are unable to find consistent information on rare diseases in a single location. Methods We design a compact database schema for faster querying; its structure is optimized to store heterogeneous data sources. Then, clinicians at Seoul National University Hospital (SNUH) review and revise those resources. Additionally, we integrated other sources to capture genomic resources and clinical trials in detail on the Korean Rare Disease Knowledge base (KRDK). Results As a result, we have developed a Web-based knowledge base, KRDK, suitable for study of Mendelian diseases that commonly occur among Koreans. This knowledge base is comprised of disease summary and review, causal gene list, laboratory and clinic directory, patient registry, and so on. Furthermore, database for analyzing and giving access to human biological information and the clinical trial management system are integrated on KRDK. Conclusions We expect that KRDK, the first rare disease knowledge base in Korea, may contribute to collaborative research and be a reliable reference for application to clinical trials. Additionally, this knowledge base is ready for querying of drug information so that visitors can search a list of rare diseases that is relative to specific drugs. Visitors can have access to KRDK via http://www.snubi.org/software/raredisease/. PMID:23346478

Panel 3: Recent advances in anatomy, pathology, and cell biology in relation to otitis media pathogenesis.

PubMed

Cayé-Thomasen, Per; Hermansson, Ann; Bakaletz, Lauren; Hellstrøm, Sten; Kanzaki, Sho; Kerschner, Joseph; Lim, David; Lin, Jizhen; Mason, Kevin; Spratley, Jorge

2013-04-01

The pathogenesis of otitis media (OM) involves a number of factors related to the anatomy, pathology, and cell biology of the middle ear, the mastoid, the Eustachian tube, and the nasopharynx. Although some issues of pathogenesis are fairly well established, others are only marginally indicated by current knowledge, and yet others remain undisclosed. The objective of this article is to provide a state-of-the-art review on recent scientific achievements in the pathogenesis of OM, as related to anatomy, pathology, and cell biology. PubMed, Ovid Medline, and Cochrane Library. Articles published on the pathogenesis of OM and the anatomy, pathology, and cell biology of the middle ear, the mastoid, the Eustachian tube, and the nasopharynx between January 2007 and June 2011 were identified. Among almost 1900 abstracts, the authors selected 130 articles for full article review and inclusion in this report. New knowledge on a number of issues emerged, including cell-specific expression and function of fluid transportation and innate immune system molecules, mucous cell metaplasia, mucin expression, bacterial adherence, and epithelial internalization, as well as the occurrence, composition, dynamics, and potential role of bacterial biofilm. In addition, the potential role of gastroesophageal reflux disease and cigarette smoke exposure has been explored further. Over the past 4 years, considerable scientific progress has been made on the pathogenesis of OM, as related to issues of anatomy, pathology, and cell biology. Based on these new achievements and a sustained lack of essential knowledge, suggestions for future research are outlined.

User-centered evaluation of Arizona BioPathway: an information extraction, integration, and visualization system.

PubMed

Quiñones, Karin D; Su, Hua; Marshall, Byron; Eggers, Shauna; Chen, Hsinchun

2007-09-01

Explosive growth in biomedical research has made automated information extraction, knowledge integration, and visualization increasingly important and critically needed. The Arizona BioPathway (ABP) system extracts and displays biological regulatory pathway information from the abstracts of journal articles. This study uses relations extracted from more than 200 PubMed abstracts presented in a tabular and graphical user interface with built-in search and aggregation functionality. This paper presents a task-centered assessment of the usefulness and usability of the ABP system focusing on its relation aggregation and visualization functionalities. Results suggest that our graph-based visualization is more efficient in supporting pathway analysis tasks and is perceived as more useful and easier to use as compared to a text-based literature-viewing method. Relation aggregation significantly contributes to knowledge-acquisition efficiency. Together, the graphic and tabular views in the ABP Visualizer provide a flexible and effective interface for pathway relation browsing and analysis. Our study contributes to pathway-related research and biological information extraction by assessing the value of a multiview, relation-based interface that supports user-controlled exploration of pathway information across multiple granularities.

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.

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…

Life lines: An art history of biological research around 1800.

PubMed

Bruhn, Matthias

2011-12-01

Around 1800, the scientific "illustrator" emerged as a new artistic profession in Europe. Artists were increasingly sought after in order to picture anatomical dissections and microscopic observations and to translate drawings into artworks for books and journals. By training and technical expertise, they introduced a particular kind of knowledge into scientific perception that also shaped the common image of nature. Illustrations of scientific publications, often undervalued as a biased interpretation of facts and subordinate to logic and description, thus convey an 'art history' of science in its own right, relevant both for the understanding of biological thought around 1800 as well as for the development of the arts and their historiography. The article is based on an analysis of botanical treatises produced for the Göttingen Society of Sciences in 1803, during an early phase of microscopic cell research, in order to determine the constitutive role of artistic knowledge and the media employed for the visualization and conceptualization of biological issues. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

IntegromeDB: an integrated system and biological search engine

PubMed Central

2012-01-01

Background With the growth of biological data in volume and heterogeneity, web search engines become key tools for researchers. However, general-purpose search engines are not specialized for the search of biological data. Description Here, we present an approach at developing a biological web search engine based on the Semantic Web technologies and demonstrate its implementation for retrieving gene- and protein-centered knowledge. The engine is available at http://www.integromedb.org. Conclusions The IntegromeDB search engine allows scanning data on gene regulation, gene expression, protein-protein interactions, pathways, metagenomics, mutations, diseases, and other gene- and protein-related data that are automatically retrieved from publicly available databases and web pages using biological ontologies. To perfect the resource design and usability, we welcome and encourage community feedback. PMID:22260095

Agent-based re-engineering of ErbB signaling: a modeling pipeline for integrative systems biology.

PubMed

Das, Arya A; Ajayakumar Darsana, T; Jacob, Elizabeth

2017-03-01

Experiments in systems biology are generally supported by a computational model which quantitatively estimates the parameters of the system by finding the best fit to the experiment. Mathematical models have proved to be successful in reverse engineering the system. The data generated is interpreted to understand the dynamics of the underlying phenomena. The question we have sought to answer is that - is it possible to use an agent-based approach to re-engineer a biological process, making use of the available knowledge from experimental and modelling efforts? Can the bottom-up approach benefit from the top-down exercise so as to create an integrated modelling formalism for systems biology? We propose a modelling pipeline that learns from the data given by reverse engineering, and uses it for re-engineering the system, to carry out in-silico experiments. A mathematical model that quantitatively predicts co-expression of EGFR-HER2 receptors in activation and trafficking has been taken for this study. The pipeline architecture takes cues from the population model that gives the rates of biochemical reactions, to formulate knowledge-based rules for the particle model. Agent-based simulations using these rules, support the existing facts on EGFR-HER2 dynamics. We conclude that, re-engineering models, built using the results of reverse engineering, opens up the possibility of harnessing the power pack of data which now lies scattered in literature. Virtual experiments could then become more realistic when empowered with the findings of empirical cell biology and modelling studies. Implemented on the Agent Modelling Framework developed in-house. C ++ code templates available in Supplementary material . liz.csir@gmail.com. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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).

Microbial Dark Matter Investigations: How Microbial Studies Transform Biological Knowledge and Empirically Sketch a Logic of Scientific Discovery

PubMed Central

Bernard, Guillaume; Pathmanathan, Jananan S; Lannes, Romain; Lopez, Philippe; Bapteste, Eric

2018-01-01

Abstract Microbes are the oldest and most widespread, phylogenetically and metabolically diverse life forms on Earth. However, they have been discovered only 334 years ago, and their diversity started to become seriously investigated even later. For these reasons, microbial studies that unveil novel microbial lineages and processes affecting or involving microbes deeply (and repeatedly) transform knowledge in biology. Considering the quantitative prevalence of taxonomically and functionally unassigned sequences in environmental genomics data sets, and that of uncultured microbes on the planet, we propose that unraveling the microbial dark matter should be identified as a central priority for biologists. Based on former empirical findings of microbial studies, we sketch a logic of discovery with the potential to further highlight the microbial unknowns. PMID:29420719

Computation as the mechanistic bridge between precision medicine and systems therapeutics.

PubMed

Hansen, J; Iyengar, R

2013-01-01

Over the past 50 years, like molecular cell biology, medicine and pharmacology have been driven by a reductionist approach. The focus on individual genes and cellular components as disease loci and drug targets has been a necessary step in understanding the basic mechanisms underlying tissue/organ physiology and drug action. Recent progress in genomics and proteomics, as well as advances in other technologies that enable large-scale data gathering and computational approaches, is providing new knowledge of both normal and disease states. Systems-biology approaches enable integration of knowledge from different types of data for precision medicine and systems therapeutics. In this review, we describe recent studies that contribute to these emerging fields and discuss how together these fields can lead to a mechanism-based therapy for individual patients.

Computation as the Mechanistic Bridge Between Precision Medicine and Systems Therapeutics

PubMed Central

Hansen, J; Iyengar, R

2014-01-01

Over the past 50 years, like molecular cell biology, medicine and pharmacology have been driven by a reductionist approach. The focus on individual genes and cellular components as disease loci and drug targets has been a necessary step in understanding the basic mechanisms underlying tissue/organ physiology and drug action. Recent progress in genomics and proteomics, as well as advances in other technologies that enable large-scale data gathering and computational approaches, is providing new knowledge of both normal and disease states. Systems-biology approaches enable integration of knowledge from different types of data for precision medicine and systems therapeutics. In this review, we describe recent studies that contribute to these emerging fields and discuss how together these fields can lead to a mechanism-based therapy for individual patients. PMID:23212109

Modeling limb-bud dysmorphogenesis in a predictive virtual embryo model

EPA Science Inventory

ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput screening (HTS) and computational methods that integrate knowledge of biological systems and in vivo toxicities (www.epa.gov/ncct/toxcast/). Many ToxCast assays assess signaling pathways and c...

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…

Learning about Intermolecular Interactions from the Cambridge Structural Database

ERIC Educational Resources Information Center

Battle, Gary M.; Allen, Frank H.

2012-01-01

A clear understanding and appreciation of noncovalent interactions, especially hydrogen bonding, are vitally important to students of chemistry and the life sciences, including biochemistry, molecular biology, pharmacology, and medicine. The opportunities afforded by the IsoStar knowledge base of intermolecular interactions to enhance the…

The electrochemical properties of the purine bases : at the interface between biological conjugates to inorganic surfaces

NASA Technical Reports Server (NTRS)

Hays, Charles C.

2003-01-01

The study of the charge transfer and interfacial reactions of the purine bases in physiological solutions provides valuable knowledge, as these processes are relevant to the origins of life. It has been proposed that the adsorption of the adsorption of the purine bases on an inorganic surface could serve as a template for specifying the arrangement of amino acids in peptides.

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,…

Development and Evaluation of an Online, Inquiry-Based Food Safety Education Program for Secondary Teachers and Their Students

ERIC Educational Resources Information Center

Beffa-Negrini, Patricia A.; Cohen, Nancy L.; Laus, Mary Jane; McLandsborough, Lynne A.

2007-01-01

Secondary science teachers who integrate food safety (FS) into curricula can provide FS knowledge and skills to youth while reinforcing science skills and concepts. National science education standards and the Biological Science Curriculum Study 5E Inquiry-based Learning Model were used to design an online training, Food Safety FIRST. The training…

Investigating the Effectiveness of an Inquiry-Based Intervention on Human Reproduction in Relation to Students' Gender, Prior Knowledge and Motivation for Learning in Biology

ERIC Educational Resources Information Center

Hadjichambis, Andreas Ch.; Georgiou, Yiannis; Paraskeva-Hadjichambi, Demetra; Kyza, Eleni A.; Mappouras, Demetrios

2016-01-01

Despite the importance of understanding how the human reproductive system works, adolescents worldwide exhibit weak conceptual understanding, which leads to serious risks, such as unwanted pregnancies and sexually transmitted diseases. Studies focusing on the development and evaluation of inquiry-based learning interventions, promoting the…

Development and Evaluation of the "Tigriopus" Course-Based Undergraduate Research Experience: Impacts on Students' Content Knowledge, Attitudes, and Motivation in a Majors Introductory Biology Course

ERIC Educational Resources Information Center

Olimpo, Jeffrey T.; Fisher, Ginger R.; DeChenne-Peters, Sue Ellen

2016-01-01

Within the past decade, course-based undergraduate research experiences (CUREs) have emerged as a viable mechanism to enhance novices' development of scientific reasoning and process skills in the science, technology, engineering, and mathematics disciplines. Recent evidence within the bioeducation literature suggests that student engagement in…

Engineering of protein folding and secretion-strategies to overcome bottlenecks for efficient production of recombinant proteins.

PubMed

Delic, Marizela; Göngrich, Rebecca; Mattanovich, Diethard; Gasser, Brigitte

2014-07-20

Recombinant protein production has developed into a huge market with enormous positive implications for human health and for the future direction of a biobased economy. Limitations in the economic and technical feasibility of production processes are often related to bottlenecks of in vivo protein folding. Based on cell biological knowledge, some major bottlenecks have been overcome by the overexpression of molecular chaperones and other folding related proteins, or by the deletion of deleterious pathways that may lead to misfolding, mistargeting, or degradation. While important success could be achieved by this strategy, the list of reported unsuccessful cases is disappointingly long and obviously dependent on the recombinant protein to be produced. Singular engineering of protein folding steps may not lead to desired results if the pathway suffers from several limitations. In particular, the connection between folding quality control and proteolytic degradation needs further attention. Based on recent understanding that multiple steps in the folding and secretion pathways limit productivity, synergistic combinations of the cell engineering approaches mentioned earlier need to be explored. In addition, systems biology-based whole cell analysis that also takes energy and redox metabolism into consideration will broaden the knowledge base for future rational engineering strategies.

Systems and synthetic biology approaches to alter plant cell walls and reduce biomass recalcitrance

DOE PAGES

Kalluri, Udaya C.; Yin, Hengfu; Yang, Xiaohan; ...

2014-11-03

Fine-tuning plant cell wall properties to render plant biomass more amenable to biofuel conversion is a colossal challenge. A deep knowledge of the biosynthesis and regulation of plant cell wall and a high-precision genome engineering toolset are the two essential pillars of efforts to alter plant cell walls and reduce biomass recalcitrance. The past decade has seen a meteoric rise in use of transcriptomics and high-resolution imaging methods resulting in fresh insights into composition, structure, formation and deconstruction of plant cell walls. Subsequent gene manipulation approaches, however, commonly include ubiquitous mis-expression of a single candidate gene in a host thatmore » carries an intact copy of the native gene. The challenges posed by pleiotropic and unintended changes resulting from such an approach are moving the field towards synthetic biology approaches. Finally, synthetic biology builds on a systems biology knowledge base and leverages high-precision tools for high-throughput assembly of multigene constructs and pathways, precision genome editing and site-specific gene stacking, silencing and/or removal. Here, we summarize the recent breakthroughs in biosynthesis and remodelling of major secondary cell wall components, assess the impediments in obtaining a systems-level understanding and explore the potential opportunities in leveraging synthetic biology approaches to reduce biomass recalcitrance.« less

Systems and synthetic biology approaches to alter plant cell walls and reduce biomass recalcitrance

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

Kalluri, Udaya C.; Yin, Hengfu; Yang, Xiaohan

Fine-tuning plant cell wall properties to render plant biomass more amenable to biofuel conversion is a colossal challenge. A deep knowledge of the biosynthesis and regulation of plant cell wall and a high-precision genome engineering toolset are the two essential pillars of efforts to alter plant cell walls and reduce biomass recalcitrance. The past decade has seen a meteoric rise in use of transcriptomics and high-resolution imaging methods resulting in fresh insights into composition, structure, formation and deconstruction of plant cell walls. Subsequent gene manipulation approaches, however, commonly include ubiquitous mis-expression of a single candidate gene in a host thatmore » carries an intact copy of the native gene. The challenges posed by pleiotropic and unintended changes resulting from such an approach are moving the field towards synthetic biology approaches. Finally, synthetic biology builds on a systems biology knowledge base and leverages high-precision tools for high-throughput assembly of multigene constructs and pathways, precision genome editing and site-specific gene stacking, silencing and/or removal. Here, we summarize the recent breakthroughs in biosynthesis and remodelling of major secondary cell wall components, assess the impediments in obtaining a systems-level understanding and explore the potential opportunities in leveraging synthetic biology approaches to reduce biomass recalcitrance.« less

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…

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...

Constraint methods that accelerate free-energy simulations of biomolecules.

PubMed

Perez, Alberto; MacCallum, Justin L; Coutsias, Evangelos A; Dill, Ken A

2015-12-28

Atomistic molecular dynamics simulations of biomolecules are critical for generating narratives about biological mechanisms. The power of atomistic simulations is that these are physics-based methods that satisfy Boltzmann's law, so they can be used to compute populations, dynamics, and mechanisms. But physical simulations are computationally intensive and do not scale well to the sizes of many important biomolecules. One way to speed up physical simulations is by coarse-graining the potential function. Another way is to harness structural knowledge, often by imposing spring-like restraints. But harnessing external knowledge in physical simulations is problematic because knowledge, data, or hunches have errors, noise, and combinatoric uncertainties. Here, we review recent principled methods for imposing restraints to speed up physics-based molecular simulations that promise to scale to larger biomolecules and motions.

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…

Identifying Ant-Mirid Spatial Interactions to Improve Biological Control in Cacao-Based Agroforestry System.

PubMed

Bagny Beilhe, Leïla; Piou, Cyril; Tadu, Zéphirin; Babin, Régis

2018-06-06

The use of ants for biological control of insect pests was the first reported case of conservation biological control. Direct and indirect community interactions between ants and pests lead to differential spatial pattern. We investigated spatial interactions between mirids, the major cocoa pest in West Africa and numerically dominant ant species, using bivariate point pattern analysis to identify potential biological control agents. We assume that potential biological control agents should display negative spatial interactions with mirids considering their niche overlap. The mirid/ant data were collected in complex cacao-based agroforestry systems sampled in three agroecological areas over a forest-savannah gradient in Cameroon. Three species, Crematogaster striatula Emery (Hymenoptera: Formicidae), Crematogaster clariventris Mayr (Hymenoptera: Formicidae), and Oecophylla longinoda Latreille (Hymenoptera: Formicidae) with high predator and aggressive behaviors were identified as dominant and showed negative spatial relationships with mirids. The weaver ant, O. longinoda was identified as the only potential biological control agent, considering its ubiquity in the plots, the similarity in niche requirements, and the spatial segregation with mirids resulting probably from exclusion mechanisms. Combining bivariate point pattern analysis to good knowledge of insect ecology was an effective method to identify a potentially good biological control agent.

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

A DNA-based pattern classifier with in vitro learning and associative recall for genomic characterization and biosensing without explicit sequence knowledge.

PubMed

Lee, Ju Seok; Chen, Junghuei; Deaton, Russell; Kim, Jin-Woo

2014-01-01

Genetic material extracted from in situ microbial communities has high promise as an indicator of biological system status. However, the challenge is to access genomic information from all organisms at the population or community scale to monitor the biosystem's state. Hence, there is a need for a better diagnostic tool that provides a holistic view of a biosystem's genomic status. Here, we introduce an in vitro methodology for genomic pattern classification of biological samples that taps large amounts of genetic information from all genes present and uses that information to detect changes in genomic patterns and classify them. We developed a biosensing protocol, termed Biological Memory, that has in vitro computational capabilities to "learn" and "store" genomic sequence information directly from genomic samples without knowledge of their explicit sequences, and that discovers differences in vitro between previously unknown inputs and learned memory molecules. The Memory protocol was designed and optimized based upon (1) common in vitro recombinant DNA operations using 20-base random probes, including polymerization, nuclease digestion, and magnetic bead separation, to capture a snapshot of the genomic state of a biological sample as a DNA memory and (2) the thermal stability of DNA duplexes between new input and the memory to detect similarities and differences. For efficient read out, a microarray was used as an output method. When the microarray-based Memory protocol was implemented to test its capability and sensitivity using genomic DNA from two model bacterial strains, i.e., Escherichia coli K12 and Bacillus subtilis, results indicate that the Memory protocol can "learn" input DNA, "recall" similar DNA, differentiate between dissimilar DNA, and detect relatively small concentration differences in samples. This study demonstrated not only the in vitro information processing capabilities of DNA, but also its promise as a genomic pattern classifier that could access information from all organisms in a biological system without explicit genomic information. The Memory protocol has high potential for many applications, including in situ biomonitoring of ecosystems, screening for diseases, biosensing of pathological features in water and food supplies, and non-biological information processing of memory devices, among many.

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

10 CFR 63.305 - Required characteristics of the reference biosphere.

Code of Federal Regulations, 2013 CFR

2013-01-01

... the region surrounding the Yucca Mountain site. (b) DOE should not project changes in society, the biosphere (other than climate), human biology, or increases or decreases of human knowledge or technology... vary factors related to the geology, hydrology, and climate based upon cautious, but reasonable...

10 CFR 63.305 - Required characteristics of the reference biosphere.

Code of Federal Regulations, 2014 CFR

2014-01-01

... the region surrounding the Yucca Mountain site. (b) DOE should not project changes in society, the biosphere (other than climate), human biology, or increases or decreases of human knowledge or technology... vary factors related to the geology, hydrology, and climate based upon cautious, but reasonable...

10 CFR 63.305 - Required characteristics of the reference biosphere.

Code of Federal Regulations, 2012 CFR

2012-01-01

... the region surrounding the Yucca Mountain site. (b) DOE should not project changes in society, the biosphere (other than climate), human biology, or increases or decreases of human knowledge or technology... vary factors related to the geology, hydrology, and climate based upon cautious, but reasonable...

Use of High-Throughput Testing and Approaches for Evaluating Chemical Risk-Relevance to Humans

EPA Science Inventory

ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput screening (HTS) and computational models that integrate knowledge of biological systems and in vivo toxicities. Many of these assays probe signaling pathways and cellular processes critical to...

Consumers of Mental Health Services.

ERIC Educational Resources Information Center

Roy, Alec

2001-01-01

Risk factors for suicide include psychiatric disorders, social factors, psychological factors, and biologic and genetic factors. Important knowledge about why people commit suicide has been obtained from 20 psychological autopsy studies of suicide victims carried out over the past 40 years. Based upon these studies, recommendations are offered for…

10 CFR 63.305 - Required characteristics of the reference biosphere.

Code of Federal Regulations, 2010 CFR

2010-01-01

... the region surrounding the Yucca Mountain site. (b) DOE should not project changes in society, the biosphere (other than climate), human biology, or increases or decreases of human knowledge or technology... vary factors related to the geology, hydrology, and climate based upon cautious, but reasonable...

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.

Cognitive structure and the affective domain: on knowing and feeling in biology

NASA Astrophysics Data System (ADS)

Thompson, Tressa L.; Mintzes, Joel J.

2002-06-01

This cross-age study explored the structural complexity and propositional validity of knowledge about and attitudes toward sharks, and the relationships among knowledge and attitudes. Responses were elicited from a convenience sample of students (5th, 8th and 11th grade, and college level) and senior citizens (n = 238). All subjects constructed a concept map on sharks and responded to a Likert-type attitude inventory. Based on the work of Novak and Gowin (Leaning How to Learn, Cambridge University Press, 1984), concept maps were scored for frequencies of non-redundant concepts and scientifically valid relationships, levels of hierarchy, incidence of branching and number of crosslinks. The attitude inventory, emerging from Kellert's (The Value of Life: Biological Diversity and Human Society, Island Press, 1996) work, generated subscale scores on four affective dimensions: scientific, naturalistic, moralistic and utilitarian/negative. Significant differences were found among subject groups on all knowledge structure variables and attitudinal dimensions. Gender differences were documented on three of four attitude subscales. A series of simple, mulitiple and canonical correlations revealed moderately strong relationships between knowledge structure variables and attitudinal dimensions. The pattern of these relationships supports conservation education efforts and instructional practices that encourage meaningful learning, knowledge restructuring and conceptual change (Mintzes et al., Assessing Science Understanding: A Human Constructivist View, Academic Press, 2000).

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.

Knowledge acquisition, semantic text mining, and security risks in health and biomedical informatics

PubMed Central

Huang, Jingshan; Dou, Dejing; Dang, Jiangbo; Pardue, J Harold; Qin, Xiao; Huan, Jun; Gerthoffer, William T; Tan, Ming

2012-01-01

Computational techniques have been adopted in medical and biological systems for a long time. There is no doubt that the development and application of computational methods will render great help in better understanding biomedical and biological functions. Large amounts of datasets have been produced by biomedical and biological experiments and simulations. In order for researchers to gain knowledge from original data, nontrivial transformation is necessary, which is regarded as a critical link in the chain of knowledge acquisition, sharing, and reuse. Challenges that have been encountered include: how to efficiently and effectively represent human knowledge in formal computing models, how to take advantage of semantic text mining techniques rather than traditional syntactic text mining, and how to handle security issues during the knowledge sharing and reuse. This paper summarizes the state-of-the-art in these research directions. We aim to provide readers with an introduction of major computing themes to be applied to the medical and biological research. PMID:22371823

Using student motivation to design groups in a non-majors biology course for team-based collaborative learning: Impacts on knowledge, views, attitudes, and perceptions

NASA Astrophysics Data System (ADS)

Walters, Kristi L.

The importance of student motivation and its connection to other learning variables (i.e., attitudes, knowledge, persistence, attendance) is well established. Collaborative work at the undergraduate level has been recognized as a valuable tool in large courses. However, motivation and collaborative group work have rarely been combined. This project utilized student motivation to learn biology to place non-major biology undergraduates in collaborative learning groups at East Carolina University, a mid-sized southeastern American university, to determine the effects of this construct on student learning. A pre-test measuring motivation to learn biology, attitudes toward biology, perceptions of biology and biologists, views of science, and content knowledge was administered. A similar post-test followed as part of the final exam. Two sections of the same introductory biology course (n = 312) were used and students were divided into homogeneous and heterogeneous groups (based on their motivation score). The heterogeneous groups (n = 32) consisted of a mixture of different motivation levels, while the homogeneous groups (n = 32) were organized into teams with similar motivation scores using tiers of high-, middle-, and low-level participants. Data analysis determined mixed perceptions of biology and biologists. These include the perceptions biology was less intriguing, less relevant, less practical, less ethical, and less understandable. Biologists were perceived as being neat and slightly intelligent, but not very altruistic, humane, ethical, logical, honest, or moral. Content knowledge scores more than doubled from pre- to post-test. Half of the items measuring views of science were not statistically significantly different from pre- to post-test. Many of the factors for attitudes toward biology became more agreeable from pre- to post-test. Correlations between motivation scores, participation levels, attendance rates, and final course grades were examined at both the individual and group level. Motivation had low correlations with the other variables. Changes in group membership (i.e., attrition) were evaluated at the group level and showed the highest rates with the heterogeneous groups and the lowest with the homogeneous middle groups. Group gender ratios were examined, but showed no correlation with final course grade. Linear regression was utilized to identify any variables that might be useful in predicting the final course grade of each student. Only participation, attendance, and final exam grade were predictive, but as they were components of the final course grade, they were not useful for the model. Differences between the groups were also examined to determine if the group type was predictive of final course grade, but no significant difference was found. Results of the study are discussed in the context of the literature on student motivation to learn science. Implications of the study are discussed through the lens of the Millennial generation's perspectives on teaching and learning. Millennials often consider an education to be a commodity and may expect results with less effort. Millennials may be expressing a pseudo-intrinsic motivation in order to impress peers and instructors, while they may actually be more extrinsically motivated to succeed

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 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.

The role of evolutionary biology in research and control of liver flukes in Southeast Asia.

PubMed

Echaubard, Pierre; Sripa, Banchob; Mallory, Frank F; Wilcox, Bruce A

2016-09-01

Stimulated largely by the availability of new technology, biomedical research at the molecular-level and chemical-based control approaches arguably dominate the field of infectious diseases. Along with this, the proximate view of disease etiology predominates to the exclusion of the ultimate, evolutionary biology-based, causation perspective. Yet, historically and up to today, research in evolutionary biology has provided much of the foundation for understanding the mechanisms underlying disease transmission dynamics, virulence, and the design of effective integrated control strategies. Here we review the state of knowledge regarding the biology of Asian liver Fluke-host relationship, parasitology, phylodynamics, drug-based interventions and liver Fluke-related cancer etiology from an evolutionary biology perspective. We consider how evolutionary principles, mechanisms and research methods could help refine our understanding of clinical disease associated with infection by Liver Flukes as well as their transmission dynamics. We identify a series of questions for an evolutionary biology research agenda for the liver Fluke that should contribute to an increased understanding of liver Fluke-associated diseases. Finally, we describe an integrative evolutionary medicine approach to liver Fluke prevention and control highlighting the need to better contextualize interventions within a broader human health and sustainable development framework. Copyright © 2016 Elsevier B.V. All rights reserved.

The Role of Evolutionary Biology in Research and Control of Liver Flukes in Southeast Asia

PubMed Central

Echaubard, Pierre; Sripa, Banchob; Mallory, Frank F.; Wilcox, Bruce A.

2016-01-01

Stimulated largely by the availability of new technology, biomedical research at the molecular-level and chemical-based control approaches arguably dominate the field of infectious diseases. Along with this, the proximate view of disease etiology predominates to the exclusion of the ultimate, evolutionary biology-based, causation perspective. Yet, historically and up to today, research in evolutionary biology has provided much of the foundation for understanding the mechanisms underlying disease transmission dynamics, virulence, and the design of effective integrated control strategies. Here we review the state of knowledge regarding the biology of Asian liver Fluke-host relationship, parasitology, phylodynamics, drug-based interventions and liver Fluke-related cancer etiology from an evolutionary biology perspective. We consider how evolutionary principles, mechanisms and research methods could help refine our understanding of clinical disease associated with infection by Liver Flukes as well as their transmission dynamics. We identify a series of questions for an evolutionary biology research agenda for the liver Fluke that should contribute to an increased understanding of liver Fluke-associated diseases. Finally, we describe an integrative evolutionary medicine approach to liver Fluke prevention and control highlighting the need to better contextualize interventions within a broader human health and sustainable development framework. PMID:27197053

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

Use of knowledge-sharing web-based portal in gross and microscopic anatomy.

PubMed

Durosaro, Olayemi; Lachman, Nirusha; Pawlina, Wojciech

2008-12-01

Changes in worldwide healthcare delivery require review of current medical school curricula structure to develop learning outcomes that ensures mastery of knowledge and clinical competency. In the last 3 years, Mayo Medical School implemented outcomes-based curriculum to encompass new graduate outcomes. Standard courses were replaced by 6-week clinically-integrated didactic blocks separated by student-self selected academic enrichment activities. Gross and microscopic anatomy was integrated with radiology and genetics respectively. Laboratory components include virtual microscopy and anatomical dissection. Students assigned to teams utilise computer portals to share learning experiences. High-resolution computed tomographic (CT) scans of cadavers prior to dissection were made available for correlative learning between the cadaveric material and radiologic images. Students work in teams on assigned presentations that include histology, cell and molecular biology, genetics and genomic using the Nexus Portal, based on DrupalEd, to share their observations, reflections and dissection findings. New generation of medical students are clearly comfortable utilising web-based programmes that maximise their learning potential of conceptually difficult and labor intensive courses. Team-based learning approach emphasising the use of knowledge-sharing computer portals maximises opportunities for students to master their knowledge and improve cognitive skills to ensure clinical competency.

Accessing and integrating data and knowledge for biomedical research.

PubMed

Burgun, A; Bodenreider, O

2008-01-01

To review the issues that have arisen with the advent of translational research in terms of integration of data and knowledge, and survey current efforts to address these issues. Using examples form the biomedical literature, we identified new trends in biomedical research and their impact on bioinformatics. We analyzed the requirements for effective knowledge repositories and studied issues in the integration of biomedical knowledge. New diagnostic and therapeutic approaches based on gene expression patterns have brought about new issues in the statistical analysis of data, and new workflows are needed are needed to support translational research. Interoperable data repositories based on standard annotations, infrastructures and services are needed to support the pooling and meta-analysis of data, as well as their comparison to earlier experiments. High-quality, integrated ontologies and knowledge bases serve as a source of prior knowledge used in combination with traditional data mining techniques and contribute to the development of more effective data analysis strategies. As biomedical research evolves from traditional clinical and biological investigations towards omics sciences and translational research, specific needs have emerged, including integrating data collected in research studies with patient clinical data, linking omics knowledge with medical knowledge, modeling the molecular basis of diseases, and developing tools that support in-depth analysis of research data. As such, translational research illustrates the need to bridge the gap between bioinformatics and medical informatics, and opens new avenues for biomedical informatics research.

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…

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

A Pharmacology-Based Enrichment Program for Undergraduates Promotes Interest in Science

PubMed Central

Godin, Elizabeth A.; Wormington, Stephanie V.; Perez, Tony; Barger, Michael M.; Snyder, Kate E.; Richman, Laura Smart; Schwartz-Bloom, Rochelle; Linnenbrink-Garcia, Lisa

2015-01-01

There is a strong need to increase the number of undergraduate students who pursue careers in science to provide the “fuel” that will power a science and technology–driven U.S. economy. Prior research suggests that both evidence-based teaching methods and early undergraduate research experiences may help to increase retention rates in the sciences. In this study, we examined the effect of a program that included 1) a Summer enrichment 2-wk minicourse and 2) an authentic Fall research course, both of which were designed specifically to support students' science motivation. Undergraduates who participated in the pharmacology-based enrichment program significantly improved their knowledge of basic biology and chemistry concepts; reported high levels of science motivation; and were likely to major in a biological, chemical, or biomedical field. Additionally, program participants who decided to major in biology or chemistry were significantly more likely to choose a pharmacology concentration than those majoring in biology or chemistry who did not participate in the enrichment program. Thus, by supporting students' science motivation, we can increase the number of students who are interested in science and science careers. PMID:26538389

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

Optimal network alignment with graphlet degree vectors.

PubMed

Milenković, Tijana; Ng, Weng Leong; Hayes, Wayne; Przulj, Natasa

2010-06-30

Important biological information is encoded in the topology of biological networks. Comparative analyses of biological networks are proving to be valuable, as they can lead to transfer of knowledge between species and give deeper insights into biological function, disease, and evolution. We introduce a new method that uses the Hungarian algorithm to produce optimal global alignment between two networks using any cost function. We design a cost function based solely on network topology and use it in our network alignment. Our method can be applied to any two networks, not just biological ones, since it is based only on network topology. We use our new method to align protein-protein interaction networks of two eukaryotic species and demonstrate that our alignment exposes large and topologically complex regions of network similarity. At the same time, our alignment is biologically valid, since many of the aligned protein pairs perform the same biological function. From the alignment, we predict function of yet unannotated proteins, many of which we validate in the literature. Also, we apply our method to find topological similarities between metabolic networks of different species and build phylogenetic trees based on our network alignment score. The phylogenetic trees obtained in this way bear a striking resemblance to the ones obtained by sequence alignments. Our method detects topologically similar regions in large networks that are statistically significant. It does this independent of protein sequence or any other information external to network topology.

Applications of a formal approach to decipher discrete genetic networks.

PubMed

Corblin, Fabien; Fanchon, Eric; Trilling, Laurent

2010-07-20

A growing demand for tools to assist the building and analysis of biological networks exists in systems biology. We argue that the use of a formal approach is relevant and applicable to address questions raised by biologists about such networks. The behaviour of these systems being complex, it is essential to exploit efficiently every bit of experimental information. In our approach, both the evolution rules and the partial knowledge about the structure and the behaviour of the network are formalized using a common constraint-based language. In this article our formal and declarative approach is applied to three biological applications. The software environment that we developed allows to specifically address each application through a new class of biologically relevant queries. We show that we can describe easily and in a formal manner the partial knowledge about a genetic network. Moreover we show that this environment, based on a constraint algorithmic approach, offers a wide variety of functionalities, going beyond simple simulations, such as proof of consistency, model revision, prediction of properties, search for minimal models relatively to specified criteria. The formal approach proposed here deeply changes the way to proceed in the exploration of genetic and biochemical networks, first by avoiding the usual trial-and-error procedure, and second by placing the emphasis on sets of solutions, rather than a single solution arbitrarily chosen among many others. Last, the constraint approach promotes an integration of model and experimental data in a single framework.

Welcome to Nanoscience: Interdisciplinary Environmental Explorations, Grades 9-12

ERIC Educational Resources Information Center

Madden, Andrew S.; Hochella, Michael F., Jr.; Glasson, George E.; Grady, Julie R.; Bank, Tracy L.; Green, Andre M.; Norris, Mary A.; Hurst, Andrew N.; Eriksson, Susan C.

2011-01-01

In a society where technology plays an ever-increasing role, students' ability to understand the underlying science and make smart social and environmental decisions based on that knowledge is crucial. "Welcome to Nanoscience" helps biology, chemistry, and Earth science teachers introduce the revolutionary fields of nanoscience and nanotechnology…

Short-Term Environmental Education--Does It Work?--An Evaluation of the "Green Classroom"

ERIC Educational Resources Information Center

Drissner, Jurgen; Haase, Hans-Martin; Hille, Katrin

2010-01-01

The "Green Classroom" in Ulm is an experiential learning forum outside school. Its educational concept is based on experimental learning and is geared towards expanding biological knowledge and developing environmental attitudes regarding preservation and utilisation of nature. We assessed the environmental attitude of 92 students before…

Short-Term Environmental Education: Long-Term Effectiveness?

ERIC Educational Resources Information Center

Drissner, Jürgen Reinhold; Haase, Hans-Martin; Wittig, Susanne; Hille, Katrin

2014-01-01

The "Green Classroom" in the Botanical Garden of the University of Ulm is a learning forum outdoor school that is used by about 2500 school students annually. Its educational concept is based on experiential learning and is geared towards expanding students' biological knowledge and developing positive attitudes towards small animals and…

Relationships between Prospective Elementary Teachers' Classroom Practice and Their Conceptions of Biology and of Teaching Science.

ERIC Educational Resources Information Center

Meyer, Helen; Tabachnick, B. Robert; Hewson, Peter W.; Lemberger, John; Park, Hyun-Ju

1999-01-01

Discusses three prospective elementary teachers' conceptions of teaching science and selected portions of their knowledge base in life science. Explores how these teachers' conceptions, along with their teaching actions, developed during the course of a teacher-education program. Contains 21 references. (Author/WRM)

Exploitation of biotechnology in a large company.

PubMed

Dart, E C

1989-08-31

Almost from the outset, most large companies saw the 'new biotechnology' not as a new business but as a set of very powerful techniques that, in time, would radically improve the understanding of biological systems. This new knowledge was generally seen by them as enhancing the process of invention and not as a substitute for tried and tested ways of meeting clearly identified targets. As the knowledge base grows, so the big-company response to biotechnology becomes more positive. Within ICI, biotechnology is now integrated into five bio-businesses (Pharmaceuticals, Agrochemicals, Seeds, Diagnostics and Biological Products). Within the Central Toxicology Laboratory it also contributes to the understanding of the mechanisms of toxic action of chemicals as part of assessing risk. ICI has entered two of these businesses (Seeds and Diagnostics) because it sees biotechnology making a major contribution to the profitability of each.

Visual Literacy in Preservice Teachers: a Case Study in Biology

NASA Astrophysics Data System (ADS)

Ruiz-Gallardo, José Reyes; García Fernández, Beatriz; Mateos Jiménez, Antonio

2017-07-01

In this study, we explore the competence of preservice teachers (n = 161) in labelling and creating new cross-sectional human diagrams, based on anatomy knowledge depicted in longitudinal sections. Using educational standards to assess visual literacy and ad hoc open questions, results indicate limited skills for both tasks. However, their competence is particularly poor creating diagrams, where shortcomings were observed not only in visual literacy but in content knowledge. We discuss the misconceptions detected during these assessments. Visual literacy training should be strengthened for these students, as it is a skill that is especially important for future teachers to use in learning, assessing, and reflecting on content in science education. This is particularly important in preservice teachers since they should be fluent in the use of visual teaching tools in teaching anatomy and other content in the biology curriculum.

A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool.

PubMed

Mazandu, Gaston K; Chimusa, Emile R; Mbiyavanga, Mamana; Mulder, Nicola J

2016-02-01

Gene Ontology (GO) semantic similarity measures are being used for biological knowledge discovery based on GO annotations by integrating biological information contained in the GO structure into data analyses. To empower users to quickly compute, manipulate and explore these measures, we introduce A-DaGO-Fun (ADaptable Gene Ontology semantic similarity-based Functional analysis). It is a portable software package integrating all known GO information content-based semantic similarity measures and relevant biological applications associated with these measures. A-DaGO-Fun has the advantage not only of handling datasets from the current high-throughput genome-wide applications, but also allowing users to choose the most relevant semantic similarity approach for their biological applications and to adapt a given module to their needs. A-DaGO-Fun is freely available to the research community at http://web.cbio.uct.ac.za/ITGOM/adagofun. It is implemented in Linux using Python under free software (GNU General Public Licence). gmazandu@cbio.uct.ac.za or Nicola.Mulder@uct.ac.za 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.

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

Science Goals in Radiation Protection for Exploration

NASA Technical Reports Server (NTRS)

Cucinotta, Francs A.

2008-01-01

Space radiation presents major challenges to future missions to the Earth s moon or Mars. Health risks of concern include cancer, degenerative and performance risks to the central nervous system, heart and lens, and the acute radiation syndromes. The galactic cosmic rays (GCR) contain high energy and charge (HZE) nuclei, which have been shown to cause qualitatively distinct biological damage compared to terresterial radiation, such as X-rays or gamma-rays, causing risk estimates to be highly uncertain. The biological effects of solar particle events (SPE) are similar to terresterial radiation except for their biological dose-rate modifiers; however the onset and size of SPEs are difficult to predict. The high energies of GCR reduce the effectiveness of shielding, while SPE s can be shielded however the current gap in radiobiological knowledge hinders optimization. Methods used to project risks on Earth must be modified because of the large uncertainties in projecting health risks from space radiation, and thus impact mission requirements and costs. We describe NASA s unique approach to radiation safety that applies probabilistic risk assessments and uncertainty based criteria within the occupational health program for astronauts and to mission design. The two terrestrial criteria of a point estimate of maximum acceptable level of risk and application of the principle of As Low As Reasonably Achievable (ALARA) are supplemented by a third requirement that protects against risk projection uncertainties using the upper 95% confidence level (CL) in radiation risk projection models. Exploration science goals in radiation protection are centered on ground-based research to achieve the necessary biological knowledge, and in the development of new technologies to improve SPE monitoring and optimize shielding. Radiobiology research is centered on a ground based program investigating the radiobiology of high-energy protons and HZE nuclei at the NASA Space Radiation Laboratory (NSRL) located at DoE s Brookhaven National Laboratory in Upton, NY. We describe recent NSRL results that are closing the knowledge gap in HZE radiobiology and improving exploration risk estimates. Linking probabilistic risk assessment to research goals makes it possible to express risk management objectives in terms of quantitative metrics, which include the number of days in space without exceeding a given risk level within well defined confidence limits, and probabilistic assessments of the effectiveness of design trade spaces such as material type, mass, solar cycle, crew selection criteria, and biological countermeasures. New research in SPE alert and risk assessment, individual radiation sensitivity, and biological countermeasure development are described.

Evaluating the effectiveness of a practical inquiry-based learning bioinformatics module on undergraduate student engagement and applied skills.

PubMed

Brown, James A L

2016-05-06

A pedagogic intervention, in the form of an inquiry-based peer-assisted learning project (as a practical student-led bioinformatics module), was assessed for its ability to increase students' engagement, practical bioinformatic skills and process-specific knowledge. Elements assessed were process-specific knowledge following module completion, qualitative student-based module evaluation and the novelty, scientific validity and quality of written student reports. Bioinformatics is often the starting point for laboratory-based research projects, therefore high importance was placed on allowing students to individually develop and apply processes and methods of scientific research. Students led a bioinformatic inquiry-based project (within a framework of inquiry), discovering, justifying and exploring individually discovered research targets. Detailed assessable reports were produced, displaying data generated and the resources used. Mimicking research settings, undergraduates were divided into small collaborative groups, with distinctive central themes. The module was evaluated by assessing the quality and originality of the students' targets through reports, reflecting students' use and understanding of concepts and tools required to generate their data. Furthermore, evaluation of the bioinformatic module was assessed semi-quantitatively using pre- and post-module quizzes (a non-assessable activity, not contributing to their grade), which incorporated process- and content-specific questions (indicative of their use of the online tools). Qualitative assessment of the teaching intervention was performed using post-module surveys, exploring student satisfaction and other module specific elements. Overall, a positive experience was found, as was a post module increase in correct process-specific answers. In conclusion, an inquiry-based peer-assisted learning module increased students' engagement, practical bioinformatic skills and process-specific knowledge. © 2016 by The International Union of Biochemistry and Molecular Biology, 44:304-313 2016. © 2016 The International Union of Biochemistry and Molecular Biology.

From gene to protein: A 3-week intensive course in molecular biology for physical scientists.

PubMed

Nadeau, Jay L

2009-07-01

This article describes a 3-week intensive molecular biology methods course based upon fluorescent proteins, which is successfully taught at the McGill University to advanced undergraduates and graduates in physics, chemical engineering, biomedical engineering, and medicine. No previous knowledge of biological terminology or methods is expected, so the material could readily be adapted to earlier undergraduates or students in other fields. The course emphasizes hands-on experience with one half-hour of lecture and 3 and a half hours of laboratory 4 days per week, for a total of 39 hours. The materials are simple and low in cost and all software used is free, making the budget accessible to small universities and community colleges that possess basic teaching wet labs. Conceptual understanding is reinforced with lab reports and an independent final paper on a subject of the student's choice. The final paper describes a possible thesis project, not necessarily the student's own, with assessment based upon grasping of key concepts and methods of molecular biology. Copyright © 2009 International Union of Biochemistry and Molecular Biology, Inc.

Biologically Based Methods for Pest Management in Agriculture under Changing Climates: Challenges and Future Directions.

PubMed

Chidawanyika, Frank; Mudavanhu, Pride; Nyamukondiwa, Casper

2012-11-09

The current changes in global climatic regimes present a significant societal challenge, affecting in all likelihood insect physiology, biochemistry, biogeography and population dynamics. With the increasing resistance of many insect pest species to chemical insecticides and an increasing organic food market, pest control strategies are slowly shifting towards more sustainable, ecologically sound and economically viable options. Biologically based pest management strategies present such opportunities through predation or parasitism of pests and plant direct or indirect defense mechanisms that can all be important components of sustainable integrated pest management programs. Inevitably, the efficacy of biological control systems is highly dependent on natural enemy-prey interactions, which will likely be modified by changing climates. Therefore, knowledge of how insect pests and their natural enemies respond to climate variation is of fundamental importance in understanding biological insect pest management under global climate change. Here, we discuss biological control, its challenges under climate change scenarios and how increased global temperatures will require adaptive management strategies to cope with changing status of insects and their natural enemies.

Development and implementation of an expert system to improve the control of nitrification and denitrification in the Vic wastewater treatment plant.

PubMed

Ribas, F; Rodríguez-Roda, I; Serrat, J; Clara, P; Comas, J

2008-05-01

Wastewater treatment plants employ various physical, chemical and biological processes to reduce pollutants from raw wastewater. One of the most important is the biological nitrogen removal process through nitrification and denitrification steps taking place in various sections of the biological reactor. One of the most extensively used configurations to achieve the biological nitrogen removal is an activated sludge system using oxidation ditch or extended aeration. To improve nitrogen removal in the wastewater treatment plant (WWTP) of Vic (Catalonia, NE Spain), the automatic aeration control system was complemented with an Expert System to always provide the most appropriate aeration or anoxia sequence based on the values of ammonium and nitrates given by an automatic analyzer. This article illustrates the development and implementation of this knowledge-based system within the framework of a Decision Support System, which performs SCADA functions. The paper also shows that the application of the decision support system in the Vic WWTP resulted in significant improvements to the biological nitrogen removal.

Biological and Psychosocial Predictors of Postpartum Depression: Systematic Review and Call for Integration

PubMed Central

Tanner Stapleton, Lynlee R.; Guardino, Christine M.; Hahn-Holbrook, Jennifer; Schetter, Christine Dunkel

2017-01-01

Postpartum depression (PPD) adversely affects the health and well being of many new mothers, their infants, and their families. A comprehensive understanding of biopsychosocial precursors to PPD is needed to solidify the current evidence base for best practices in translation. We conducted a systematic review of research published from 2000 through 2013 on biological and psychosocial factors associated with PPD and postpartum depressive symptoms. Two hundred fourteen publications based on 199 investigations of 151,651 women in the first postpartum year met inclusion criteria. The biological and psychosocial literatures are largely distinct, and few studies provide integrative analyses. The strongest PPD risk predictors among biological processes are hypothalamic-pituitary-adrenal dysregulation, inflammatory processes, and genetic vulnerabilities. Among psychosocial factors, the strongest predictors are severe life events, some forms of chronic strain, relationship quality, and support from partner and mother. Fully integrated biopsychosocial investigations with large samples are needed to advance our knowledge of PPD etiology. PMID:25822344

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…

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.

Blackboard architecture for medical image interpretation

NASA Astrophysics Data System (ADS)

Davis, Darryl N.; Taylor, Christopher J.

1991-06-01

There is a growing interest in using sophisticated knowledge-based systems for biomedical image interpretation. We present a principled attempt to use artificial intelligence methodologies in interpreting lateral skull x-ray images. Such radiographs are routinely used in cephalometric analysis to provide quantitative measurements useful to clinical orthodontists. Manual and interactive methods of analysis are known to be error prone and previous attempts to automate this analysis typically fail to capture the expertise and adaptability required to cope with the variability in biological structure and image quality. An integrated model-based system has been developed which makes use of a blackboard architecture and multiple knowledge sources. A model definition interface allows quantitative models, of feature appearance and location, to be built from examples as well as more qualitative modelling constructs. Visual task definition and blackboard control modules allow task-specific knowledge sources to act on information available to the blackboard in a hypothesise and test reasoning cycle. Further knowledge-based modules include object selection, location hypothesis, intelligent segmentation, and constraint propagation systems. Alternative solutions to given tasks are permitted.

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)

German National Proficiency Scales in Biology: Internal Structure, Relations to General Cognitive Abilities and Verbal Skills

PubMed Central

KÖLLER, OLAF

2016-01-01

ABSTRACT National and international large‐scale assessments (LSA) have a major impact on educational systems, which raises fundamental questions about the validity of the measures regarding their internal structure and their relations to relevant covariates. Given its importance, research on the validity of instruments specifically developed for LSA is still sparse, especially in science and its subdomains biology, chemistry, and physics. However, policy decisions for the improvement of educational quality based on LSA can only be helpful if valid information on students’ achievement levels is provided. In the present study, the nature of the measurement instruments based on the German Educational Standards in Biology is examined. On the basis of data from 3,165 students in Grade 10, we present dimensional analyses and report the relationship between different subdimensions of biology literacy and cognitive covariates such as general cognitive abilities and verbal skills. A theory‐driven two‐dimensional model fitted the data best. Content knowledge and scientific inquiry, two subdimensions of biology literacy, are highly correlated and show differential correlational patterns to the covariates. We argue that the underlying structure of biology should be incorporated into curricula, teacher training and future assessments. PMID:27818532

German National Proficiency Scales in Biology: Internal Structure, Relations to General Cognitive Abilities and Verbal Skills.

PubMed

Kampa, Nele; Köller, Olaf

2016-09-01

National and international large-scale assessments (LSA) have a major impact on educational systems, which raises fundamental questions about the validity of the measures regarding their internal structure and their relations to relevant covariates. Given its importance, research on the validity of instruments specifically developed for LSA is still sparse, especially in science and its subdomains biology, chemistry, and physics. However, policy decisions for the improvement of educational quality based on LSA can only be helpful if valid information on students' achievement levels is provided. In the present study, the nature of the measurement instruments based on the German Educational Standards in Biology is examined. On the basis of data from 3,165 students in Grade 10, we present dimensional analyses and report the relationship between different subdimensions of biology literacy and cognitive covariates such as general cognitive abilities and verbal skills. A theory-driven two-dimensional model fitted the data best. Content knowledge and scientific inquiry, two subdimensions of biology literacy, are highly correlated and show differential correlational patterns to the covariates. We argue that the underlying structure of biology should be incorporated into curricula, teacher training and future assessments.

Ames Life Science Data Archive: Translational Rodent Research at Ames

NASA Technical Reports Server (NTRS)

Wood, Alan E.; French, Alison J.; Ngaotheppitak, Ratana; Leung, Dorothy M.; Vargas, Roxana S.; Maese, Chris; Stewart, Helen

2014-01-01

The Life Science Data Archive (LSDA) office at Ames is responsible for collecting, curating, distributing and maintaining information pertaining to animal and plant experiments conducted in low earth orbit aboard various space vehicles from 1965 to present. The LSDA will soon be archiving data and tissues samples collected on the next generation of commercial vehicles; e.g., SpaceX & Cygnus Commercial Cargo Craft. To date over 375 rodent flight experiments with translational application have been archived by the Ames LSDA office. This knowledge base of fundamental research can be used to understand mechanisms that affect higher organisms in microgravity and help define additional research whose results could lead the way to closing gaps identified by the Human Research Program (HRP). This poster will highlight Ames contribution to the existing knowledge base and how the LSDA can be a resource to help answer the questions surrounding human health in long duration space exploration. In addition, it will illustrate how this body of knowledge was utilized to further our understanding of how space flight affects the human system and the ability to develop countermeasures that negate the deleterious effects of space flight. The Ames Life Sciences Data Archive (ALSDA) includes current descriptions of over 700 experiments conducted aboard the Shuttle, International Space Station (ISS), NASA/MIR, Bion/Cosmos, Gemini, Biosatellites, Apollo, Skylab, Russian Foton, and ground bed rest studies. Research areas cover Behavior and Performance, Bone and Calcium Physiology, Cardiovascular Physiology, Cell and Molecular Biology, Chronobiology, Developmental Biology, Endocrinology, Environmental Monitoring, Gastrointestinal Physiology, Hematology, Immunology, Life Support System, Metabolism and Nutrition, Microbiology, Muscle Physiology, Neurophysiology, Pharmacology, Plant Biology, Pulmonary Physiology, Radiation Biology, Renal, Fluid and Electrolyte Physiology, and Toxicology. These experiment descriptions and data can be accessed online via the public LSDA website (http://lsda.jsc.nasa.gov) and information can be requested via the Data Request form at http://lsda.jsc.nasa.gov/common/dataRequest/dataRequest.aspx or by contacting the ALSDA Office at: Alison.J.French@nasa.gov

[Application of microelectronics CAD tools to synthetic biology].

PubMed

Madec, Morgan; Haiech, Jacques; Rosati, Élise; Rezgui, Abir; Gendrault, Yves; Lallement, Christophe

2017-02-01

Synthetic biology is an emerging science that aims to create new biological functions that do not exist in nature, based on the knowledge acquired in life science over the last century. Since the beginning of this century, several projects in synthetic biology have emerged. The complexity of the developed artificial bio-functions is relatively low so that empirical design methods could be used for the design process. Nevertheless, with the increasing complexity of biological circuits, this is no longer the case and a large number of computer aided design softwares have been developed in the past few years. These tools include languages for the behavioral description and the mathematical modelling of biological systems, simulators at different levels of abstraction, libraries of biological devices and circuit design automation algorithms. All of these tools already exist in other fields of engineering sciences, particularly in microelectronics. This is the approach that is put forward in this paper. © 2017 médecine/sciences – Inserm.

Building a developmental toxicity ontology.

PubMed

Baker, Nancy; Boobis, Alan; Burgoon, Lyle; Carney, Edward; Currie, Richard; Fritsche, Ellen; Knudsen, Thomas; Laffont, Madeleine; Piersma, Aldert H; Poole, Alan; Schneider, Steffen; Daston, George

2018-04-03

As more information is generated about modes of action for developmental toxicity and more data are generated using high-throughput and high-content technologies, it is becoming necessary to organize that information. This report discussed the need for a systematic representation of knowledge about developmental toxicity (i.e., an ontology) and proposes a method to build one based on knowledge of developmental biology and mode of action/ adverse outcome pathways in developmental toxicity. This report is the result of a consensus working group developing a plan to create an ontology for developmental toxicity that spans multiple levels of biological organization. This report provide a description of some of the challenges in building a developmental toxicity ontology and outlines a proposed methodology to meet those challenges. As the ontology is built on currently available web-based resources, a review of these resources is provided. Case studies on one of the most well-understood morphogens and developmental toxicants, retinoic acid, are presented as examples of how such an ontology might be developed. This report outlines an approach to construct a developmental toxicity ontology. Such an ontology will facilitate computer-based prediction of substances likely to induce human developmental toxicity. © 2018 Wiley Periodicals, Inc.

Trends in Modern Drug Discovery.

PubMed

Eder, Jörg; Herrling, Paul L

2016-01-01

Drugs discovered by the pharmaceutical industry over the past 100 years have dramatically changed the practice of medicine and impacted on many aspects of our culture. For many years, drug discovery was a target- and mechanism-agnostic approach that was based on ethnobotanical knowledge often fueled by serendipity. With the advent of modern molecular biology methods and based on knowledge of the human genome, drug discovery has now largely changed into a hypothesis-driven target-based approach, a development which was paralleled by significant environmental changes in the pharmaceutical industry. Laboratories became increasingly computerized and automated, and geographically dispersed research sites are now more and more clustered into large centers to capture technological and biological synergies. Today, academia, the regulatory agencies, and the pharmaceutical industry all contribute to drug discovery, and, in order to translate the basic science into new medical treatments for unmet medical needs, pharmaceutical companies have to have a critical mass of excellent scientists working in many therapeutic fields, disciplines, and technologies. The imperative for the pharmaceutical industry to discover breakthrough medicines is matched by the increasing numbers of first-in-class drugs approved in recent years and reflects the impact of modern drug discovery approaches, technologies, and genomics.

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.

Systems and synthetic biology approaches to alter plant cell walls and reduce biomass recalcitrance.

PubMed

Kalluri, Udaya C; Yin, Hengfu; Yang, Xiaohan; Davison, Brian H

2014-12-01

Fine-tuning plant cell wall properties to render plant biomass more amenable to biofuel conversion is a colossal challenge. A deep knowledge of the biosynthesis and regulation of plant cell wall and a high-precision genome engineering toolset are the two essential pillars of efforts to alter plant cell walls and reduce biomass recalcitrance. The past decade has seen a meteoric rise in use of transcriptomics and high-resolution imaging methods resulting in fresh insights into composition, structure, formation and deconstruction of plant cell walls. Subsequent gene manipulation approaches, however, commonly include ubiquitous mis-expression of a single candidate gene in a host that carries an intact copy of the native gene. The challenges posed by pleiotropic and unintended changes resulting from such an approach are moving the field towards synthetic biology approaches. Synthetic biology builds on a systems biology knowledge base and leverages high-precision tools for high-throughput assembly of multigene constructs and pathways, precision genome editing and site-specific gene stacking, silencing and/or removal. Here, we summarize the recent breakthroughs in biosynthesis and remodelling of major secondary cell wall components, assess the impediments in obtaining a systems-level understanding and explore the potential opportunities in leveraging synthetic biology approaches to reduce biomass recalcitrance. Published 2014. This article is a U.S. Government work and is in the public domain in the USA. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

ATHENA: A knowledge-based hybrid backpropagation-grammatical evolution neural network algorithm for discovering epistasis among quantitative trait Loci

PubMed Central

2010-01-01

Background Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritability in highly studied complex traits has been explained by genetic variation. Non-additive gene-gene interactions, which are not often explored, are thought to be one source of this "missing" heritability. Methods Stochastic methods employing evolutionary algorithms have demonstrated promise in being able to detect and model gene-gene and gene-environment interactions that influence human traits. Here we demonstrate modifications to a neural network algorithm in ATHENA (the Analysis Tool for Heritable and Environmental Network Associations) resulting in clear performance improvements for discovering gene-gene interactions that influence human traits. We employed an alternative tree-based crossover, backpropagation for locally fitting neural network weights, and incorporation of domain knowledge obtainable from publicly accessible biological databases for initializing the search for gene-gene interactions. We tested these modifications in silico using simulated datasets. Results We show that the alternative tree-based crossover modification resulted in a modest increase in the sensitivity of the ATHENA algorithm for discovering gene-gene interactions. The performance increase was highly statistically significant when backpropagation was used to locally fit NN weights. We also demonstrate that using domain knowledge to initialize the search for gene-gene interactions results in a large performance increase, especially when the search space is larger than the search coverage. Conclusions We show that a hybrid optimization procedure, alternative crossover strategies, and incorporation of domain knowledge from publicly available biological databases can result in marked increases in sensitivity and performance of the ATHENA algorithm for detecting and modelling gene-gene interactions that influence a complex human trait. PMID:20875103

BioTextQuest: a web-based biomedical text mining suite for concept discovery.

PubMed

Papanikolaou, Nikolas; Pafilis, Evangelos; Nikolaou, Stavros; Ouzounis, Christos A; Iliopoulos, Ioannis; Promponas, Vasilis J

2011-12-01

BioTextQuest combines automated discovery of significant terms in article clusters with structured knowledge annotation, via Named Entity Recognition services, offering interactive user-friendly visualization. A tag-cloud-based illustration of terms labeling each document cluster are semantically annotated according to the biological entity, and a list of document titles enable users to simultaneously compare terms and documents of each cluster, facilitating concept association and hypothesis generation. BioTextQuest allows customization of analysis parameters, e.g. clustering/stemming algorithms, exclusion of documents/significant terms, to better match the biological question addressed. http://biotextquest.biol.ucy.ac.cy vprobon@ucy.ac.cy; iliopj@med.uoc.gr Supplementary data are available at Bioinformatics online.

Inquiry-based examination of chemical disruption of bacterial biofilms.

PubMed

Redelman, Carly V; Hawkins, Misty A W; Drumwright, Franklin R; Ransdell, Beverly; Marrs, Kathleen; Anderson, Gregory G

2012-01-01

Inquiry-based instruction in the sciences has been demonstrated as a successful educational strategy to use for both high school and college science classrooms. As participants in the NSF Graduate STEM Fellows in K-12 Education (GK-12) Program, we were tasked with creating novel inquiry-based activities for high school classrooms. As a way to introduce microbiology, molecular biology, ecology, and human health to students, we created a laboratory activity involving formation of biofilms composed of environmental bacteria from pond water and investigation into the resistance of these biofilms to antimicrobial agents. Two high schools participated in this study in different ways. Pike High School biology and advanced environmental science classrooms obtained pond water samples and grew biofilms from the bacteria in the pond water on plastic plates. They also observed killing of these biofilms by common household antimicrobial agents. As a senior capstone project, students at Arsenal Technical High School built on these research findings by isolating two different bacterial strains from the pond water and demonstrating the stimulatory effect of ethanol on biofilms formed by isolated bacterial strains. These activities were successful at introducing complex biological topics to high school students in a unique and exciting way. The students scored significantly higher on postactivity surveys compared with preactivity surveys that measured microbiology knowledge and experimental design knowledge. Furthermore, these projects seemed to elicit an excitement for science in the students who participated. Copyright © 2012 Wiley Periodicals, Inc.

The molecular biology of inflammatory bowel diseases.

PubMed

Corfield, Anthony P; Wallace, Heather M; Probert, Chris S J

2011-08-01

IBDs (inflammatory bowel diseases) are a group of diseases affecting the gastrointestinal tract. The diseases are multifactorial and cover genetic aspects: susceptibility genes, innate and adaptive responses to inflammation, and structure and efficacy of the mucosal protective barrier. Animal models of IBD have been developed to gain further knowledge of the disease mechanisms. These topics form an overlapping background to enable an improved understanding of the molecular features of these diseases. A series of articles is presented based on the topics covered at the Biochemical Society Focused Meeting The Molecular Biology of Inflammatory Bowel Diseases.

[Habitability and biological life support systems for man].

PubMed

Gazenko, O G; Grigor'ev, A I; Meleshko, G I; Shepelev, E Ia

1990-01-01

This paper discusses general concepts and specific details of the habitability of space stations and planetary bases completely isolated from the Earth for long periods of time. It emphasizes inadequacy of the present-day knowledge about natural conditions that provide a biologically acceptable environment on the Earth as well as lack of information about life support systems as a source of consumables (oxygen, water, food) and a tool for waste management. The habitability of advanced space vehicles is closely related to closed bioregenerative systems used as life support systems.

Physical Activity and Movement Proficiency: The Need for a Biocultural Approach.

PubMed

Malina, Robert M; Cumming, Sean P; Coelho E Silva, Manuel J

2016-05-01

"Gaps in Our Knowledge" are discussed in the context of the need to integrate biological and behavioral factors in a biocultural approach to physical activity and movement proficiency. Specific issues considered include outdoor play, organized and informal activity, biological maturation, tracking of activity, development of movement proficiency, and individual differences. Studies considered are largely based on youth in economically better-off, developed countries in the western culture context. There is a need to extend studies of physical activity and movement proficiency to different cultural contexts.

Novel and rare prenyllipids - Occurrence and biological activity.

PubMed

Szymańska, Renata; Kruk, Jerzy

2018-01-01

The data presented indicate that there is a variety of unique prenyllipids, often of very limited taxonomic distribution, whose origin, biosynthesis, metabolism and biological function deserves to be elucidated. These compounds include tocoenols, tocochromanol esters, tocochromanol acids, plastoquinones and ubiquinones. Additionally, based on the available data, it can be assumed that there are still unrecognized prenyllipids, like prenylquinols fatty acid esters of the hydroquinone ring, including prenylquinol phosphates, and others, whose biological function might be of great importance. Our knowledge of these compounds is not only important from the scientific point of view, but may also be of practical significance to medicine, pharmacy or cosmetics. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Prevention and treatment of tuberculosis infection in candidates for biologic therapy: A multidisciplinary consensus statement adapted to the dermatology patient.

PubMed

Rodríguez-Jiménez, P; Mir-Viladrich, I; Chicharro, P; Solano-López, G; López-Longo, F J; Taxonera, C; Sánchez-Martínez, P; Martínez-Lacasa, X; García-Gasalla, M; Dorca, J; Arias-Guillén, M; García-García, J M; Dauden, E

2018-06-02

Patients with chronic inflammatory diseases being treated with immunosuppressive drugs, and with tumor necrosis factor inhibitors in particular, have an increased risk of infection by Mycobacterium tuberculosis. Screening for latent tuberculosis infection and preventive therapy to reduce the risk of progression to active tuberculosis are mandatory in this group of patients. This updated multidisciplinary consensus document presents the latest expert opinions on the treatment and prevention of tuberculosis in candidates for biologic therapy and establishes recommendations based on current knowledge relating to the use of biologic agents. Copyright © 2018 AEDV. Publicado por Elsevier España, S.L.U. All rights reserved.

Into the field: naturalistic education and the future of conservation.

PubMed

Hayes, Mark A

2009-10-01

Some educational psychologists and researchers have argued that there are multiple ways of being intelligent. In the early 1980s, Howard Gardner presented a theory of multiple intelligences by proposing that humans can be described not by a single kind of intelligence, or intelligence quotient score, but rather by a variety of kinds of intelligence. This idea of considering multiple views of intelligence has helped educators look at intelligence from a less rigid, more expansive perspective. I considered how the relatively new concept of naturalistic intelligence, which is the cognitive potential to process information that is exhibited by expert naturalists, might influence the design of undergraduate biology curricula. Naturalistic intelligence can be fostered in undergraduate biology students by emphasizing the need for well-rounded scientific naturalists; developing curricula that involves students in outdoor inquiry-based projects; and helping students learn how to observe both the natural world and their own learning, skills that are essential to developing expert naturalistic knowledge. Professors, graduate students, and administrators can improve the naturalistic intelligence of undergraduate biology students by giving these students opportunities to be involved in outdoor research. Time spent outdoors alone and among people with expertise in natural history, ecology, and conservation biology will have important influences on the knowledge and skills biology undergraduates learn, the careers they pursue, and the contributions they make to conserving Earth's biodiversity.

Mesoscale Eddies Are Oases for Higher Trophic Marine Life

PubMed Central

Godø, Olav R.; Samuelsen, Annette; Macaulay, Gavin J.; Patel, Ruben; Hjøllo, Solfrid Sætre; Horne, John; Kaartvedt, Stein; Johannessen, Johnny A.

2012-01-01

Mesoscale eddies stimulate biological production in the ocean, but knowledge of energy transfers to higher trophic levels within eddies remains fragmented and not quantified. Increasing the knowledge base is constrained by the inability of traditional sampling methods to adequately sample biological processes at the spatio-temporal scales at which they occur. By combining satellite and acoustic observations over spatial scales of 10 s of km horizontally and 100 s of m vertically, supported by hydrographical and biological sampling we show that anticyclonic eddies shape distribution and density of marine life from the surface to bathyal depths. Fish feed along density structures of eddies, demonstrating that eddies catalyze energy transfer across trophic levels. Eddies create attractive pelagic habitats, analogous to oases in the desert, for higher trophic level aquatic organisms through enhanced 3-D motion that accumulates and redistributes biomass, contributing to overall bioproduction in the ocean. Integrating multidisciplinary observation methodologies promoted a new understanding of biophysical interaction in mesoscale eddies. Our findings emphasize the impact of eddies on the patchiness of biomass in the sea and demonstrate that they provide rich feeding habitat for higher trophic marine life. PMID:22272294

Patterns of thinking about phylogenetic trees: A study of student learning and the potential of tree thinking to improve comprehension of biological concepts

NASA Astrophysics Data System (ADS)

Naegle, Erin

Evolution education is a critical yet challenging component of teaching and learning biology. There is frequently an emphasis on natural selection when teaching about evolution and conducting educational research. A full understanding of evolution, however, integrates evolutionary processes, such as natural selection, with the resulting evolutionary patterns, such as species divergence. Phylogenetic trees are models of evolutionary patterns. The perspective gained from understanding biology through phylogenetic analyses is referred to as tree thinking. Due to the increasing prevalence of tree thinking in biology, understanding how to read phylogenetic trees is an important skill for students to learn. Interpreting graphics is not an intuitive process, as graphical representations are semiotic objects. This is certainly true concerning phylogenetic tree interpretation. Previous research and anecdotal evidence report that students struggle to correctly interpret trees. The objective of this research was to describe and investigate the rationale underpinning the prior knowledge of introductory biology students' tree thinking Understanding prior knowledge is valuable as prior knowledge influences future learning. In Chapter 1, qualitative methods such as semi-structured interviews were used to explore patterns of student rationale in regard to tree thinking. Seven common tree thinking misconceptions are described: (1) Equating the degree of trait similarity with the extent of relatedness, (2) Environmental change is a necessary prerequisite to evolution, (3) Essentialism of species, (4) Evolution is inherently progressive, (5) Evolution is a linear process, (6) Not all species are related, and (7) Trees portray evolution through the hybridization of species. These misconceptions are based in students' incomplete or incorrect understanding of evolution. These misconceptions are often reinforced by the misapplication of cultural conventions to make sense of trees. Chapter 2 explores the construction, validity, and reliability of a tree thinking concept inventory. Concept inventories are research based instruments that diagnose faulty reasoning among students. Such inventories are tools for improving teaching and learning of concepts. Test scores indicate that tree thinking misconceptions are held by novice and intermediate biology students. Finally, Chapter 3 presents a tree thinking rubric. The rubric aids teachers in selecting and improving introductory tree thinking learning exercises that address students' tree thinking misconceptions.

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

A Bayesian approach to estimating hidden variables as well as missing and wrong molecular interactions in ordinary differential equation-based mathematical models.

PubMed

Engelhardt, Benjamin; Kschischo, Maik; Fröhlich, Holger

2017-06-01

Ordinary differential equations (ODEs) are a popular approach to quantitatively model molecular networks based on biological knowledge. However, such knowledge is typically restricted. Wrongly modelled biological mechanisms as well as relevant external influence factors that are not included into the model are likely to manifest in major discrepancies between model predictions and experimental data. Finding the exact reasons for such observed discrepancies can be quite challenging in practice. In order to address this issue, we suggest a Bayesian approach to estimate hidden influences in ODE-based models. The method can distinguish between exogenous and endogenous hidden influences. Thus, we can detect wrongly specified as well as missed molecular interactions in the model. We demonstrate the performance of our Bayesian dynamic elastic-net with several ordinary differential equation models from the literature, such as human JAK-STAT signalling, information processing at the erythropoietin receptor, isomerization of liquid α -Pinene, G protein cycling in yeast and UV-B triggered signalling in plants. Moreover, we investigate a set of commonly known network motifs and a gene-regulatory network. Altogether our method supports the modeller in an algorithmic manner to identify possible sources of errors in ODE-based models on the basis of experimental data. © 2017 The Author(s).

Sequence-specific bias correction for RNA-seq data using recurrent neural networks.

PubMed

Zhang, Yao-Zhong; Yamaguchi, Rui; Imoto, Seiya; Miyano, Satoru

2017-01-25

The recent success of deep learning techniques in machine learning and artificial intelligence has stimulated a great deal of interest among bioinformaticians, who now wish to bring the power of deep learning to bare on a host of bioinformatical problems. Deep learning is ideally suited for biological problems that require automatic or hierarchical feature representation for biological data when prior knowledge is limited. In this work, we address the sequence-specific bias correction problem for RNA-seq data redusing Recurrent Neural Networks (RNNs) to model nucleotide sequences without pre-determining sequence structures. The sequence-specific bias of a read is then calculated based on the sequence probabilities estimated by RNNs, and used in the estimation of gene abundance. We explore the application of two popular RNN recurrent units for this task and demonstrate that RNN-based approaches provide a flexible way to model nucleotide sequences without knowledge of predetermined sequence structures. Our experiments show that training a RNN-based nucleotide sequence model is efficient and RNN-based bias correction methods compare well with the-state-of-the-art sequence-specific bias correction method on the commonly used MAQC-III data set. RNNs provides an alternative and flexible way to calculate sequence-specific bias without explicitly pre-determining sequence structures.

Biological interactions of carbon-based nanomaterials: From coronation to degradation.

PubMed

Bhattacharya, Kunal; Mukherjee, Sourav P; Gallud, Audrey; Burkert, Seth C; Bistarelli, Silvia; Bellucci, Stefano; Bottini, Massimo; Star, Alexander; Fadeel, Bengt

2016-02-01

Carbon-based nanomaterials including carbon nanotubes, graphene oxide, fullerenes and nanodiamonds are potential candidates for various applications in medicine such as drug delivery and imaging. However, the successful translation of nanomaterials for biomedical applications is predicated on a detailed understanding of the biological interactions of these materials. Indeed, the potential impact of the so-called bio-corona of proteins, lipids, and other biomolecules on the fate of nanomaterials in the body should not be ignored. Enzymatic degradation of carbon-based nanomaterials by immune-competent cells serves as a special case of bio-corona interactions with important implications for the medical use of such nanomaterials. In the present review, we highlight emerging biomedical applications of carbon-based nanomaterials. We also discuss recent studies on nanomaterial 'coronation' and how this impacts on biodistribution and targeting along with studies on the enzymatic degradation of carbon-based nanomaterials, and the role of surface modification of nanomaterials for these biological interactions. Advances in technology have produced many carbon-based nanomaterials. These are increasingly being investigated for the use in diagnostics and therapeutics. Nonetheless, there remains a knowledge gap in terms of the understanding of the biological interactions of these materials. In this paper, the authors provided a comprehensive review on the recent biomedical applications and the interactions of various carbon-based nanomaterials. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Hilbert-Schmidt and Sobol sensitivity indices for static and time series Wnt signaling measurements in colorectal cancer - part A.

PubMed

Sinha, Shriprakash

2017-12-04

Ever since the accidental discovery of Wingless [Sharma R.P., Drosophila information service, 1973, 50, p 134], research in the field of Wnt signaling pathway has taken significant strides in wet lab experiments and various cancer clinical trials, augmented by recent developments in advanced computational modeling of the pathway. Information rich gene expression profiles reveal various aspects of the signaling pathway and help in studying different issues simultaneously. Hitherto, not many computational studies exist which incorporate the simultaneous study of these issues. This manuscript ∙ explores the strength of contributing factors in the signaling pathway, ∙ analyzes the existing causal relations among the inter/extracellular factors effecting the pathway based on prior biological knowledge and ∙ investigates the deviations in fold changes in the recently found prevalence of psychophysical laws working in the pathway. To achieve this goal, local and global sensitivity analysis is conducted on the (non)linear responses between the factors obtained from static and time series expression profiles using the density (Hilbert-Schmidt Information Criterion) and variance (Sobol) based sensitivity indices. The results show the advantage of using density based indices over variance based indices mainly due to the former's employment of distance measures & the kernel trick via Reproducing kernel Hilbert space (RKHS) that capture nonlinear relations among various intra/extracellular factors of the pathway in a higher dimensional space. In time series data, using these indices it is now possible to observe where in time, which factors get influenced & contribute to the pathway, as changes in concentration of the other factors are made. This synergy of prior biological knowledge, sensitivity analysis & representations in higher dimensional spaces can facilitate in time based administration of target therapeutic drugs & reveal hidden biological information within colorectal cancer samples.

A basis for a visual language for describing, archiving and analyzing functional models of complex biological systems

PubMed Central

Cook, Daniel L; Farley, Joel F; Tapscott, Stephen J

2001-01-01

Background: We propose that a computerized, internet-based graphical description language for systems biology will be essential for describing, archiving and analyzing complex problems of biological function in health and disease. Results: We outline here a conceptual basis for designing such a language and describe BioD, a prototype language that we have used to explore the utility and feasibility of this approach to functional biology. Using example models, we demonstrate that a rather limited lexicon of icons and arrows suffices to describe complex cell-biological systems as discrete models that can be posted and linked on the internet. Conclusions: Given available computer and internet technology, BioD may be implemented as an extensible, multidisciplinary language that can be used to archive functional systems knowledge and be extended to support both qualitative and quantitative functional analysis. PMID:11305940

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.

[From gene cloning to expressional analysis--practice and experience from educational reform of experimental gene engineering].

PubMed

Wu, Yan-Hua; Guo, Bin; Lou, Hui-Ling; Cui, Yu-Liang; Gu, Hui-Juan; Qiao, Shou-Yi

2012-02-01

Experimental gene engineering is a laboratory course focusing on the molecular structure, expression pattern and biological function of genes. Providing our students with a solid knowledge base and correct ways to conduct research is very important for high-quality education of genetic engineering. Inspired by recent progresses in this field, we improved the experimental gene engineering course by adding more updated knowledge and technologies and emphasizing on the combination of teaching and research, with the aim of offering our students a good start in their scientific careers.

Entitymetrics: Measuring the Impact of Entities

PubMed Central

Ding, Ying; Song, Min; Han, Jia; Yu, Qi; Yan, Erjia; Lin, Lili; Chambers, Tamy

2013-01-01

This paper proposes entitymetrics to measure the impact of knowledge units. Entitymetrics highlight the importance of entities embedded in scientific literature for further knowledge discovery. In this paper, we use Metformin, a drug for diabetes, as an example to form an entity-entity citation network based on literature related to Metformin. We then calculate the network features and compare the centrality ranks of biological entities with results from Comparative Toxicogenomics Database (CTD). The comparison demonstrates the usefulness of entitymetrics to detect most of the outstanding interactions manually curated in CTD. PMID:24009660

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.

Developmental Dyslexia: Early Precursors, Neurobehavioral Markers, and Biological Substrates

ERIC Educational Resources Information Center

Benasich, April A., Ed.; Fitch, R. Holly, Ed.

2012-01-01

Understanding the precursors and early indicators of dyslexia is key to early identification and effective intervention. Now there's a single research volume that brings together the very latest knowledge on the earliest stages of dyslexia and the diverse genetic, neurobiological, and cognitive factors that may contribute to it. Based on findings…

Using avian focal species to inform rangeland management in California oak woodland

Treesearch

Alicia D. Young; Breanna Owens; Melissa Odell; Corey Shake; Wendell Gilgert; Geoffrey R. Geupel

2015-01-01

Biological knowledge about bird focal species may be used to inform planning, habitat management, and restoration efforts, with the assumption that the implementation of these species-based recommendations will maintain and enhance healthy functioning habitats and the ecosystems services they provide. Point Blue Conservation Science in collaboration with the Natural...

Communicating Biotech Advances: Fiction versus Reality.

PubMed

Małyska, Aleksandra; Bolla, Robert; Twardowski, Tomasz

2018-02-01

Bioscience novels use selected technologies of genetic engineering and synthetic biology to create entertaining stories. These novels are usually based on scientific knowledge, but they may arouse public concerns about technology and drive public reluctance to accept innovative technologies. The scientific community must adopt more efficient communication and transparency. Copyright © 2017 Elsevier Ltd. All rights reserved.

Understanding the social acceptability of natural resource decisionmaking processes by using a knowledge base modeling approach.

Treesearch

Christina Kakoyannis; Bruce Shindler; George Stankey

2001-01-01

Natural resource managers are being confronted with increasing conflict and litigation with those who find their management plans unacceptable. Compatible and sustainable management decisions necessitate that natural resource agencies generate plans that are not only biologically possible and economically feasible but also socially acceptable. Currently, however, we...

Application of adverse outcome pathways (AOPs) in human health and ecotoxicology capturing divergent consequences of conserved molecular initiating events via AOP networks

EPA Science Inventory

The adverse outcome pathway (AOP) framework was developed to help organize and disseminate existing knowledge concerning the means through which specific perturbations of biological pathways can lead to adverse outcomes considered relevant to risk-based regulatory decision-making...

Application of Adverse Outcome Pathways (AOPs) in Human Health and Ecotoxicology Capturing Divergent Consequences of Conserved Molecular Initiating Events via AOP Networks (Presentation)

EPA Science Inventory

The adverse outcome pathway (AOP) framework was developed to help organize and disseminate existing knowledge concerning the means through which specific perturbations of biological pathways can lead to adverse outcomes considered relevant to risk-based regulatory decision-making...

Chapter 17. Information needs: Great gray owls

Treesearch

Gregory D. Hayward

1994-01-01

Current understanding of great gray owl biology and ecology is based on studies of less than five populations. In an ideal world, a strong conservation strategy would require significant new information. However, current knowledge suggests that conservation of this forest owl should involve fewer conflicts than either the boreal or flammulated owl. The mix of forest...

Performance-Based Task Assessment of Higher-Order Proficiencies in Redesigned STEM High Schools

ERIC Educational Resources Information Center

Ernst, Jeremy V.; Glennie, Elizabeth; Li, Songze

2017-01-01

This study explored student abilities in applying conceptual knowledge when presented with structured performance tasks. Specifically, the study gauged proficiency in higher-order applications of students enrolled in earth and environmental science or biology. The student sample was drawn from a Redesigned STEM high school model where a tested…

Gene Isolation Using Degenerate Primers Targeting Protein Motif: A Laboratory Exercise

ERIC Educational Resources Information Center

Yeo, Brandon Pei Hui; Foong, Lian Chee; Tam, Sheh May; Lee, Vivian; Hwang, Siaw San

2018-01-01

Structures and functions of protein motifs are widely included in many biology-based course syllabi. However, little emphasis is placed to link this knowledge to applications in biotechnology to enhance the learning experience. Here, the conserved motifs of nucleotide binding site-leucine rich repeats (NBS-LRR) proteins, successfully used for the…

What Really Matters: Assessing Individual Problem-Solving Performance in the Context of Biological Sciences

ERIC Educational Resources Information Center

Anderson, William L.; Sensibaugh, Cheryl A.; Osgood, Marcy P.; Mitchell, Steven M.

2011-01-01

The evaluation of higher-level cognitive skills can augment traditional discipline-based knowledge testing by providing timely assessment of individual student problem-solving abilities that are critical for success in any professional development program. However, the wide-spread acceptance and implementation of higher level cognitive skills…

The Role of Field Exercises in Ecological Learning and Values Education: Action Research on the Use of Campus Wetlands

ERIC Educational Resources Information Center

Sukhontapatipak, Chutamas; Srikosamatara, Sompoad

2012-01-01

Providing undergraduate biology students with ecological knowledge and environmental awareness is critical for developing professionalism in sustainable development. In addition to the cognitive and psychomotor development, outdoor ecological exercises combining place-based education and experiential learning can stimulate the affective domain of…

Effects of a Research-Infused Botanical Curriculum on Undergraduates' Content Knowledge, STEM Competencies, and Attitudes toward Plant Sciences

ERIC Educational Resources Information Center

Ward, Jennifer Rhode; Clarke, H. David; Horton, Jonathan L.

2014-01-01

In response to the American Association for the Advancement of Science's Vision and Change in Undergraduate Biology Education initiative, we infused authentic, plant-based research into majors' courses at a public liberal arts university. Faculty members designed a financially sustainable pedagogical approach, utilizing vertically integrated…

Construction of a Digital Video Library: A Socio-Technical Pilot Study on College Students' Attitudes

ERIC Educational Resources Information Center

Chen, Hsin-Liang; Choi, Gilok

2005-01-01

This study investigates socio-technical aspects of digital video libraries based on college students' learning experiences and perspectives. Forty-one students in biology classes were studied through a survey and individual interviews. Findings are presented by the students' knowledge of computer technology, experiences with AV materials, and…

On a Calculus-Based Statistics Course for Life Science Students

ERIC Educational Resources Information Center

Watkins, Joseph C.

2010-01-01

The choice of pedagogy in statistics should take advantage of the quantitative capabilities and scientific background of the students. In this article, we propose a model for a statistics course that assumes student competency in calculus and a broadening knowledge in biology. We illustrate our methods and practices through examples from the…

Lessons for Religious Education from Cognitive Science of Religion

ERIC Educational Resources Information Center

Brelsford, Theodore

2005-01-01

Recent work in the cognitive sciences provides new neurological/biological and evolutionary bases for understanding the construction of knowledge (in the form of sets of ideas containing functionally useful inferences) and the capacity for imagination (as the ability to run inferences and generate ideas from information) in the human mind. In…

Learning Genetics through an Authentic Research Simulation in Bioinformatics

ERIC Educational Resources Information Center

Gelbart, Hadas; Yarden, Anat

2006-01-01

Following the rationale that learning is an active process of knowledge construction as well as enculturation into a community of experts, we developed a novel web-based learning environment in bioinformatics for high-school biology majors in Israel. The learning environment enables the learners to actively participate in a guided inquiry process…

Fundamentals of pulmonary drug delivery.

PubMed

Groneberg, D A; Witt, C; Wagner, U; Chung, K F; Fischer, A

2003-04-01

Aerosol administration of peptide-based drugs plays an important role in the treatment of pulmonary and systemic diseases and the unique cellular properties of airway epithelium offers a great potential to deliver new compounds. As the relative contributions from the large airways to the alveolar space are important to the local and systemic availability, the sites and mechanism of uptake and transport of different target compounds have to be characterized. Among the different respiratory cells, the ciliated epithelial cells of the larger and smaller airways and the type I and type II pneumocytes are the key players in pulmonary drug transport. With their diverse cellular characteristics, each of these cell types displays a unique uptake possibility. Next to the knowledge of these cellular aspects, the nature of aerosolized drugs, characteristics of delivery systems and the depositional and pulmonary clearance mechanisms display major targets to optimize pulmonary drug delivery. Based on the growing knowledge on pulmonary cell biology and pathophysiology due to modern methods of molecular biology, the future characterization of pulmonary drug transport pathways can lead to new strategies in aerosol drug therapy.

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

Bioengineered silk scaffolds in 3D tissue modeling with focus on mammary tissues.

PubMed

Maghdouri-White, Yas; Bowlin, Gary L; Lemmon, Christopher A; Dréau, Didier

2016-02-01

In vitro generation of three-dimensional (3D) biological tissues and organ-like structures is a promising strategy to study and closely model complex aspects of the molecular, cellular, and physiological interactions of tissue. In particular, in vitro 3D tissue modeling holds promises to further our understanding of breast development. Indeed, biologically relevant 3D structures that combine mammary cells and engineered matrices have improved our knowledge of mammary tissue growth, organization, and differentiation. Several polymeric biomaterials have been used as scaffolds to engineer 3D mammary tissues. Among those, silk fibroin-based biomaterials have many biologically relevant properties and have been successfully used in multiple medical applications. Here, we review the recent advances in engineered scaffolds with an emphasis on breast-like tissue generation and the benefits of modified silk-based scaffolds. Copyright © 2015 Elsevier B.V. All rights reserved.

Accessing and Integrating Data and Knowledge for Biomedical Research

PubMed Central

Burgun, A.; Bodenreider, O.

2008-01-01

Summary Objectives To review the issues that have arisen with the advent of translational research in terms of integration of data and knowledge, and survey current efforts to address these issues. Methods Using examples form the biomedical literature, we identified new trends in biomedical research and their impact on bioinformatics. We analyzed the requirements for effective knowledge repositories and studied issues in the integration of biomedical knowledge. Results New diagnostic and therapeutic approaches based on gene expression patterns have brought about new issues in the statistical analysis of data, and new workflows are needed are needed to support translational research. Interoperable data repositories based on standard annotations, infrastructures and services are needed to support the pooling and meta-analysis of data, as well as their comparison to earlier experiments. High-quality, integrated ontologies and knowledge bases serve as a source of prior knowledge used in combination with traditional data mining techniques and contribute to the development of more effective data analysis strategies. Conclusion As biomedical research evolves from traditional clinical and biological investigations towards omics sciences and translational research, specific needs have emerged, including integrating data collected in research studies with patient clinical data, linking omics knowledge with medical knowledge, modeling the molecular basis of diseases, and developing tools that support in-depth analysis of research data. As such, translational research illustrates the need to bridge the gap between bioinformatics and medical informatics, and opens new avenues for biomedical informatics research. PMID:18660883

Examining the pedagogical content knowledge and practice of experienced secondary biology teachers for teaching diffusion and osmosis

NASA Astrophysics Data System (ADS)

Lankford, Deanna

Teachers are the most important factor in student learning (National Research Council, 1996); yet little is known about the specialized knowledge held by experienced teachers. The purpose of this study was twofold: first, to make explicit the pedagogical content knowledge (PCK) for teaching diffusion and osmosis held by experienced biology teachers and, second, to reveal how topic-specific PCK informs teacher practice. The Magnusson et al. (1999) PCK model served as the theoretical framework for the study. The overarching research question was: When teaching lessons on osmosis and diffusion, how do experienced biology teachers draw upon their topic-specific pedagogical content knowledge? Data sources included observations of two consecutive lessons, three semi-structured interviews, lesson plans, and student handouts. Data analysis indicated five of the six teachers held a constructivist orientation to science teaching and engaged students in explorations of diffusion and osmosis prior to introducing the concepts to students. Explanations for diffusion and osmosis were based upon students' observations and experiences during explorations. All six teachers used representations at the molecular, cellular, and plant organ levels to serve as foci for explorations of diffusion and osmosis. Three potential learning difficulties identified by the teachers included: (a) understanding vocabulary terms, (b) predicting the direction of osmosis, and (c) identifying random molecular motion as the driving force for diffusion and osmosis. Participants used student predictions as formative assessments to reveal misconceptions before instruction and evaluate conceptual understanding during instruction. This study includes implications for teacher preparation, research, and policy.

Network analysis reveals stage-specific changes in zebrafish embryo development using time course whole transcriptome profiling and prior biological knowledge.

PubMed

Zhang, Yuji

2015-01-01

Molecular networks act as the backbone of molecular activities within cells, offering a unique opportunity to better understand the mechanism of diseases. While network data usually constitute only static network maps, integrating them with time course gene expression information can provide clues to the dynamic features of these networks and unravel the mechanistic driver genes characterizing cellular responses. Time course gene expression data allow us to broadly "watch" the dynamics of the system. However, one challenge in the analysis of such data is to establish and characterize the interplay among genes that are altered at different time points in the context of a biological process or functional category. Integrative analysis of these data sources will lead us a more complete understanding of how biological entities (e.g., genes and proteins) coordinately perform their biological functions in biological systems. In this paper, we introduced a novel network-based approach to extract functional knowledge from time-dependent biological processes at a system level using time course mRNA sequencing data in zebrafish embryo development. The proposed method was applied to investigate 1α, 25(OH)2D3-altered mechanisms in zebrafish embryo development. We applied the proposed method to a public zebrafish time course mRNA-Seq dataset, containing two different treatments along four time points. We constructed networks between gene ontology biological process categories, which were enriched in differential expressed genes between consecutive time points and different conditions. The temporal propagation of 1α, 25-Dihydroxyvitamin D3-altered transcriptional changes started from a few genes that were altered initially at earlier stage, to large groups of biological coherent genes at later stages. The most notable biological processes included neuronal and retinal development and generalized stress response. In addition, we also investigated the relationship among biological processes enriched in co-expressed genes under different conditions. The enriched biological processes include translation elongation, nucleosome assembly, and retina development. These network dynamics provide new insights into the impact of 1α, 25-Dihydroxyvitamin D3 treatment in bone and cartilage development. We developed a network-based approach to analyzing the DEGs at different time points by integrating molecular interactions and gene ontology information. These results demonstrate that the proposed approach can provide insight on the molecular mechanisms taking place in vertebrate embryo development upon treatment with 1α, 25(OH)2D3. Our approach enables the monitoring of biological processes that can serve as a basis for generating new testable hypotheses. Such network-based integration approach can be easily extended to any temporal- or condition-dependent genomic data analyses.

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 schema theory analysis of students' think aloud protocols in an STS biology context

NASA Astrophysics Data System (ADS)

Quinlan, Catherine Louise

This dissertation study is a conglomerate of the fields of Science Education and Applied Cognitive Psychology. The goal of this study is to determine what organizational features and knowledge representation patterns high school students exhibit over time for issues pertinent to science and society. Participants are thirteen tenth grade students in a diverse suburban-urban classroom in a northeastern state. Students' think alouds are recorded, pre-, post-, and late-post treatment. Treatment consists of instruction in three Science, Technology, and Society (STS) biology issues, namely the human genome project, nutrition and health, and stem cell research. Coding and analyses are performed using Marshall's knowledge representations---identification knowledge, elaboration knowledge, planning knowledge, and execution knowledge, as well as qualitative research analysis methods. Schema theory, information processing theory, and other applied cognitive theory provide a framework in which to understand and explain students' schema descriptions and progressions over time. The results show that students display five organizational features in their identification and elaboration knowledge. Students also fall into one of four categories according to if they display prior schema or no prior schema, and their orientation "for" or "against," some of the issues. Students with prior schema and orientation "against" display the most robust schema descriptions and schema progressions. Those with no prior schemas and orientation "against" show very modest schema progressions best characterized by their keyword searches. This study shows the importance in considering not only students' integrated schemas but also their individual schemes. A role for the use of a more schema-based instruction that scaffolds student learning is implicated.

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/

Effects of a research-infused botanical curriculum on undergraduates' content knowledge, STEM competencies, and attitudes toward plant sciences.

PubMed

Ward, Jennifer Rhode; Clarke, H David; Horton, Jonathan L

2014-01-01

In response to the American Association for the Advancement of Science's Vision and Change in Undergraduate Biology Education initiative, we infused authentic, plant-based research into majors' courses at a public liberal arts university. Faculty members designed a financially sustainable pedagogical approach, utilizing vertically integrated curricular modules based on undergraduate researchers' field and laboratory projects. Our goals were to 1) teach botanical concepts, from cells to ecosystems; 2) strengthen competencies in statistical analysis and scientific writing; 3) pique plant science interest; and 4) allow all undergraduates to contribute to genuine research. Our series of inquiry-centered exercises mitigated potential faculty barriers to adopting research-rich curricula, facilitating teaching/research balance by gathering publishable scholarly data during laboratory class periods. Student competencies were assessed with pre- and postcourse quizzes and rubric-graded papers, and attitudes were evaluated with pre- and postcourse surveys. Our revised curriculum increased students' knowledge and awareness of plant science topics, improved scientific writing, enhanced statistical knowledge, and boosted interest in conducting research. More than 300 classroom students have participated in our program, and data generated from these modules' assessment allowed faculty and students to present 28 contributed talks or posters and publish three papers in 4 yr. Future steps include analyzing the effects of repeated module exposure on student learning and creating a regional consortium to increase our project's pedagogical impact. © 2014 J. R. Ward et al. 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).

MIPS Arabidopsis thaliana Database (MAtDB): an integrated biological knowledge resource based on the first complete plant genome

PubMed Central

Schoof, Heiko; Zaccaria, Paolo; Gundlach, Heidrun; Lemcke, Kai; Rudd, Stephen; Kolesov, Grigory; Arnold, Roland; Mewes, H. W.; Mayer, Klaus F. X.

2002-01-01

Arabidopsis thaliana is the first plant for which the complete genome has been sequenced and published. Annotation of complex eukaryotic genomes requires more than the assignment of genetic elements to the sequence. Besides completing the list of genes, we need to discover their cellular roles, their regulation and their interactions in order to understand the workings of the whole plant. The MIPS Arabidopsis thaliana Database (MAtDB; http://mips.gsf.de/proj/thal/db) started out as a repository for genome sequence data in the European Scientists Sequencing Arabidopsis (ESSA) project and the Arabidopsis Genome Initiative. Our aim is to transform MAtDB into an integrated biological knowledge resource by integrating diverse data, tools, query and visualization capabilities and by creating a comprehensive resource for Arabidopsis as a reference model for other species, including crop plants. PMID:11752263

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.

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.

Bioorthogonal chemistry: applications in activity-based protein profiling.

PubMed

Willems, Lianne I; van der Linden, Wouter A; Li, Nan; Li, Kah-Yee; Liu, Nora; Hoogendoorn, Sascha; van der Marel, Gijs A; Florea, Bogdan I; Overkleeft, Herman S

2011-09-20

The close interaction between organic chemistry and biology goes back to the late 18th century, when the modern natural sciences began to take shape. After synthetic organic chemistry arose as a discipline, organic chemists almost immediately began to pursue the synthesis of naturally occurring compounds, thereby contributing to the understanding of their functions in biological processes. Research in those days was often remarkably interdisciplinary; in fact, it constituted chemical biology research before the phrase even existed. For example, histological dyes, both of an organic and inorganic nature, were developed and applied by independent researchers (Gram and Golgi) with the aim of visualizing cellular substructures (the bacterial cell wall and the Golgi apparatus). Over the years, as knowledge within the various fields of the natural sciences deepened, research disciplines drifted apart, becoming rather monodisciplinary. In these years, broadly ranging from the end of World War II to about the 1980s, organic chemistry continued to impact life sciences research, but contributions were of a more indirect nature. As an example, the development of the polymerase chain reaction, from which molecular biology and genetics research have greatly profited, was partly predicated on the availability of synthetic oligonucleotides. These molecules first became available in the late 1960s, the result of organic chemists pursuing the synthesis of DNA oligomers primarily because of the synthetic challenges involved. Today, academic natural sciences research is again becoming more interdisciplinary, and sometimes even multidisciplinary. What was termed "chemical biology" by Stuart Schreiber at the end of the last century can be roughly described as the use of intellectually chemical approaches to shed light on processes that are fundamentally rooted in biology. Chemical tools and techniques that are developed for biological studies in the exciting and rapidly evolving field of chemical biology research include contributions from many areas of the multifaceted discipline of chemistry, and particularly from organic chemistry. Researchers apply knowledge inherent to organic chemistry, such as reactivity and selectivity, to the manipulation of specific biomolecules in biological samples (cell extracts, living cells, and sometimes even animal models) to gain insight into the biological phenomena in which these molecules participate. In this Account, we highlight some of the recent developments in chemical biology research driven by organic chemistry, with a focus on bioorthogonal chemistry in relation to activity-based protein profiling. The rigorous demands of bioorthogonality have not yet been realized in a truly bioorthogonal reagent pair, but remarkable progress has afforded a range of tangible contributions to chemical biology research. Activity-based protein profiling, which aims to obtain information on the workings of a protein (or protein family) within the larger context of the full biological system, has in particular benefited from these advances. Both activity-based protein profiling and bioorthogonal chemistry have been around for approximately 15 years, and about 8 years ago the two fields very profitably intersected. We expect that each discipline, both separately and in concert, will continue to make important contributions to chemical biology research. © 2011 American Chemical Society

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.

A knowledge-based control system for air-scour optimisation in membrane bioreactors.

PubMed

Ferrero, G; Monclús, H; Sancho, L; Garrido, J M; Comas, J; Rodríguez-Roda, I

2011-01-01

Although membrane bioreactors (MBRs) technology is still a growing sector, its progressive implementation all over the world, together with great technical achievements, has allowed it to reach a mature degree, just comparable to other more conventional wastewater treatment technologies. With current energy requirements around 0.6-1.1 kWh/m3 of treated wastewater and investment costs similar to conventional treatment plants, main market niche for MBRs can be areas with very high restrictive discharge limits, where treatment plants have to be compact or where water reuse is necessary. Operational costs are higher than for conventional treatments; consequently there is still a need and possibilities for energy saving and optimisation. This paper presents the development of a knowledge-based decision support system (DSS) for the integrated operation and remote control of the biological and physical (filtration and backwashing or relaxation) processes in MBRs. The core of the DSS is a knowledge-based control module for air-scour consumption automation and energy consumption minimisation.

New developments of a knowledge based system (VEG) for inferring vegetation characteristics

NASA Technical Reports Server (NTRS)

Kimes, D. S.; Harrison, P. A.; Harrison, P. R.

1992-01-01

An extraction technique for inferring physical and biological surface properties of vegetation using nadir and/or directional reflectance data as input has been developed. A knowledge-based system (VEG) accepts spectral data of an unknown target as input, determines the best strategy for inferring the desired vegetation characteristic, applies the strategy to the target data, and provides a rigorous estimate of the accuracy of the inference. Progress in developing the system is presented. VEG combines methods from remote sensing and artificial intelligence, and integrates input spectral measurements with diverse knowledge bases. VEG has been developed to (1) infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; (2) test and develop new extraction techniques on an internal spectral database; (3) browse, plot, or analyze directional reflectance data in the system's spectral database; (4) discriminate between user-defined vegetation classes using spectral and directional reflectance relationships; and (5) infer unknown view angles from known view angles (known as view angle extension).

[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

A national comparison of biochemistry and molecular biology capstone experiences.

PubMed

Aguanno, Ann; Mertz, Pamela; Martin, Debra; Bell, Ellis

2015-01-01

Recognizing the increasingly integrative nature of the molecular life sciences, the American Society for Biochemistry and Molecular Biology (ASBMB) recommends that Biochemistry and Molecular Biology (BMB) programs develop curricula based on concepts, content, topics, and expected student outcomes, rather than courses. To that end, ASBMB conducted a series of regional workshops to build a BMB Concept Inventory containing validated assessment tools, based on foundational and discipline-specific knowledge and essential skills, for the community to use. A culminating activity, which integrates the educational experience, is often part of undergraduate molecular life science programs. These "capstone" experiences are commonly defined as an attempt to measure student ability to synthesize and integrate acquired knowledge. However, the format, implementation, and approach to outcome assessment of these experiences are quite varied across the nation. Here we report the results of a nation-wide survey on BMB capstone experiences and discuss this in the context of published reports about capstones and the findings of the workshops driving the development of the BMB Concept Inventory. Both the survey results and the published reports reveal that, although capstone practices do vary, certain formats for the experience are used more frequently and similarities in learning objectives were identified. The use of rubrics to measure student learning is also regularly reported, but details about these assessment instruments are sparse in the literature and were not a focus of our survey. Finally, we outline commonalities in the current practice of capstones and suggest the next steps needed to elucidate best practices. © 2015 The International Union of Biochemistry and Molecular Biology.

Knowledge environments representing molecular entities for the virtual physiological human.

PubMed

Hofmann-Apitius, Martin; Fluck, Juliane; Furlong, Laura; Fornes, Oriol; Kolárik, Corinna; Hanser, Susanne; Boeker, Martin; Schulz, Stefan; Sanz, Ferran; Klinger, Roman; Mevissen, Theo; Gattermayer, Tobias; Oliva, Baldo; Friedrich, Christoph M

2008-09-13

In essence, the virtual physiological human (VPH) is a multiscale representation of human physiology spanning from the molecular level via cellular processes and multicellular organization of tissues to complex organ function. The different scales of the VPH deal with different entities, relationships and processes, and in consequence the models used to describe and simulate biological functions vary significantly. Here, we describe methods and strategies to generate knowledge environments representing molecular entities that can be used for modelling the molecular scale of the VPH. Our strategy to generate knowledge environments representing molecular entities is based on the combination of information extraction from scientific text and the integration of information from biomolecular databases. We introduce @neuLink, a first prototype of an automatically generated, disease-specific knowledge environment combining biomolecular, chemical, genetic and medical information. Finally, we provide a perspective for the future implementation and use of knowledge environments representing molecular entities for the VPH.

Performance of nursing auxiliaries and technicians in managing piercing cutting material: a necessary study.

PubMed

Moura, Elaine Cristina Carvalho; Moreira, Maria de Fátima Santana; da Fonseca, Soraia Martins

2009-01-01

This study aimed to analyze the knowledge of nursing auxiliaries and technicians in handling and disposing of piercing-cutting material and describe their performance. This qualitative-descriptive research was carried out with three nursing auxiliaries and 12 technicians at a medium-size hospital, totaling 15 participants interviewed through a semi-structured script. Discourse was analyzed through the content analysis technique. Results appoint that, even though the participants have theoretical knowledge on the management of piercing-cutting material, they do not totally follow their knowledge, which exposes them to several biological risks, revealing reproductive knowledge and performance. Thus, we propose the implementation of continuing education programs based on constructivist methodological approach aiming at effective practices in the management and disposal of piercing-cutting material. In this perspective, research clarifying how adults apprehend knowledge can deepen the results described in the study.

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.

Defining the Relationship of Student Achievement Between STEM Subjects Through Canonical Correlation Analysis of 2011 Trends in International Mathematics and Science Study (TIMSS) Data

NASA Astrophysics Data System (ADS)

O'Neal, Melissa Jean

Canonical correlation analysis was used to analyze data from Trends in International Mathematics and Science Study (TIMSS) 2011 achievement databases encompassing information from fourth/eighth grades. Student achievement in life science/biology was correlated with achievement in mathematics and other sciences across three analytical areas: mathematics and science student performance, achievement in cognitive domains, and achievement in content domains. Strong correlations between student achievement in life science/biology with achievement in mathematics and overall science occurred for both high- and low-performing education systems. Hence, partial emphases on the inter-subject connections did not always lead to a better student learning outcome in STEM education. In addition, student achievement in life science/biology was positively correlated with achievement in mathematics and science cognitive domains; these patterns held true for correlations of life science/biology with mathematics as well as other sciences. The importance of linking student learning experiences between and within STEM domains to support high performance on TIMSS assessments was indicated by correlations of moderate strength (57 TIMSS assessments was indicated by correlations of moderate strength (57 < r < 85) stronger correlations (73 < r < 97) between life science/biology and other science domains. Results demonstrated the foundational nature of STEM knowledge at the fourth grade level, and established the importance of strong interconnections among life science/biology, mathematics, and other sciences. At the eighth grade level, students who built increasing levels of cognitive complexity upon firm foundations were prepared for successful learning throughout their educational careers. The results from this investigation promote a holistic design of school learning opportunities to improve student achievement in life science/biology and other science, technology, engineering, and mathematics (STEM) subjects at the elementary and middle school levels. While the curriculum can vary from combined STEM subjects to separated mathematics or science courses, both professional learning communities (PLC) for teachers and problem-based learning (PBL) for learners can be strengthened through new knowledge construction beyond the traditional boundaries of each subject. It is the knowledge transfer across subjects that breaks barriers of future STEM discoveries to improve STEM education outcomes.

We Are Not Alone: The iMOP Initiative and Its Roles in a Biology- and Disease-Driven Human Proteome Project.

PubMed

Tholey, Andreas; Taylor, Nicolas L; Heazlewood, Joshua L; Bendixen, Emøke

2017-12-01

Mapping of the human proteome has advanced significantly in recent years and will provide a knowledge base to accelerate our understanding of how proteins and protein networks can affect human health and disease. However, providing solutions to human health challenges will likely fail if insights are exclusively based on studies of human samples and human proteomes. In recent years, it has become evident that human health depends on an integrated understanding of the many species that make human life possible. These include the commensal microorganisms that are essential to human life, pathogens, and food species as well as the classic model organisms that enable studies of biological mechanisms. The Human Proteome Organization (HUPO) initiative on multiorganism proteomes (iMOP) works to support proteome research undertaken on nonhuman species that remain widely under-studied compared with the progress in human proteome research. This perspective argues the need for further research on multiple species that impact human life. We also present an update on recent progress in model organisms, microbiota, and food species, address the emerging problem of antibiotics resistance, and outline how iMOP activities could lead to a more inclusive approach for the human proteome project (HPP) to better support proteome research aimed at improving human health and furthering knowledge on human biology.

The Era of International Space Station Utilization Begins: Research Strategy, International Collaboration, and Realized Potential

NASA Technical Reports Server (NTRS)

Thumm, Tracy; Robinson, Julie A.; Ruttley, Tara; Johnson-Green, Perry; Karabadzhak, George; Nakamura, Tai; Sorokin, Igor V.; Zell, Martin; Jean, Sabbagh

2010-01-01

With the assembly of the International Space Station (ISS) nearing completion and the support of a full-time crew of six, a new era of utilization for research is beginning. For more than 15 years, the ISS international partnership has weathered financial, technical and political challenges proving that nations can work together to complete assembly of the largest space vehicle in history. And while the ISS partners can be proud of having completed one of the most ambitious engineering projects ever conceived, the challenge of successfully using the platform remains. During the ISS assembly phase, the potential benefits of space-based research and development were demonstrated; including the advancement of scientific knowledge based on experiments conducted in space, development and testing of new technologies, and derivation of Earth applications from new understanding. The configurability and human-tended capabilities of the ISS provide a unique platform. The international utilization strategy is based on research ranging from physical sciences, biology, medicine, psychology, to Earth observation, human exploration preparation and technology demonstration. The ability to complete follow-on investigations in a period of months allows researchers to make rapid advances based on new knowledge gained from ISS activities. During the utilization phase, the ISS partners are working together to track the objectives, accomplishments, and the applications of the new knowledge gained. This presentation will summarize the consolidated international results of these tracking activities and approaches. Areas of current research on ISS with strong international cooperation will be highlighted including cardiovascular studies, cell and plant biology studies, radiation, physics of matter, and advanced alloys. Scientific knowledge and new technologies derived from research on the ISS will be realized through improving quality of life on Earth and future spaceflight endeavours. Extension of the ISS through 2020 and beyond will insure that the benefits of research will be achievable for the International Partnership.

A roadmap for knowledge exchange and mobilization research in conservation and natural resource management.

PubMed

Nguyen, Vivian M; Young, Nathan; Cooke, Steven J

2017-08-01

Scholars across all disciplines have long been interested in how knowledge moves within and beyond their community of peers. Rapid environmental changes and calls for sustainable management practices mean the best knowledge possible is needed to inform decisions, policies, and practices to protect biodiversity and sustainably manage vulnerable natural resources. Although the conservation literature on knowledge exchange (KE) and knowledge mobilization (KM) has grown in recent years, much of it is based on context-specific case studies. This presents a challenge for learning cumulative lessons from KE and KM research and thus effectively using knowledge in conservation and natural resources management. Although continued research on the gap between knowledge and action is valuable, overarching conceptual frameworks are now needed to enable summaries and comparisons across diverse KE-KM research. We propose a knowledge-action framework that provides a conceptual roadmap for future research and practice in KE/KM with the aim of synthesizing lessons learned from contextual case studies and guiding the development and testing of hypotheses in this domain. Our knowledge-action framework has 3 elements that occur at multiple levels and scales: knowledge production (e.g., academia and government), knowledge mediation (e.g., knowledge networks, actors, relational dimension, and contextual dimension), and knowledge-based action (e.g., instrumental, symbolic, and conceptual). The framework integrates concepts from the sociology of science in particular, and serves as a guide to further comprehensive understanding of knowledge exchange and mobilization in conservation and sustainable natural resource management. © 2016 Society for Conservation Biology.

Evolutionary game theory for physical and biological scientists. II. Population dynamics equations can be associated with interpretations

PubMed Central

Liao, David; Tlsty, Thea D.

2014-01-01

The use of mathematical equations to analyse population dynamics measurements is being increasingly applied to elucidate complex dynamic processes in biological systems, including cancer. Purely ‘empirical’ equations may provide sufficient accuracy to support predictions and therapy design. Nevertheless, interpretation of fitting equations in terms of physical and biological propositions can provide additional insights that can be used both to refine models that prove inconsistent with data and to understand the scope of applicability of models that validate. The purpose of this tutorial is to assist readers in mathematically associating interpretations with equations and to provide guidance in choosing interpretations and experimental systems to investigate based on currently available biological knowledge, techniques in mathematical and computational analysis and methods for in vitro and in vivo experiments. PMID:25097752

Student Understanding of pH: "I Don't Know What the Log Actually Is, I Only Know Where the Button Is on My Calculator"

ERIC Educational Resources Information Center

Watters, Dianne J.; Watters, James J.

2006-01-01

In foundation biochemistry and biological chemistry courses, a major problem area that has been identified is students' lack of understanding of pH, acids, bases, and buffers and their inability to apply their knowledge in solving acid/base problems. The aim of this study was to explore students' conceptions of pH and their ability to solve…

Agent-Based Modeling in Systems Pharmacology.

PubMed

Cosgrove, J; Butler, J; Alden, K; Read, M; Kumar, V; Cucurull-Sanchez, L; Timmis, J; Coles, M

2015-11-01

Modeling and simulation (M&S) techniques provide a platform for knowledge integration and hypothesis testing to gain insights into biological systems that would not be possible a priori. Agent-based modeling (ABM) is an M&S technique that focuses on describing individual components rather than homogenous populations. This tutorial introduces ABM to systems pharmacologists, using relevant case studies to highlight how ABM-specific strengths have yielded success in the area of preclinical mechanistic modeling.

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 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.

An e-learning application on electrochemotherapy

PubMed Central

Corovic, Selma; Bester, Janez; Miklavcic, Damijan

2009-01-01

Background Electrochemotherapy is an effective approach in local tumour treatment employing locally applied high-voltage electric pulses in combination with chemotherapeutic drugs. In planning and performing electrochemotherapy a multidisciplinary expertise is required and collaboration, knowledge and experience exchange among the experts from different scientific fields such as medicine, biology and biomedical engineering is needed. The objective of this study was to develop an e-learning application in order to provide the educational content on electrochemotherapy and its underlying principles and to support collaboration, knowledge and experience exchange among the experts involved in the research and clinics. Methods The educational content on electrochemotherapy and cell and tissue electroporation was based on previously published studies from molecular dynamics, lipid bilayers, single cell level and simplified tissue models to complex biological tissues and research and clinical results of electrochemotherapy treatment. We used computer graphics such as model-based visualization (i.e. 3D numerical modelling using finite element method) and 3D computer animations and graphical illustrations to facilitate the representation of complex biological and physical aspects in electrochemotherapy. The e-learning application is integrated into an interactive e-learning environment developed at our institution, enabling collaboration and knowledge exchange among the users. We evaluated the designed e-learning application at the International Scientific workshop and postgraduate course (Electroporation Based Technologies and Treatments). The evaluation was carried out by testing the pedagogical efficiency of the presented educational content and by performing the usability study of the application. Results The e-learning content presents three different levels of knowledge on cell and tissue electroporation. In the first part of the e-learning application we explain basic principles of electroporation process. The second part provides educational content about importance of modelling and visualization of local electric field in electroporation-based treatments. In the third part we developed an interactive module for visualization of local electric field distribution in 3D tissue models of cutaneous tumors for different parameters such as voltage applied, distance between electrodes, electrode dimension and shape, tissue geometry and electric conductivity. The pedagogical efficiency assessment showed that the participants improved their level of knowledge. The results of usability evaluation revealed that participants found the application simple to learn, use and navigate. The participants also found the information provided by the application easy to understand. Conclusion The e-learning application we present in this article provides educational material on electrochemotherapy and its underlying principles such as cell and tissue electroporation. The e-learning application is developed to provide an interactive educational content in order to simulate the "hands-on" learning approach about the parameters being important for successful therapy. The e-learning application together with the interactive e-learning environment is available to the users to provide collaborative and flexible learning in order to facilitate knowledge exchange among the experts from different scientific fields that are involved in electrochemotherapy. The modular structure of the application allows for upgrade with new educational content collected from the clinics and research, and can be easily adapted to serve as a collaborative e-learning tool also in other electroporation-based treatments such as gene electrotransfer, gene vaccination, irreversible tissue ablation and transdermal gene and drug delivery. The presented e-learning application provides an easy and rapid approach for information, knowledge and experience exchange among the experts from different scientific fields, which can facilitate development and optimisation of electroporation-based treatments. PMID:19843322

An e-learning application on electrochemotherapy.

PubMed

Corovic, Selma; Bester, Janez; Miklavcic, Damijan

2009-10-20

Electrochemotherapy is an effective approach in local tumour treatment employing locally applied high-voltage electric pulses in combination with chemotherapeutic drugs. In planning and performing electrochemotherapy a multidisciplinary expertise is required and collaboration, knowledge and experience exchange among the experts from different scientific fields such as medicine, biology and biomedical engineering is needed. The objective of this study was to develop an e-learning application in order to provide the educational content on electrochemotherapy and its underlying principles and to support collaboration, knowledge and experience exchange among the experts involved in the research and clinics. The educational content on electrochemotherapy and cell and tissue electroporation was based on previously published studies from molecular dynamics, lipid bilayers, single cell level and simplified tissue models to complex biological tissues and research and clinical results of electrochemotherapy treatment. We used computer graphics such as model-based visualization (i.e. 3D numerical modelling using finite element method) and 3D computer animations and graphical illustrations to facilitate the representation of complex biological and physical aspects in electrochemotherapy. The e-learning application is integrated into an interactive e-learning environment developed at our institution, enabling collaboration and knowledge exchange among the users. We evaluated the designed e-learning application at the International Scientific workshop and postgraduate course (Electroporation Based Technologies and Treatments). The evaluation was carried out by testing the pedagogical efficiency of the presented educational content and by performing the usability study of the application. The e-learning content presents three different levels of knowledge on cell and tissue electroporation. In the first part of the e-learning application we explain basic principles of electroporation process. The second part provides educational content about importance of modelling and visualization of local electric field in electroporation-based treatments. In the third part we developed an interactive module for visualization of local electric field distribution in 3D tissue models of cutaneous tumors for different parameters such as voltage applied, distance between electrodes, electrode dimension and shape, tissue geometry and electric conductivity. The pedagogical efficiency assessment showed that the participants improved their level of knowledge. The results of usability evaluation revealed that participants found the application simple to learn, use and navigate. The participants also found the information provided by the application easy to understand. The e-learning application we present in this article provides educational material on electrochemotherapy and its underlying principles such as cell and tissue electroporation. The e-learning application is developed to provide an interactive educational content in order to simulate the "hands-on" learning approach about the parameters being important for successful therapy. The e-learning application together with the interactive e-learning environment is available to the users to provide collaborative and flexible learning in order to facilitate knowledge exchange among the experts from different scientific fields that are involved in electrochemotherapy. The modular structure of the application allows for upgrade with new educational content collected from the clinics and research, and can be easily adapted to serve as a collaborative e-learning tool also in other electroporation-based treatments such as gene electrotransfer, gene vaccination, irreversible tissue ablation and transdermal gene and drug delivery. The presented e-learning application provides an easy and rapid approach for information, knowledge and experience exchange among the experts from different scientific fields, which can facilitate development and optimisation of electroporation-based treatments.

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

Tools for knowledge acquisition within the NeuroScholar system and their application to anatomical tract-tracing data

PubMed Central

Burns, Gully APC; Cheng, Wei-Cheng

2006-01-01

Background Knowledge bases that summarize the published literature provide useful online references for specific areas of systems-level biology that are not otherwise supported by large-scale databases. In the field of neuroanatomy, groups of small focused teams have constructed medium size knowledge bases to summarize the literature describing tract-tracing experiments in several species. Despite years of collation and curation, these databases only provide partial coverage of the available published literature. Given that the scientists reading these papers must all generate the interpretations that would normally be entered into such a system, we attempt here to provide general-purpose annotation tools to make it easy for members of the community to contribute to the task of data collation. Results In this paper, we describe an open-source, freely available knowledge management system called 'NeuroScholar' that allows straightforward structured markup of the PDF files according to a well-designed schema to capture the essential details of this class of experiment. Although, the example worked through in this paper is quite specific to neuroanatomical connectivity, the design is freely extensible and could conceivably be used to construct local knowledge bases for other experiment types. Knowledge representations of the experiment are also directly linked to the contributing textual fragments from the original research article. Through the use of this system, not only could members of the community contribute to the collation task, but input data can be gathered for automated approaches to permit knowledge acquisition through the use of Natural Language Processing (NLP). Conclusion We present a functional, working tool to permit users to populate knowledge bases for neuroanatomical connectivity data from the literature through the use of structured questionnaires. This system is open-source, fully functional and available for download from [1]. PMID:16895608

Team-teaching a current events-based biology course for nonmajors.

PubMed

Bondos, Sarah E; Phillips, Dereth

2008-01-01

Rice University has created a team-taught interactive biology course for nonmajors with a focus on cutting edge biology in the news-advances in biotechnology, medicine, and science policy, along with the biological principles and methodology upon which these advances are based. The challenges inherent to teaching current topics were minimized by team-teaching the course, providing knowledgeable and enthusiastic lecturers for every topic while distributing the effort required to update material. Postdoctoral associates and advanced graduate students served as lecturers, providing an opportunity for them to develop their teaching skills and learn to communicate effectively with nonscientists on newsworthy topics related to their research. Laboratory tours, in-class demonstrations, and mock-ups helped lecturers convey surprisingly advanced ideas with students who lacked a strong theoretical or practical science background. A faculty member and co-coordinator administer the class, organize class activities, and mentor the speakers on teaching techniques and lecture design. Course design, lecture topics, hands-on activities, and approaches to successfully solve the difficulties inherent to team teaching are discussed. Course evaluations reflect student involvement in, and enjoyment of, the class. Copyright © 2008 International Union of Biochemistry and Molecular Biology, Inc.

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 ADVERSE OUTCOME PATHWAY (AOP) FRAMEWORK: A FRAMEWORK FOR ORGANIZING BIOLOGICAL KNOWLEDGE LEADING TO HEALTH RISKS.

EPA Science Inventory

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 Molecul...

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…

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

EPA Science Inventory

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 he...

The Curriculum Ideology of the South African Secondary School Biology

ERIC Educational Resources Information Center

Mnguni, Lindelani

2013-01-01

South Africa has had a number of curriculum reforms since 1994 which have been based on both political and education grounds. However, there is a dearth of knowledge about the nature of the envisioned graduates, especially with respect to social challenges. This can be addressed by exploring the curriculum ideology which outlines the vision of…

Inviting Queer Ideas into the Science Classroom: Studying Sexuality Education from a Queer Perspective

ERIC Educational Resources Information Center

Lundin, Mattias

2014-01-01

Science education has been pointed out as fact-based and built on reliable knowledge. Nevertheless, there are areas that include other aspects. Sexual education is, according to the Swedish syllabus, such an example and it involves aspects as love, sexuality and relations. These aspects suggest a possible tension between the biological and…

Approaches to Biology Teaching and Learning: Understanding the Wrong Answers--Teaching toward Conceptual Change

ERIC Educational Resources Information Center

Tanner, Kimberly; Allen, Deborah

2005-01-01

Underpinning science education reform movements in the last 20 years--at all levels and within all disciplines--is an explicit shift in the goals of science teaching from students simply creating a knowledge base of scientific facts to students developing deeper understandings of major concepts within a scientific discipline. For example, what use…

"Model-Based Reasoning Is Not a Simple Thing": Investigating Enactment of Modeling in Five High School Biology Classrooms

ERIC Educational Resources Information Center

Gaytan, Candice Renee

2017-01-01

Modeling is an important scientific practice through which scientists generate, evaluate, and revise scientific knowledge, and it can be translated into science classrooms as a means for engaging students in authentic scientific practice. Much of the research investigating modeling in classrooms focuses on student learning, leaving a gap in…

Computational Scientific Inquiry with Virtual Worlds and Agent-Based Models: New Ways of Doing Science to Learn Science

ERIC Educational Resources Information Center

Jacobson, Michael J.; Taylor, Charlotte E.; Richards, Deborah

2016-01-01

In this paper, we propose computational scientific inquiry (CSI) as an innovative model for learning important scientific knowledge and new practices for "doing" science. This approach involves the use of a "game-like" virtual world for students to experience virtual biological fieldwork in conjunction with using an agent-based…

On a Calculus-based Statistics Course for Life Science Students

PubMed Central

2010-01-01

The choice of pedagogy in statistics should take advantage of the quantitative capabilities and scientific background of the students. In this article, we propose a model for a statistics course that assumes student competency in calculus and a broadening knowledge in biology. We illustrate our methods and practices through examples from the curriculum. PMID:20810962

From Innovation to Impact at Scale: Lessons Learned from a Cluster of Research-Community Partnerships

ERIC Educational Resources Information Center

Schindler, Holly S.; Fisher, Philip A.; Shonkoff, Jack P.

2017-01-01

This article presents a description of how an interdisciplinary network of academic researchers, community-based programs, parents, and state agencies have joined together to design, test, and scale a suite of innovative intervention strategies rooted in new knowledge about the biology of adversity. Through a process of cocreation, collective…

Construction of an ortholog database using the semantic web technology for integrative analysis of genomic data.

PubMed

Chiba, Hirokazu; Nishide, Hiroyo; Uchiyama, Ikuo

2015-01-01

Recently, various types of biological data, including genomic sequences, have been rapidly accumulating. To discover biological knowledge from such growing heterogeneous data, a flexible framework for data integration is necessary. Ortholog information is a central resource for interlinking corresponding genes among different organisms, and the Semantic Web provides a key technology for the flexible integration of heterogeneous data. We have constructed an ortholog database using the Semantic Web technology, aiming at the integration of numerous genomic data and various types of biological information. To formalize the structure of the ortholog information in the Semantic Web, we have constructed the Ortholog Ontology (OrthO). While the OrthO is a compact ontology for general use, it is designed to be extended to the description of database-specific concepts. On the basis of OrthO, we described the ortholog information from our Microbial Genome Database for Comparative Analysis (MBGD) in the form of Resource Description Framework (RDF) and made it available through the SPARQL endpoint, which accepts arbitrary queries specified by users. In this framework based on the OrthO, the biological data of different organisms can be integrated using the ortholog information as a hub. Besides, the ortholog information from different data sources can be compared with each other using the OrthO as a shared ontology. Here we show some examples demonstrating that the ortholog information described in RDF can be used to link various biological data such as taxonomy information and Gene Ontology. Thus, the ortholog database using the Semantic Web technology can contribute to biological knowledge discovery through integrative data analysis.

Designing and testing a classroom curriculum to teach preschoolers about the biology of physical activity: The respiration system as an underlying biological causal mechanism

NASA Astrophysics Data System (ADS)

Ewing, Tracy S.

The present study examined young children's understanding of respiration and oxygen as a source of vital energy underlying physical activity. Specifically, the purpose of the study was to explore whether a coherent biological theory, characterized by an understanding that bodily parts (heart and lungs) and processes (oxygen in respiration) as part of a biological system, can be taught as a foundational concept to reason about physical activity. The effects of a biology-based intervention curriculum designed to teach preschool children about bodily functions as a part of the respiratory system, the role of oxygen as a vital substance and how physical activity acts an energy source were examined. Participants were recruited from three private preschool classrooms (two treatment; 1 control) in Southern California and included a total of 48 four-year-old children (30 treatment; 18 control). Findings from this study suggested that young children could be taught relevant biological concepts about the role of oxygen in respiratory processes. Children who received biology-based intervention curriculum made significant gains in their understanding of the biology of respiration, identification of physical and sedentary activities. In addition these children demonstrated that coherence of conceptual knowledge was correlated with improved accuracy at activity identification and reasoning about the inner workings of the body contributing to endurance. Findings from this study provided evidence to support the benefits of providing age appropriate but complex coherent biological instruction to children in early childhood settings.

A review on powder-based additive manufacturing for tissue engineering: selective laser sintering and inkjet 3D printing

PubMed Central

Shirazi, Seyed Farid Seyed; Gharehkhani, Samira; Mehrali, Mehdi; Yarmand, Hooman; Metselaar, Hendrik Simon Cornelis; Adib Kadri, Nahrizul; Osman, Noor Azuan Abu

2015-01-01

Since most starting materials for tissue engineering are in powder form, using powder-based additive manufacturing methods is attractive and practical. The principal point of employing additive manufacturing (AM) systems is to fabricate parts with arbitrary geometrical complexity with relatively minimal tooling cost and time. Selective laser sintering (SLS) and inkjet 3D printing (3DP) are two powerful and versatile AM techniques which are applicable to powder-based material systems. Hence, the latest state of knowledge available on the use of AM powder-based techniques in tissue engineering and their effect on mechanical and biological properties of fabricated tissues and scaffolds must be updated. Determining the effective setup of parameters, developing improved biocompatible/bioactive materials, and improving the mechanical/biological properties of laser sintered and 3D printed tissues are the three main concerns which have been investigated in this article. PMID:27877783

A review on powder-based additive manufacturing for tissue engineering: selective laser sintering and inkjet 3D printing.

PubMed

Shirazi, Seyed Farid Seyed; Gharehkhani, Samira; Mehrali, Mehdi; Yarmand, Hooman; Metselaar, Hendrik Simon Cornelis; Adib Kadri, Nahrizul; Osman, Noor Azuan Abu

2015-06-01

Since most starting materials for tissue engineering are in powder form, using powder-based additive manufacturing methods is attractive and practical. The principal point of employing additive manufacturing (AM) systems is to fabricate parts with arbitrary geometrical complexity with relatively minimal tooling cost and time. Selective laser sintering (SLS) and inkjet 3D printing (3DP) are two powerful and versatile AM techniques which are applicable to powder-based material systems. Hence, the latest state of knowledge available on the use of AM powder-based techniques in tissue engineering and their effect on mechanical and biological properties of fabricated tissues and scaffolds must be updated. Determining the effective setup of parameters, developing improved biocompatible/bioactive materials, and improving the mechanical/biological properties of laser sintered and 3D printed tissues are the three main concerns which have been investigated in this article.

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).

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.

A proposal for a computer-based framework of support for public health in the management of biological incidents: the Czech Republic experience.

PubMed

Bures, Vladimír; Otcenásková, Tereza; Cech, Pavel; Antos, Karel

2012-11-01

Biological incidents jeopardising public health require decision-making that consists of one dominant feature: complexity. Therefore, public health decision-makers necessitate appropriate support. Based on the analogy with business intelligence (BI) principles, the contextual analysis of the environment and available data resources, and conceptual modelling within systems and knowledge engineering, this paper proposes a general framework for computer-based decision support in the case of a biological incident. At the outset, the analysis of potential inputs to the framework is conducted and several resources such as demographic information, strategic documents, environmental characteristics, agent descriptors and surveillance systems are considered. Consequently, three prototypes were developed, tested and evaluated by a group of experts. Their selection was based on the overall framework scheme. Subsequently, an ontology prototype linked with an inference engine, multi-agent-based model focusing on the simulation of an environment, and expert-system prototypes were created. All prototypes proved to be utilisable support tools for decision-making in the field of public health. Nevertheless, the research revealed further issues and challenges that might be investigated by both public health focused researchers and practitioners.

NASA Human Research Program Space Radiation Program Element

NASA Technical Reports Server (NTRS)

Chappell, Lori; Huff, Janice; Patel, Janapriya; Wang, Minli; Hu, Shaowwen; Kidane, Yared; Myung-Hee, Kim; Li, Yongfeng; Nounu, Hatem; Plante, Ianik;

Bioimaging of cells and tissues using accelerator-based sources.

PubMed

Petibois, Cyril; Cestelli Guidi, Mariangela

2008-07-01

A variety of techniques exist that provide chemical information in the form of a spatially resolved image: electron microprobe analysis, nuclear microprobe analysis, synchrotron radiation microprobe analysis, secondary ion mass spectrometry, and confocal fluorescence microscopy. Linear (LINAC) and circular (synchrotrons) particle accelerators have been constructed worldwide to provide to the scientific community unprecedented analytical performances. Now, these facilities match at least one of the three analytical features required for the biological field: (1) a sufficient spatial resolution for single cell (< 1 mum) or tissue (<1 mm) analyses, (2) a temporal resolution to follow molecular dynamics, and (3) a sensitivity in the micromolar to nanomolar range, thus allowing true investigations on biological dynamics. Third-generation synchrotrons now offer the opportunity of bioanalytical measurements at nanometer resolutions with incredible sensitivity. Linear accelerators are more specialized in their physical features but may exceed synchrotron performances. All these techniques have become irreplaceable tools for developing knowledge in biology. This review highlights the pros and cons of the most popular techniques that have been implemented on accelerator-based sources to address analytical issues on biological specimens.

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

How to design cell-based biosensors using the sol-gel process.

PubMed

Depagne, Christophe; Roux, Cécile; Coradin, Thibaud

2011-05-01

Inorganic gels formed using the sol-gel process are promising hosts for the encapsulation of living organisms and the design of cell-based biosensors. However, the possibility to use the biological activity of entrapped cells as a biological signal requires a good understanding and careful control of the chemical and physical conditions in which the organisms are placed before, during, and after gel formation, and their impact on cell viability. Moreover, it is important to examine the possible transduction methods that are compatible with sol-gel encapsulated cells. Through an updated presentation of the current knowledge in this field and based on selected examples, this review shows how it has been possible to convert a chemical technology initially developed for the glass industry into a biotechnological tool, with current limitations and promising specificities.

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

The need and potential for building a integrated knowledge-base of the Earth-Human system

NASA Astrophysics Data System (ADS)

Jacobs, Clifford

2011-03-01

The pursuit of scientific understanding is increasingly based on interdisciplinary research. To understand more deeply the planet and its interactions requires a progressively more holistic approach, exploring knowledge coming from all scientific and engineering disciplines including but not limited to, biology, chemistry, computer sciences, geosciences, material sciences, mathematics, physics, cyberinfrastucture, and social sciences. Nowhere is such an approach more critical than in the study of global climate change in which one of the major challenges is the development of next-generation Earth System Models that include coupled and interactive representations of ecosystems, agricultural working lands and forests, urban environments, biogeochemistry, atmospheric chemistry, ocean and atmospheric currents, the water cycle, land ice, and human activities.

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.

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.

Zebrafish Whole-Adult-Organism Chemogenomics for Large-Scale Predictive and Discovery Chemical Biology

PubMed Central

Lam, Siew Hong; Mathavan, Sinnakarupan; Tong, Yan; Li, Haixia; Karuturi, R. Krishna Murthy; Wu, Yilian; Vega, Vinsensius B.; Liu, Edison T.; Gong, Zhiyuan

2008-01-01

The ability to perform large-scale, expression-based chemogenomics on whole adult organisms, as in invertebrate models (worm and fly), is highly desirable for a vertebrate model but its feasibility and potential has not been demonstrated. We performed expression-based chemogenomics on the whole adult organism of a vertebrate model, the zebrafish, and demonstrated its potential for large-scale predictive and discovery chemical biology. Focusing on two classes of compounds with wide implications to human health, polycyclic (halogenated) aromatic hydrocarbons [P(H)AHs] and estrogenic compounds (ECs), we generated robust prediction models that can discriminate compounds of the same class from those of different classes in two large independent experiments. The robust expression signatures led to the identification of biomarkers for potent aryl hydrocarbon receptor (AHR) and estrogen receptor (ER) agonists, respectively, and were validated in multiple targeted tissues. Knowledge-based data mining of human homologs of zebrafish genes revealed highly conserved chemical-induced biological responses/effects, health risks, and novel biological insights associated with AHR and ER that could be inferred to humans. Thus, our study presents an effective, high-throughput strategy of capturing molecular snapshots of chemical-induced biological states of a whole adult vertebrate that provides information on biomarkers of effects, deregulated signaling pathways, and possible affected biological functions, perturbed physiological systems, and increased health risks. These findings place zebrafish in a strategic position to bridge the wide gap between cell-based and rodent models in chemogenomics research and applications, especially in preclinical drug discovery and toxicology. PMID:18618001

Biotechnology by Design: An Introductory Level, Project-Based, Synthetic Biology Laboratory Program for Undergraduate Students.

PubMed

Beach, Dale L; Alvarez, Consuelo J

2015-12-01

Synthetic biology offers an ideal opportunity to promote undergraduate laboratory courses with research-style projects, immersing students in an inquiry-based program that enhances the experience of the scientific process. We designed a semester-long, project-based laboratory curriculum using synthetic biology principles to develop a novel sensory device. Students develop subject matter knowledge of molecular genetics and practical skills relevant to molecular biology, recombinant DNA techniques, and information literacy. During the spring semesters of 2014 and 2015, the Synthetic Biology Laboratory Project was delivered to sophomore genetics courses. Using a cloning strategy based on standardized BioBrick genetic "parts," students construct a "reporter plasmid" expressing a reporter gene (GFP) controlled by a hybrid promoter regulated by the lac-repressor protein (lacI). In combination with a "sensor plasmid," the production of the reporter phenotype is inhibited in the presence of a target environmental agent, arabinose. When arabinose is absent, constitutive GFP expression makes cells glow green. But the presence of arabinose activates a second promoter (pBAD) to produce a lac-repressor protein that will inhibit GFP production. Student learning was assessed relative to five learning objectives, using a student survey administered at the beginning (pre-survey) and end (post-survey) of the course, and an additional 15 open-ended questions from five graded Progress Report assignments collected throughout the course. Students demonstrated significant learning gains (p < 0.05) for all learning outcomes. Ninety percent of students indicated that the Synthetic Biology Laboratory Project enhanced their understanding of molecular genetics. The laboratory project is highly adaptable for both introductory and advanced courses.

Comparison of Student Achievement Using Didactic, Inquiry-Based, and the Combination of Two Approaches of Science Instruction

NASA Astrophysics Data System (ADS)

Foster, Hyacinth Carmen

Science educators and administrators support the idea that inquiry-based and didactic-based instructional strategies have varying effects on students' acquisition of science concepts. The research problem addressed whether incorporating the two approaches covered the learning requirements of all students in science classes, enabling them to meet state and national standards. The purpose of this quasiexperimental, posttest design research study was to determine if student learning and achievement in high school biology classes differed for each type of instructional method. Constructivism theory suggested that each learner creates knowledge over time because of the learners' interactions with the environment. The optimal teaching method, didactic (teacher-directed), inquiry-based, or a combination of two approaches instructional method, becomes essential if students are to discover ways to learn information. The research question examined which form of instruction had a significant effect on student achievement in biology. The data analysis consisted of single-factor, independent-measures analysis of variance (ANOVA) that tested the hypotheses of the research study. Locally, the results indicated greater and statistically significant differences in standardized laboratory scores for students who were taught using the combination of two approaches. Based on these results, biology instructors will gain new insights into ways of improving the instructional process. Social change may occur as the science curriculum leadership applies the combination of two instructional approaches to improve acquisition of science concepts by biology students.

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.

From biology to mathematical models and back: teaching modeling to biology students, and biology to math and engineering students.

PubMed

Chiel, Hillel J; McManus, Jeffrey M; Shaw, Kendrick M

2010-01-01

We describe the development of a course to teach modeling and mathematical analysis skills to students of biology and to teach biology to students with strong backgrounds in mathematics, physics, or engineering. The two groups of students have different ways of learning material and often have strong negative feelings toward the area of knowledge that they find difficult. To give students a sense of mastery in each area, several complementary approaches are used in the course: 1) a "live" textbook that allows students to explore models and mathematical processes interactively; 2) benchmark problems providing key skills on which students make continuous progress; 3) assignment of students to teams of two throughout the semester; 4) regular one-on-one interactions with instructors throughout the semester; and 5) a term project in which students reconstruct, analyze, extend, and then write in detail about a recently published biological model. Based on student evaluations and comments, an attitude survey, and the quality of the students' term papers, the course has significantly increased the ability and willingness of biology students to use mathematical concepts and modeling tools to understand biological systems, and it has significantly enhanced engineering students' appreciation of biology.

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.

Rational design and optimization of downstream processes of virus particles for biopharmaceutical applications: current advances.

PubMed

Vicente, Tiago; Mota, José P B; Peixoto, Cristina; Alves, Paula M; Carrondo, Manuel J T

2011-01-01

The advent of advanced therapies in the pharmaceutical industry has moved the spotlight into virus-like particles and viral vectors produced in cell culture holding great promise in a myriad of clinical targets, including cancer prophylaxis and treatment. Even though a couple of cases have reached the clinic, these products have yet to overcome a number of biological and technological challenges before broad utilization. Concerning the manufacturing processes, there is significant research focusing on the optimization of current cell culture systems and, more recently, on developing scalable downstream processes to generate material for pre-clinical and clinical trials. We review the current options for downstream processing of these complex biopharmaceuticals and underline current advances on knowledge-based toolboxes proposed for rational optimization of their processing. Rational tools developed to increase the yet scarce knowledge on the purification processes of complex biologicals are discussed as alternative to empirical, "black-boxed" based strategies classically used for process development. Innovative methodologies based on surface plasmon resonance, dynamic light scattering, scale-down high-throughput screening and mathematical modeling for supporting ion-exchange chromatography show great potential for a more efficient and cost-effective process design, optimization and equipment prototyping. Copyright © 2011 Elsevier Inc. All rights reserved.

Understanding pictorial information in biology: students' cognitive activities and visual reading strategies

NASA Astrophysics Data System (ADS)

Brandstetter, Miriam; Sandmann, Angela; Florian, Christine

2017-06-01

In classroom, scientific contents are increasingly communicated through visual forms of representations. Students' learning outcomes rely on their ability to read and understand pictorial information. Understanding pictorial information in biology requires cognitive effort and can be challenging to students. Yet evidence-based knowledge about students' visual reading strategies during the process of understanding pictorial information is pending. Therefore, 42 students at the age of 14-15 were asked to think aloud while trying to understand visual representations of the blood circulatory system and the patellar reflex. A category system was developed differentiating 16 categories of cognitive activities. A Principal Component Analysis revealed two underlying patterns of activities that can be interpreted as visual reading strategies: 1. Inferences predominated by using a problem-solving schema; 2. Inferences predominated by recall of prior content knowledge. Each pattern consists of a specific set of cognitive activities that reflect selection, organisation and integration of pictorial information as well as different levels of expertise. The results give detailed insights into cognitive activities of students who were required to understand the pictorial information of complex organ systems. They provide an evidence-based foundation to derive instructional aids that can promote students pictorial-information-based learning on different levels of expertise.

An Educational Program of Mechatronics for Multidisciplinary Knowledge Acquisition

NASA Astrophysics Data System (ADS)

Watanuki, Keiichi; Kojima, Kazuyuki

Recently, as the technologies surrounding mechanical engineering have improved remarkably, the expectations for students who graduate from departments of mechanical engineering have increased. For example, in order to develop a mechatronics system, a student needs to integrate a wide variety of technologies, such as mechanical engineering, electrical and electronics engineering, and information technology. Therefore, from the perspective of educators, the current education system, which stresses expertizing each technology, should be replaced by an education system that stresses integrating multidisciplinary knowledge. In this paper, a trial education program for students of the department of mechanical engineering in our university, in which students are required to integrate multidisciplinary knowledge in order to develop a biologically-based robot, is described. Finally, the efficacy of the program is analyzed.

Prior knowledge guided active modules identification: an integrated multi-objective approach.

PubMed

Chen, Weiqi; Liu, Jing; He, Shan

2017-03-14

Active module, defined as an area in biological network that shows striking changes in molecular activity or phenotypic signatures, is important to reveal dynamic and process-specific information that is correlated with cellular or disease states. A prior information guided active module identification approach is proposed to detect modules that are both active and enriched by prior knowledge. We formulate the active module identification problem as a multi-objective optimisation problem, which consists two conflicting objective functions of maximising the coverage of known biological pathways and the activity of the active module simultaneously. Network is constructed from protein-protein interaction database. A beta-uniform-mixture model is used to estimate the distribution of p-values and generate scores for activity measurement from microarray data. A multi-objective evolutionary algorithm is used to search for Pareto optimal solutions. We also incorporate a novel constraints based on algebraic connectivity to ensure the connectedness of the identified active modules. Application of proposed algorithm on a small yeast molecular network shows that it can identify modules with high activities and with more cross-talk nodes between related functional groups. The Pareto solutions generated by the algorithm provides solutions with different trade-off between prior knowledge and novel information from data. The approach is then applied on microarray data from diclofenac-treated yeast cells to build network and identify modules to elucidate the molecular mechanisms of diclofenac toxicity and resistance. Gene ontology analysis is applied to the identified modules for biological interpretation. Integrating knowledge of functional groups into the identification of active module is an effective method and provides a flexible control of balance between pure data-driven method and prior information guidance.

Read, retrieve, connect and use: An intervention strategy for science and scientific literacy

NASA Astrophysics Data System (ADS)

Monahan, Kerryane T.

American students underachieve on local, state, national, and international assessments of science. Student performance on standardized assessments has driven numerous educational reforms including No Child Left Behind and Race to the Top with a resulting increased focus on student achievement. Local districts and schools struggle with how to improve student achievement in order to meet the requirements of state and federal legislation. International and national government officials extoll the value of science in driving the economic prosperity of a nation adding increased pressure to improve science scores in the United States. Moreover, to be effective decision-makers personally and within a democracy, citizens must be scientifically literate. Read, Retrieve, Connect and Use (RRCU) is an instructional strategy that combined state biology content standards, with the new Common Core Standards for Literacy in Science through evidenced-based literacy strategies recommended by the National Reading Panel. This study aimed to assess the efficacy of an intervention, RRCU to improve science content knowledge and literacy skills in Biology and Language Arts. The findings identified reading skill, as measured by FCAT Reading as predictive of Biology test scores indicating a close relationship between reading comprehension and the ability to learn and be assessed on science content knowledge. The data did not indicate RRCU was an effective means of improving student science content knowledge or literacy skills. However, teachers responded positively to the strategy as a means to reinforce content knowledge and support literacy skills. Future recommendations include improving the study design and expanding the use of the strategy to middle school to build a foundation of effective literacy skills students can use to cope with the depth and complexity of science content at the high school level.

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)

Predictors of student success in entry-level science courses

NASA Astrophysics Data System (ADS)

Singh, Mamta K.

Although the educational evaluation process is useful and valuable and is supported by the Higher Education Act, a strong research base for program evaluation of college entry-level science courses is still lacking. Studies in science disciplines such as, biology, chemistry, and physics have addressed various affective and demographic factors and their relationships to student achievement. However, the literature contains little information that specifically addresses student biology content knowledge skills (basics and higher order thinking skills) and identifies factors that affect students' success in entry-level college science courses. These gate-keeping courses require detailed evaluation if the goal of an institution is to increase students' performance and success in these courses. These factors are, in fact, a stepping stone for increasing the number of graduates in Science, Technology, Engineering, and Mathematics (STEM) majors. The present study measured students' biology content knowledge and investigated students' performance and success in college biology, chemistry, and physics entry-level courses. Seven variables---gender, ethnicity, high school Grade Point Average (GPA), high school science, college major, school financial aid support, and work hours were used as independent variables and course final performance as a dichotomous dependent variable. The sample comprised voluntary student participants in entry-level science courses. The study attempted to explore eight research questions. Content knowledge assessments, demographic information analysis, multiple regression analysis, and binary logistic regression analysis were used to address research questions. The results suggested that high school GPA was a consistently good predictor of students' performance and success in entry-level science courses. Additionally, high school chemistry was a significant predictor variable for student success in entry-level biology and chemistry courses. Similarly, students' performance and success in entry-level physics courses were influenced by high school physics. Finally, the study developed student success equation with high school GAP and high school chemistry as good predictors of students' success in entry-level science courses.

Virtual fetal pig dissection as an agent of knowledge acquisition and attitudinal change in female high school biology students

NASA Astrophysics Data System (ADS)

Maloney, Rebecca Scudari

One way to determine if all students can learn through the use of computers is to introduce a lesson taught completely via computers and compare the results with those gained when the same lesson is taught in a traditional manner. This study attempted to determine if a virtual fetal pig dissection can be used as a viable alternative for an actual dissection for females enrolled in high school biology classes by comparing the knowledge acquisition and attitudinal change between the experimental (virtual dissection) and control (actual dissection) groups. Two hundred and twenty-four students enrolled in biology classes in a suburban all-girl parochial high school participated in this study. Female students in an all-girl high school were chosen because research shows differences in science competency and computer usage between the genders that may mask the performance of females on computer-based tasks in a science laboratory exercise. Students who completed the virtual dissection scored significantly higher on practical test and objective tests that were used to measure knowledge acquisition. Attitudinal change was measured by examining the students' attitudes toward dissections, computer usage in the classroom, and toward biology both before and after the dissections using pre and post surveys. Significant results in positive gain scores were found in the virtual dissection group's attitude toward dissections, and their negative gain score toward virtual dissections. Attitudinal changes toward computers and biology were not significant. A purposefully selected sample of the students were interviewed, in addition to gathering a sample of the students' daily dissection journals, as data highlighting their thoughts and feelings about their dissection experience. Further research is suggested to determine if a virtual laboratory experience can be a substitute for actual dissections, or may serve as an enhancement to an actual dissection.

Business as Usual: An Assessment of Donald Rumsfeld’s Transformation Vision and Transformation’s Prospects for the Future

DTIC Science & Technology

2008-06-01

capabilities: • Goal 1: Protecting critical bases and defeating chemical, biological, rad and nuclear weapons. • Goal 2: Projecting and sustaining ...bases is the supply side of the equation, whereas projecting and sustaining forces is the equation’s consumption side. The product of this equation...dominance through comprehensive knowledge, focused execution, and coordinated sustainment shared cross fully netted maritime, joint, and combined forces.123

Designing a post-genomics knowledge ecosystem to translate pharmacogenomics into public health action.

PubMed

Dove, Edward S; Faraj, Samer A; Kolker, Eugene; Ozdemir, Vural

2012-01-01

Translation of pharmacogenomics to public health action is at the epicenter of the life sciences agenda. Post-genomics knowledge is simultaneously co-produced at multiple scales and locales by scientists, crowd-sourcing and biological citizens. The latter are entrepreneurial citizens who are autonomous, self-governing and increasingly conceptualizing themselves in biological terms, ostensibly taking responsibility for their own health, and engaging in patient advocacy and health activism. By studying these heterogeneous 'scientific cultures', we can locate innovative parameters of collective action to move pharmacogenomics to practice (personalized therapeutics). To this end, we reconceptualize knowledge-based innovation as a complex ecosystem comprising 'actors' and 'narrators'. For robust knowledge translation, we require a nested post-genomics technology governance system composed of first-order narrators (for example, social scientists, philosophers, bioethicists) situated at arm's length from innovation actors (for example, pharmacogenomics scientists). Yet, second-order narrators (for example, an independent and possibly crowd-funded think-tank of citizen scholars, marginalized groups and knowledge end-users) are crucial to prevent first-order narrators from gaining excessive power that can be misused in the course of steering innovations. To operate such 'self-calibrating' and nested innovation ecosystems, we introduce the concept of 'wiki-governance' to enable mutual and iterative learning among innovation actors and first- and second-order narrators. '[A] scientific expert is someone who knows more and more about less and less, until finally knowing (almost) everything about (almost) nothing.' [1] 'Ubuntu: I am because you are.' [2].

Designing a post-genomics knowledge ecosystem to translate pharmacogenomics into public health action

PubMed Central

2012-01-01

Translation of pharmacogenomics to public health action is at the epicenter of the life sciences agenda. Post-genomics knowledge is simultaneously co-produced at multiple scales and locales by scientists, crowd-sourcing and biological citizens. The latter are entrepreneurial citizens who are autonomous, self-governing and increasingly conceptualizing themselves in biological terms, ostensibly taking responsibility for their own health, and engaging in patient advocacy and health activism. By studying these heterogeneous 'scientific cultures', we can locate innovative parameters of collective action to move pharmacogenomics to practice (personalized therapeutics). To this end, we reconceptualize knowledge-based innovation as a complex ecosystem comprising 'actors' and 'narrators'. For robust knowledge translation, we require a nested post-genomics technology governance system composed of first-order narrators (for example, social scientists, philosophers, bioethicists) situated at arm's length from innovation actors (for example, pharmacogenomics scientists). Yet, second-order narrators (for example, an independent and possibly crowd-funded think-tank of citizen scholars, marginalized groups and knowledge end-users) are crucial to prevent first-order narrators from gaining excessive power that can be misused in the course of steering innovations. To operate such 'self-calibrating' and nested innovation ecosystems, we introduce the concept of 'wiki-governance' to enable mutual and iterative learning among innovation actors and first- and second-order narrators. '[A] scientific expert is someone who knows more and more about less and less, until finally knowing (almost) everything about (almost) nothing.' [1] 'Ubuntu: I am because you are.' [2] PMID:23194449

Expansion of Biology Teachers' Pedagogical Content Knowledge (PCK) During a Long-Term Professional Development Program

NASA Astrophysics Data System (ADS)

Rozenszajn, Ronit; Yarden, Anat

2014-02-01

Experienced teachers possess a unique teaching knowledge comprised of an inter-related set of knowledge and beliefs that gives direction and justification to a teacher's actions. This study examined the expansion of two components of pedagogical content knowledge (PCK) of three in-service teachers in the course of a professional development program aimed at designing new teaching and learning materials suggested by the teachers themselves. The research presents an enlargement of previous PCK representations by focusing on a detailed representation of two main PCK domains: teaching and learning, including ten PCK components that emerged in the course of data analysis. This representation enabled revealing the unique PCK held by each teacher and to characterize the expansion of the two components of the participating teachers' PCK during the long-term professional development program. Retention of major parts of the expanded PCK a year after termination of the program implies that designing and implementing new teaching and learning materials based on the teachers' experiences, needs, and knowledge in a workshop format accompanied by biology and science education courses might provide a powerful means for PCK expansion. We recommend that designers of professional development programs be aware of the unique PCK held by each teacher in order to promote meaningful professional development of each teacher. Moreover, the PCK representations that were identified in the course of this study enabled clarifying the "orientation toward teaching science" category of PCK which appears to be unclear in current literature.

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…

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…

A top-level ontology of functions and its application in the Open Biomedical Ontologies.

PubMed

Burek, Patryk; Hoehndorf, Robert; Loebe, Frank; Visagie, Johann; Herre, Heinrich; Kelso, Janet

2006-07-15

A clear understanding of functions in biology is a key component in accurate modelling of molecular, cellular and organismal biology. Using the existing biomedical ontologies it has been impossible to capture the complexity of the community's knowledge about biological functions. We present here a top-level ontological framework for representing knowledge about biological functions. This framework lends greater accuracy, power and expressiveness to biomedical ontologies by providing a means to capture existing functional knowledge in a more formal manner. An initial major application of the ontology of functions is the provision of a principled way in which to curate functional knowledge and annotations in biomedical ontologies. Further potential applications include the facilitation of ontology interoperability and automated reasoning. A major advantage of the proposed implementation is that it is an extension to existing biomedical ontologies, and can be applied without substantial changes to these domain ontologies. The Ontology of Functions (OF) can be downloaded in OWL format from http://onto.eva.mpg.de/. Additionally, a UML profile and supplementary information and guides for using the OF can be accessed from the same website.

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).