Information processing in bacteria: memory, computation, and statistical physics: a key issues review.

PubMed

Lan, Ganhui; Tu, Yuhai

2016-05-01

Living systems have to constantly sense their external environment and adjust their internal state in order to survive and reproduce. Biological systems, from as complex as the brain to a single E. coli cell, have to process these data in order to make appropriate decisions. How do biological systems sense external signals? How do they process the information? How do they respond to signals? Through years of intense study by biologists, many key molecular players and their interactions have been identified in different biological machineries that carry out these signaling functions. However, an integrated, quantitative understanding of the whole system is still lacking for most cellular signaling pathways, not to say the more complicated neural circuits. To study signaling processes in biology, the key thing to measure is the input-output relationship. The input is the signal itself, such as chemical concentration, external temperature, light (intensity and frequency), and more complex signals such as the face of a cat. The output can be protein conformational changes and covalent modifications (phosphorylation, methylation, etc), gene expression, cell growth and motility, as well as more complex output such as neuron firing patterns and behaviors of higher animals. Due to the inherent noise in biological systems, the measured input-output dependence is often noisy. These noisy data can be analysed by using powerful tools and concepts from information theory such as mutual information, channel capacity, and the maximum entropy hypothesis. This information theory approach has been successfully used to reveal the underlying correlations between key components of biological networks, to set bounds for network performance, and to understand possible network architecture in generating observed correlations. Although the information theory approach provides a general tool in analysing noisy biological data and may be used to suggest possible network architectures in preserving information, it does not reveal the underlying mechanism that leads to the observed input-output relationship, nor does it tell us much about which information is important for the organism and how biological systems use information to carry out specific functions. To do that, we need to develop models of the biological machineries, e.g. biochemical networks and neural networks, to understand the dynamics of biological information processes. This is a much more difficult task. It requires deep knowledge of the underlying biological network-the main players (nodes) and their interactions (links)-in sufficient detail to build a model with predictive power, as well as quantitative input-output measurements of the system under different perturbations (both genetic variations and different external conditions) to test the model predictions to guide further development of the model. Due to the recent growth of biological knowledge thanks in part to high throughput methods (sequencing, gene expression microarray, etc) and development of quantitative in vivo techniques such as various florescence technology, these requirements are starting to be realized in different biological systems. The possible close interaction between quantitative experimentation and theoretical modeling has made systems biology an attractive field for physicists interested in quantitative biology. In this review, we describe some of the recent work in developing a quantitative predictive model of bacterial chemotaxis, which can be considered as the hydrogen atom of systems biology. Using statistical physics approaches, such as the Ising model and Langevin equation, we study how bacteria, such as E. coli, sense and amplify external signals, how they keep a working memory of the stimuli, and how they use these data to compute the chemical gradient. In particular, we will describe how E. coli cells avoid cross-talk in a heterogeneous receptor cluster to keep a ligand-specific memory. We will also study the thermodynamic costs of adaptation for cells to maintain an accurate memory. The statistical physics based approach described here should be useful in understanding design principles for cellular biochemical circuits in general.

The informational architecture of the cell.

PubMed

Walker, Sara Imari; Kim, Hyunju; Davies, Paul C W

2016-03-13

We compare the informational architecture of biological and random networks to identify informational features that may distinguish biological networks from random. The study presented here focuses on the Boolean network model for regulation of the cell cycle of the fission yeast Schizosaccharomyces pombe. We compare calculated values of local and global information measures for the fission yeast cell cycle to the same measures as applied to two different classes of random networks: Erdös-Rényi and scale-free. We report patterns in local information processing and storage that do indeed distinguish biological from random, associated with control nodes that regulate the function of the fission yeast cell-cycle network. Conversely, we find that integrated information, which serves as a global measure of 'emergent' information processing, does not differ from random for the case presented. We discuss implications for our understanding of the informational architecture of the fission yeast cell-cycle network in particular, and more generally for illuminating any distinctive physics that may be operative in life. © 2016 The Author(s).

Synthetic Analog and Digital Circuits for Cellular Computation and Memory

PubMed Central

Purcell, Oliver; Lu, Timothy K.

2014-01-01

Biological computation is a major area of focus in synthetic biology because it has the potential to enable a wide range of applications. Synthetic biologists have applied engineering concepts to biological systems in order to construct progressively more complex gene circuits capable of processing information in living cells. Here, we review the current state of computational genetic circuits and describe artificial gene circuits that perform digital and analog computation. We then discuss recent progress in designing gene circuits that exhibit memory, and how memory and computation have been integrated to yield more complex systems that can both process and record information. Finally, we suggest new directions for engineering biological circuits capable of computation. PMID:24794536

Information fluency for undergraduate biology majors: applications of inquiry-based learning in a developmental biology course.

PubMed

Gehring, Kathleen M; Eastman, Deborah A

2008-01-01

Many initiatives for the improvement of undergraduate science education call for inquiry-based learning that emphasizes investigative projects and reading of the primary literature. These approaches give students an understanding of science as a process and help them integrate content presented in courses. At the same time, general initiatives to promote information fluency are being promoted on many college and university campuses. Information fluency refers to discipline-specific processing of information, and it involves integration of gathered information with specific ideas to form logical conclusions. We have implemented the use of inquiry-based learning to enhance and study discipline-specific information fluency skills in an upper-level undergraduate Developmental Biology course. In this study, an information literacy tutorial and a set of linked assignments using primary literature analysis were integrated with two inquiry-based laboratory research projects. Quantitative analysis of student responses suggests that the abilities of students to identify and apply valid sources of information were enhanced. Qualitative assessment revealed a set of patterns by which students gather and apply information. Self-assessment responses indicated that students recognized the impact of the assignments on their abilities to gather and apply information and that they were more confident about these abilities for future biology courses and beyond.

Information Fluency for Undergraduate Biology Majors: Applications of Inquiry-based Learning in a Developmental Biology Course

PubMed Central

Gehring, Kathleen M.

2008-01-01

Many initiatives for the improvement of undergraduate science education call for inquiry-based learning that emphasizes investigative projects and reading of the primary literature. These approaches give students an understanding of science as a process and help them integrate content presented in courses. At the same time, general initiatives to promote information fluency are being promoted on many college and university campuses. Information fluency refers to discipline-specific processing of information, and it involves integration of gathered information with specific ideas to form logical conclusions. We have implemented the use of inquiry-based learning to enhance and study discipline-specific information fluency skills in an upper-level undergraduate Developmental Biology course. In this study, an information literacy tutorial and a set of linked assignments using primary literature analysis were integrated with two inquiry-based laboratory research projects. Quantitaitve analysis of student responses suggests that the abilities of students to identify and apply valid sources of information were enhanced. Qualitative assessment revealed a set of patterns by which students gather and apply information. Self-assessment responses indicated that students recognized the impact of the assignments on their abilities to gather and apply information and that they were more confident about these abilities for future biology courses and beyond. PMID:18316808

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.

Quantum Information Biology: From Theory of Open Quantum Systems to Adaptive Dynamics

NASA Astrophysics Data System (ADS)

Asano, Masanari; Basieva, Irina; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

This chapter reviews quantum(-like) information biology (QIB). Here biology is treated widely as even covering cognition and its derivatives: psychology and decision making, sociology, and behavioral economics and finances. QIB provides an integrative description of information processing by bio-systems at all scales of life: from proteins and cells to cognition, ecological and social systems. Mathematically QIB is based on the theory of adaptive quantum systems (which covers also open quantum systems). Ideologically QIB is based on the quantum-like (QL) paradigm: complex bio-systems process information in accordance with the laws of quantum information and probability. This paradigm is supported by plenty of statistical bio-data collected at all bio-scales. QIB re ects the two fundamental principles: a) adaptivity; and, b) openness (bio-systems are fundamentally open). In addition, quantum adaptive dynamics provides the most generally possible mathematical representation of these principles.

Transmission as a basic process in microbial biology. Lwoff Award Prize Lecture.

PubMed

Baquero, Fernando

2017-11-01

Transmission is a basic process in biology and evolution, as it communicates different biological entities within and across hierarchical levels (from genes to holobionts) both in time and space. Vertical descent, replication, is transmission of information across generations (in the time dimension), and horizontal descent is transmission of information across compartments (in the space dimension). Transmission is essentially a communication process that can be studied by analogy of the classic information theory, based on 'emitters', 'messages' and 'receivers'. The analogy can be easily extended to the triad 'emigration', 'migration' and 'immigration'. A number of causes (forces) determine the emission, and another set of causes (energies) assures the reception. The message in fact is essentially constituted by 'meaningful' biological entities. A DNA sequence, a cell and a population have a semiotic dimension, are 'signs' that are eventually recognized (decoded) and integrated by receiver biological entities. In cis-acting or unenclosed transmission, the emitters and receivers correspond to separated entities of the same hierarchical level; in trans-acting or embedded transmission, the information flows between different, but frequently nested, hierarchical levels. The result (as in introgressive events) is constantly producing innovation and feeding natural selection, influencing also the evolution of transmission processes. This review is based on the concepts presented at the André Lwoff Award Lecture in the FEMS Microbiology Congress in Maastricht in 2015. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

HOW CAN BIOLOGICALLY-BASED MODELING OF ARSENIC KINETICS AND DYNAMICS INFORM THE RISK ASSESSMENT PROCESS?

EPA Science Inventory

Quantitative biologically-based models describing key events in the continuum from arsenic exposure to the development of adverse health effects provide a framework to integrate information obtained across diverse research areas. For example, genetic polymorphisms in arsenic met...

Bacteria as computers making computers

PubMed Central

Danchin, Antoine

2009-01-01

Various efforts to integrate biological knowledge into networks of interactions have produced a lively microbial systems biology. Putting molecular biology and computer sciences in perspective, we review another trend in systems biology, in which recursivity and information replace the usual concepts of differential equations, feedback and feedforward loops and the like. Noting that the processes of gene expression separate the genome from the cell machinery, we analyse the role of the separation between machine and program in computers. However, computers do not make computers. For cells to make cells requires a specific organization of the genetic program, which we investigate using available knowledge. Microbial genomes are organized into a paleome (the name emphasizes the role of the corresponding functions from the time of the origin of life), comprising a constructor and a replicator, and a cenome (emphasizing community-relevant genes), made up of genes that permit life in a particular context. The cell duplication process supposes rejuvenation of the machine and replication of the program. The paleome also possesses genes that enable information to accumulate in a ratchet-like process down the generations. The systems biology must include the dynamics of information creation in its future developments. PMID:19016882

Bacteria as computers making computers.

PubMed

Danchin, Antoine

2009-01-01

Various efforts to integrate biological knowledge into networks of interactions have produced a lively microbial systems biology. Putting molecular biology and computer sciences in perspective, we review another trend in systems biology, in which recursivity and information replace the usual concepts of differential equations, feedback and feedforward loops and the like. Noting that the processes of gene expression separate the genome from the cell machinery, we analyse the role of the separation between machine and program in computers. However, computers do not make computers. For cells to make cells requires a specific organization of the genetic program, which we investigate using available knowledge. Microbial genomes are organized into a paleome (the name emphasizes the role of the corresponding functions from the time of the origin of life), comprising a constructor and a replicator, and a cenome (emphasizing community-relevant genes), made up of genes that permit life in a particular context. The cell duplication process supposes rejuvenation of the machine and replication of the program. The paleome also possesses genes that enable information to accumulate in a ratchet-like process down the generations. The systems biology must include the dynamics of information creation in its future developments.

Impaired visual recognition of biological motion in schizophrenia.

PubMed

Kim, Jejoong; Doop, Mikisha L; Blake, Randolph; Park, Sohee

2005-09-15

Motion perception deficits have been suggested to be an important feature of schizophrenia but the behavioral consequences of such deficits are unknown. Biological motion refers to the movements generated by living beings. The human visual system rapidly and effortlessly detects and extracts socially relevant information from biological motion. A deficit in biological motion perception may have significant consequences for detecting and interpreting social information. Schizophrenia patients and matched healthy controls were tested on two visual tasks: recognition of human activity portrayed in point-light animations (biological motion task) and a perceptual control task involving detection of a grouped figure against the background noise (global-form task). Both tasks required detection of a global form against background noise but only the biological motion task required the extraction of motion-related information. Schizophrenia patients performed as well as the controls in the global-form task, but were significantly impaired on the biological motion task. In addition, deficits in biological motion perception correlated with impaired social functioning as measured by the Zigler social competence scale [Zigler, E., Levine, J. (1981). Premorbid competence in schizophrenia: what is being measured? Journal of Consulting and Clinical Psychology, 49, 96-105.]. The deficit in biological motion processing, which may be related to the previously documented deficit in global motion processing, could contribute to abnormal social functioning in schizophrenia.

Methods of information geometry in computational system biology (consistency between chemical and biological evolution).

PubMed

Astakhov, Vadim

2009-01-01

Interest in simulation of large-scale metabolic networks, species development, and genesis of various diseases requires new simulation techniques to accommodate the high complexity of realistic biological networks. Information geometry and topological formalisms are proposed to analyze information processes. We analyze the complexity of large-scale biological networks as well as transition of the system functionality due to modification in the system architecture, system environment, and system components. The dynamic core model is developed. The term dynamic core is used to define a set of causally related network functions. Delocalization of dynamic core model provides a mathematical formalism to analyze migration of specific functions in biosystems which undergo structure transition induced by the environment. The term delocalization is used to describe these processes of migration. We constructed a holographic model with self-poetic dynamic cores which preserves functional properties under those transitions. Topological constraints such as Ricci flow and Pfaff dimension were found for statistical manifolds which represent biological networks. These constraints can provide insight on processes of degeneration and recovery which take place in large-scale networks. We would like to suggest that therapies which are able to effectively implement estimated constraints, will successfully adjust biological systems and recover altered functionality. Also, we mathematically formulate the hypothesis that there is a direct consistency between biological and chemical evolution. Any set of causal relations within a biological network has its dual reimplementation in the chemistry of the system environment.

How Can Biologically-Based Modeling of Arsenic Kinetics and Dynamics Inform the Risk Assessment Process? -- ETD

EPA Science Inventory

Quantitative biologically-based models describing key events in the continuum from arsenic exposure to the development of adverse health effects provide a framework to integrate information obtained across diverse research areas. For example, genetic polymorphisms in arsenic me...

Comparative Study on Interaction of Form and Motion Processing Streams by Applying Two Different Classifiers in Mechanism for Recognition of Biological Movement

PubMed Central

2014-01-01

Research on psychophysics, neurophysiology, and functional imaging shows particular representation of biological movements which contains two pathways. The visual perception of biological movements formed through the visual system called dorsal and ventral processing streams. Ventral processing stream is associated with the form information extraction; on the other hand, dorsal processing stream provides motion information. Active basic model (ABM) as hierarchical representation of the human object had revealed novelty in form pathway due to applying Gabor based supervised object recognition method. It creates more biological plausibility along with similarity with original model. Fuzzy inference system is used for motion pattern information in motion pathway creating more robustness in recognition process. Besides, interaction of these paths is intriguing and many studies in various fields considered it. Here, the interaction of the pathways to get more appropriated results has been investigated. Extreme learning machine (ELM) has been implied for classification unit of this model, due to having the main properties of artificial neural networks, but crosses from the difficulty of training time substantially diminished in it. Here, there will be a comparison between two different configurations, interactions using synergetic neural network and ELM, in terms of accuracy and compatibility. PMID:25276860

Synthetic analog and digital circuits for cellular computation and memory.

PubMed

Purcell, Oliver; Lu, Timothy K

2014-10-01

Biological computation is a major area of focus in synthetic biology because it has the potential to enable a wide range of applications. Synthetic biologists have applied engineering concepts to biological systems in order to construct progressively more complex gene circuits capable of processing information in living cells. Here, we review the current state of computational genetic circuits and describe artificial gene circuits that perform digital and analog computation. We then discuss recent progress in designing gene networks that exhibit memory, and how memory and computation have been integrated to yield more complex systems that can both process and record information. Finally, we suggest new directions for engineering biological circuits capable of computation. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Pragmatic information in biology and physics.

PubMed

Roederer, Juan G

2016-03-13

I will show how an objective definition of the concept of information and the consideration of recent results about information processing in the human brain help clarify some fundamental aspects of physics and biology. Rather than attempting to define information ab initio, I introduce the concept of interaction between material bodies as a primary concept. Two distinct categories can be identified: (i) interactions which can always be reduced to a superposition of physical interactions (forces) between elementary constituents; and (ii) interactions between complex bodies which cannot be expressed as a superposition of interactions between parts, and in which patterns and forms (in space and/or time) play the determining role. Pragmatic information is then defined as the link between a given pattern and the ensuing pattern-specific change. I will show that pragmatic information is a biological concept; it plays no active role in the purely physical domain-it only does so when a living organism intervenes. The consequences for physics (including foundations of quantum mechanics) and biology (including brain function) will be discussed. This will include speculations about three fundamental transitions, from the quantum to the classical domain, from natural inanimate to living systems, and from subhuman to human brain information-processing operations, introduced here in their direct connection with the concept of pragmatic information. © 2016 The Author(s).

Global form and motion processing in healthy ageing.

PubMed

Agnew, Hannah C; Phillips, Louise H; Pilz, Karin S

2016-05-01

The ability to perceive biological motion has been shown to deteriorate with age, and it is assumed that older adults rely more on the global form than local motion information when processing point-light walkers. Further, it has been suggested that biological motion processing in ageing is related to a form-based global processing bias. Here, we investigated the relationship between older adults' preference for form information when processing point-light actions and an age-related form-based global processing bias. In a first task, we asked older (>60years) and younger adults (19-23years) to sequentially match three different point-light actions; normal actions that contained local motion and global form information, scrambled actions that contained primarily local motion information, and random-position actions that contained primarily global form information. Both age groups overall performed above chance in all three conditions, and were more accurate for actions that contained global form information. For random-position actions, older adults were less accurate than younger adults but there was no age-difference for normal or scrambled actions. These results indicate that both age groups rely more on global form than local motion to match point-light actions, but can use local motion on its own to match point-light actions. In a second task, we investigated form-based global processing biases using the Navon task. In general, participants were better at discriminating the local letters but faster at discriminating global letters. Correlations showed that there was no significant linear relationship between performance in the Navon task and biological motion processing, which suggests that processing biases in form- and motion-based tasks are unrelated. Copyright © 2016. Published by Elsevier B.V.

Huyghens Engines--a new concept and its embodiment for nano-micro interlevel information processing.

PubMed

Santoli, Salvatore

2009-02-01

Current criteria in Bionanotechnology based on software and sensor/actuator hardware of Artificial Intelligence for bioinspired nanostructured systems lack the nanophysical background and key mathematics to describe and mimick the biological hierarchies of nano-to-micro-integrated informational/energetic levels. It is argued that bionanoscale hardware/software undividable solidarity can be mimicked by artificial nanostructured systems featuring intra/interlevel information processing through the emerging organization principle of quantum holography, described by the Heisenberg group G and by harmonic analysis on G. From a property of G as a Lie group, quantum holography is shown to merge the quantum/classical dynamic-symbolic ongoings into the structure-function unity of biological sensing-information processing-actuating, while by Ch. Huyghens' principles about wave motion and coupled oscillators synchronization it applies to environmental waves of any kind, so embodying a universal information processing engine, dubbed Huyghens Engine, that mimicks the holistic nanobiological structure-function solidarity and the kinetics/thermodynamics of nano/micro interface information transfer.

Modeling biochemical transformation processes and information processing with Narrator.

PubMed

Mandel, Johannes J; Fuss, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

2007-03-27

Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Narrator is a flexible and intuitive systems biology tool. It is specifically intended for users aiming to construct and simulate dynamic models of biology without recourse to extensive mathematical detail. Its design facilitates mappings to different formal languages and frameworks. The combined set of features makes Narrator unique among tools of its kind. Narrator is implemented as Java software program and available as open-source from http://www.narrator-tool.org.

Modeling biochemical transformation processes and information processing with Narrator

PubMed Central

Mandel, Johannes J; Fuß, Hendrik; Palfreyman, Niall M; Dubitzky, Werner

2007-01-01

Background Software tools that model and simulate the dynamics of biological processes and systems are becoming increasingly important. Some of these tools offer sophisticated graphical user interfaces (GUIs), which greatly enhance their acceptance by users. Such GUIs are based on symbolic or graphical notations used to describe, interact and communicate the developed models. Typically, these graphical notations are geared towards conventional biochemical pathway diagrams. They permit the user to represent the transport and transformation of chemical species and to define inhibitory and stimulatory dependencies. A critical weakness of existing tools is their lack of supporting an integrative representation of transport, transformation as well as biological information processing. Results Narrator is a software tool facilitating the development and simulation of biological systems as Co-dependence models. The Co-dependence Methodology complements the representation of species transport and transformation together with an explicit mechanism to express biological information processing. Thus, Co-dependence models explicitly capture, for instance, signal processing structures and the influence of exogenous factors or events affecting certain parts of a biological system or process. This combined set of features provides the system biologist with a powerful tool to describe and explore the dynamics of life phenomena. Narrator's GUI is based on an expressive graphical notation which forms an integral part of the Co-dependence Methodology. Behind the user-friendly GUI, Narrator hides a flexible feature which makes it relatively easy to map models defined via the graphical notation to mathematical formalisms and languages such as ordinary differential equations, the Systems Biology Markup Language or Gillespie's direct method. This powerful feature facilitates reuse, interoperability and conceptual model development. Conclusion Narrator is a flexible and intuitive systems biology tool. It is specifically intended for users aiming to construct and simulate dynamic models of biology without recourse to extensive mathematical detail. Its design facilitates mappings to different formal languages and frameworks. The combined set of features makes Narrator unique among tools of its kind. Narrator is implemented as Java software program and available as open-source from . PMID:17389034

Theoretical aspects of cellular decision-making and information-processing.

PubMed

Kobayashi, Tetsuya J; Kamimura, Atsushi

2012-01-01

Microscopic biological processes have extraordinary complexity and variety at the sub-cellular, intra-cellular, and multi-cellular levels. In dealing with such complex phenomena, conceptual and theoretical frameworks are crucial, which enable us to understand seemingly different intra- and inter-cellular phenomena from unified viewpoints. Decision-making is one such concept that has attracted much attention recently. Since a number of cellular behavior can be regarded as processes to make specific actions in response to external stimuli, decision-making can cover and has been used to explain a broad range of different cellular phenomena [Balázsi et al. (Cell 144(6):910, 2011), Zeng et al. (Cell 141(4):682, 2010)]. Decision-making is also closely related to cellular information-processing because appropriate decisions cannot be made without exploiting the information that the external stimuli contain. Efficiency of information transduction and processing by intra-cellular networks determines the amount of information obtained, which in turn limits the efficiency of subsequent decision-making. Furthermore, information-processing itself can serve as another concept that is crucial for understanding of other biological processes than decision-making. In this work, we review recent theoretical developments on cellular decision-making and information-processing by focusing on the relation between these two concepts.

Processing Biological Gender and Number Information during Chinese Pronoun Resolution: ERP Evidence for Functional Differentiation

ERIC Educational Resources Information Center

Xu, Xiaodong; Jiang, Xiaoming; Zhou, Xiaolin

2013-01-01

There have been a number of behavioral and neural studies on the processing of syntactic gender and number agreement information, marked by different morpho-syntactic features during sentence comprehension. By using the event-related potential (ERP) technique, the present study investigated whether the processing of semantic gender information and…

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

Laser apparatus and method for microscopic and spectroscopic analysis and processing of biological cells

DOEpatents

Gourley, Paul L.; Gourley, Mark F.

1997-01-01

An apparatus and method for microscopic and spectroscopic analysis and processing of biological cells. The apparatus comprises a laser having an analysis region within the laser cavity for containing one or more biological cells to be analyzed. The presence of a cell within the analysis region in superposition with an activated portion of a gain medium of the laser acts to encode information about the cell upon the laser beam, the cell information being recoverable by an analysis means that preferably includes an array photodetector such as a CCD camera and a spectrometer. The apparatus and method may be used to analyze biomedical cells including blood cells and the like, and may include processing means for manipulating, sorting, or eradicating cells after analysis thereof.

Laser apparatus and method for microscopic and spectroscopic analysis and processing of biological cells

DOEpatents

Gourley, P.L.; Gourley, M.F.

1997-03-04

An apparatus and method are disclosed for microscopic and spectroscopic analysis and processing of biological cells. The apparatus comprises a laser having an analysis region within the laser cavity for containing one or more biological cells to be analyzed. The presence of a cell within the analysis region in superposition with an activated portion of a gain medium of the laser acts to encode information about the cell upon the laser beam, the cell information being recoverable by an analysis means that preferably includes an array photodetector such as a CCD camera and a spectrometer. The apparatus and method may be used to analyze biomedical cells including blood cells and the like, and may include processing means for manipulating, sorting, or eradicating cells after analysis. 20 figs.

Learning cell biology as a team: a project-based approach to upper-division cell biology.

PubMed

Wright, Robin; Boggs, James

2002-01-01

To help students develop successful strategies for learning how to learn and communicate complex information in cell biology, we developed a quarter-long cell biology class based on team projects. Each team researches a particular human disease and presents information about the cellular structure or process affected by the disease, the cellular and molecular biology of the disease, and recent research focused on understanding the cellular mechanisms of the disease process. To support effective teamwork and to help students develop collaboration skills useful for their future careers, we provide training in working in small groups. A final poster presentation, held in a public forum, summarizes what students have learned throughout the quarter. Although student satisfaction with the course is similar to that of standard lecture-based classes, a project-based class offers unique benefits to both the student and the instructor.

Information Memory Processing and Retrieval: The Use of Information Theory to Study Primacy and Recency Characteristics of Ninth Grade Science Students Processing Learning Tasks.

ERIC Educational Resources Information Center

Dunlop, David L.

Reported is another study related to the Project on an Information Memory Model. This study involved using information theory to investigate the concepts of primacy and recency as they were exhibited by ninth-grade science students while processing a biological sorting problem and an immediate, abstract recall task. Two hundred randomly selected…

Computer retina that models the primate retina

NASA Astrophysics Data System (ADS)

Shah, Samir; Levine, Martin D.

1994-06-01

At the retinal level, the strategies utilized by biological visual systems allow them to outperform machine vision systems, serving to motivate the design of electronic or `smart' sensors based on similar principles. Design of such sensors in silicon first requires a model of retinal information processing which captures the essential features exhibited by biological retinas. In this paper, a simple retinal model is presented, which qualitatively accounts for the achromatic information processing in the primate cone system. The model exhibits many of the properties found in biological retina such as data reduction through nonuniform sampling, adaptation to a large dynamic range of illumination levels, variation of visual acuity with illumination level, and enhancement of spatio temporal contrast information. The model is validated by replicating experiments commonly performed by electrophysiologists on biological retinas and comparing the response of the computer retina to data from experiments in monkeys. In addition, the response of the model to synthetic images is shown. The experiments demonstrate that the model behaves in a manner qualitatively similar to biological retinas and thus may serve as a basis for the development of an `artificial retina.'

The application of biological motion research: biometrics, sport, and the military.

PubMed

Steel, Kylie; Ellem, Eathan; Baxter, David

2015-02-01

The body of research that examines the perception of biological motion is extensive and explores the factors that are perceived from biological motion and how this information is processed. This research demonstrates that individuals are able to use relative (temporal and spatial) information from a person's movement to recognize factors, including gender, age, deception, emotion, intention, and action. The research also demonstrates that movement presents idiosyncratic properties that allow individual discrimination, thus providing the basis for significant exploration in the domain of biometrics and social signal processing. Medical forensics, safety garments, and victim selection domains also have provided a history of research on the perception of biological motion applications; however, a number of additional domains present opportunities for application that have not been explored in depth. Therefore, the purpose of this paper is to present an overview of the current applications of biological motion-based research and to propose a number of areas where biological motion research, specific to recognition, could be applied in the future.

Effects of aerobic and anaerobic biological processes on leaching of heavy metals from soil amended with sewage sludge compost.

PubMed

Fang, Wen; Wei, Yonghong; Liu, Jianguo; Kosson, David S; van der Sloot, Hans A; Zhang, Peng

2016-12-01

The risk from leaching of heavy metals is a major factor hindering land application of sewage sludge compost (SSC). Understanding the change in heavy metal leaching resulting from soil biological processes provides important information for assessing long-term behavior of heavy metals in the compost amended soil. In this paper, 180days aerobic incubation and 240days anaerobic incubation were conducted to investigate the effects of the aerobic and anaerobic biological processes on heavy metal leaching from soil amended with SSC, combined with chemical speciation modeling. Results showed that leaching concentrations of heavy metals at natural pH were similar before and after biological process. However, the major processes controlling heavy metals were influenced by the decrease of DOC with organic matter mineralization during biological processes. Mineralization of organic matter lowered the contribution of DOC-complexation to Ni and Zn leaching. Besides, the reducing condition produced by biological processes, particularly by the anaerobic biological process, resulted in the loss of sorption sites for As on Fe hydroxide, which increased the potential risk of As release at alkaline pH. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantum biological channel modeling and capacity calculation.

PubMed

Djordjevic, Ivan B

2012-12-10

Quantum mechanics has an important role in photosynthesis, magnetoreception, and evolution. There were many attempts in an effort to explain the structure of genetic code and transfer of information from DNA to protein by using the concepts of quantum mechanics. The existing biological quantum channel models are not sufficiently general to incorporate all relevant contributions responsible for imperfect protein synthesis. Moreover, the problem of determination of quantum biological channel capacity is still an open problem. To solve these problems, we construct the operator-sum representation of biological channel based on codon basekets (basis vectors), and determine the quantum channel model suitable for study of the quantum biological channel capacity and beyond. The transcription process, DNA point mutations, insertions, deletions, and translation are interpreted as the quantum noise processes. The various types of quantum errors are classified into several broad categories: (i) storage errors that occur in DNA itself as it represents an imperfect storage of genetic information, (ii) replication errors introduced during DNA replication process, (iii) transcription errors introduced during DNA to mRNA transcription, and (iv) translation errors introduced during the translation process. By using this model, we determine the biological quantum channel capacity and compare it against corresponding classical biological channel capacity. We demonstrate that the quantum biological channel capacity is higher than the classical one, for a coherent quantum channel model, suggesting that quantum effects have an important role in biological systems. The proposed model is of crucial importance towards future study of quantum DNA error correction, developing quantum mechanical model of aging, developing the quantum mechanical models for tumors/cancer, and study of intracellular dynamics in general.

Zsyntax: a formal language for molecular biology with projected applications in text mining and biological prediction.

PubMed

Boniolo, Giovanni; D'Agostino, Marcello; Di Fiore, Pier Paolo

2010-03-03

We propose a formal language that allows for transposing biological information precisely and rigorously into machine-readable information. This language, which we call Zsyntax (where Z stands for the Greek word zetaomegaeta, life), is grounded on a particular type of non-classical logic, and it can be used to write algorithms and computer programs. We present it as a first step towards a comprehensive formal language for molecular biology in which any biological process can be written and analyzed as a sort of logical "deduction". Moreover, we illustrate the potential value of this language, both in the field of text mining and in that of biological prediction.

The Interface between Physics and Biology: An Unexplored Territory.

ERIC Educational Resources Information Center

Marx, George

1980-01-01

Discusses from the physicist's point of view the connection between biology and physics and the usefulness of physical laws for understanding biological processes. Discusses these fields of research in secondary school science: molecular science, regulation, statistics and information, corrosion and evolution, chance and necessity, and…

INACTIVATION OF BIOLOGICAL CONTAMINANTS IN DRINKING WATER IN RESPONSE TO A TERRORIST ATTACK

EPA Science Inventory

In the event of an intentional biological contamination of a drinking water treatment and distribution system, information on the removal and/or inactivation of known biological agents by drinking water treatment processes is needed. This project was initiated to determine what i...

Designer cell signal processing circuits for biotechnology

PubMed Central

Bradley, Robert W.; Wang, Baojun

2015-01-01

Microorganisms are able to respond effectively to diverse signals from their environment and internal metabolism owing to their inherent sophisticated information processing capacity. A central aim of synthetic biology is to control and reprogramme the signal processing pathways within living cells so as to realise repurposed, beneficial applications ranging from disease diagnosis and environmental sensing to chemical bioproduction. To date most examples of synthetic biological signal processing have been built based on digital information flow, though analogue computing is being developed to cope with more complex operations and larger sets of variables. Great progress has been made in expanding the categories of characterised biological components that can be used for cellular signal manipulation, thereby allowing synthetic biologists to more rationally programme increasingly complex behaviours into living cells. Here we present a current overview of the components and strategies that exist for designer cell signal processing and decision making, discuss how these have been implemented in prototype systems for therapeutic, environmental, and industrial biotechnological applications, and examine emerging challenges in this promising field. PMID:25579192

The use of writing assignments to help students synthesize content in upper-level undergraduate biology courses.

PubMed

Sparks-Thissen, Rebecca L

2017-02-01

Biology education is undergoing a transformation toward a more student-centered, inquiry-driven classroom. Many educators have designed engaging assignments that are designed to help undergraduate students gain exposure to the scientific process and data analysis. One of these types of assignments is use of a grant proposal assignment. Many instructors have used these assignments in lecture-based courses to help students process information in the literature and apply that information to a novel problem such as design of an antiviral drug or a vaccine. These assignments have been helpful in engaging students in the scientific process in the absence of an inquiry-driven laboratory. This commentary discusses the application of these grant proposal writing assignments to undergraduate biology courses. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Information Science Research: The Search for the Nature of Information.

ERIC Educational Resources Information Center

Kochen, Manfred

1984-01-01

High-level scientific research in the information sciences is illustrated by sampling of recent discoveries involving adaptive information processing strategies, computer and information systems, centroid scaling, economic growth of computer and communication industries, and information flow in biological systems. Relationship of information…

Using Primary Literature in an Undergraduate Assignment: Demonstrating Connections among Cellular Processes

ERIC Educational Resources Information Center

Yeong, Foong May

2015-01-01

Learning basic cell biology in an essential module can be daunting to second-year undergraduates, given the depth of information that is provided in major molecular and cell biology textbooks. Moreover, lectures on cellular pathways are organised into sections, such that at the end of lectures, students might not see how various processes are…

A comparative approach for the investigation of biological information processing: An examination of the structure and function of computer hard drives and DNA

PubMed Central

2010-01-01

Background The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Methods Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Results Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological systems do not have an external source for a map of their stored information or for an operational instruction set; rather, they must contain an organizational template conserved within their intra-nuclear architecture that "manipulates" the laws of chemistry and physics into a highly robust instruction set. We propose that the epigenetic structure of the intra-nuclear environment and the non-coding RNA may play the roles of a Biological File Allocation Table (BFAT) and biological operating system (Bio-OS) in eukaryotic cells. Conclusions The comparison of functional and structural characteristics of the DNA complex and the computer hard drive leads to a new descriptive paradigm that identifies the DNA as a dynamic storage system of biological information. This system is embodied in an autonomous operating system that inductively follows organizational structures, data hierarchy and executable operations that are well understood in the computer science industry. Characterizing the "DNA hard drive" in this fashion can lead to insights arising from discrepancies in the descriptive framework, particularly with respect to positing the role of epigenetic processes in an information-processing context. Further expansions arising from this comparison include the view of cells as parallel computing machines and a new approach towards characterizing cellular control systems. PMID:20092652

A comparative approach for the investigation of biological information processing: an examination of the structure and function of computer hard drives and DNA.

PubMed

D'Onofrio, David J; An, Gary

2010-01-21

The robust storage, updating and utilization of information are necessary for the maintenance and perpetuation of dynamic systems. These systems can exist as constructs of metal-oxide semiconductors and silicon, as in a digital computer, or in the "wetware" of organic compounds, proteins and nucleic acids that make up biological organisms. We propose that there are essential functional properties of centralized information-processing systems; for digital computers these properties reside in the computer's hard drive, and for eukaryotic cells they are manifest in the DNA and associated structures. Presented herein is a descriptive framework that compares DNA and its associated proteins and sub-nuclear structure with the structure and function of the computer hard drive. We identify four essential properties of information for a centralized storage and processing system: (1) orthogonal uniqueness, (2) low level formatting, (3) high level formatting and (4) translation of stored to usable form. The corresponding aspects of the DNA complex and a computer hard drive are categorized using this classification. This is intended to demonstrate a functional equivalence between the components of the two systems, and thus the systems themselves. Both the DNA complex and the computer hard drive contain components that fulfill the essential properties of a centralized information storage and processing system. The functional equivalence of these components provides insight into both the design process of engineered systems and the evolved solutions addressing similar system requirements. However, there are points where the comparison breaks down, particularly when there are externally imposed information-organizing structures on the computer hard drive. A specific example of this is the imposition of the File Allocation Table (FAT) during high level formatting of the computer hard drive and the subsequent loading of an operating system (OS). Biological systems do not have an external source for a map of their stored information or for an operational instruction set; rather, they must contain an organizational template conserved within their intra-nuclear architecture that "manipulates" the laws of chemistry and physics into a highly robust instruction set. We propose that the epigenetic structure of the intra-nuclear environment and the non-coding RNA may play the roles of a Biological File Allocation Table (BFAT) and biological operating system (Bio-OS) in eukaryotic cells. The comparison of functional and structural characteristics of the DNA complex and the computer hard drive leads to a new descriptive paradigm that identifies the DNA as a dynamic storage system of biological information. This system is embodied in an autonomous operating system that inductively follows organizational structures, data hierarchy and executable operations that are well understood in the computer science industry. Characterizing the "DNA hard drive" in this fashion can lead to insights arising from discrepancies in the descriptive framework, particularly with respect to positing the role of epigenetic processes in an information-processing context. Further expansions arising from this comparison include the view of cells as parallel computing machines and a new approach towards characterizing cellular control systems.

Towards a Unified Approach to Information Integration - A review paper on data/information fusion

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

Whitney, Paul D.; Posse, Christian; Lei, Xingye C.

2005-10-14

Information or data fusion of data from different sources are ubiquitous in many applications, from epidemiology, medical, biological, political, and intelligence to military applications. Data fusion involves integration of spectral, imaging, text, and many other sensor data. For example, in epidemiology, information is often obtained based on many studies conducted by different researchers at different regions with different protocols. In the medical field, the diagnosis of a disease is often based on imaging (MRI, X-Ray, CT), clinical examination, and lab results. In the biological field, information is obtained based on studies conducted on many different species. In military field, informationmore » is obtained based on data from radar sensors, text messages, chemical biological sensor, acoustic sensor, optical warning and many other sources. Many methodologies are used in the data integration process, from classical, Bayesian, to evidence based expert systems. The implementation of the data integration ranges from pure software design to a mixture of software and hardware. In this review we summarize the methodologies and implementations of data fusion process, and illustrate in more detail the methodologies involved in three examples. We propose a unified multi-stage and multi-path mapping approach to the data fusion process, and point out future prospects and challenges.« less

Complexity Level Analysis Revisited: What Can 30 Years of Hindsight Tell Us about How the Brain Might Represent Visual Information?

PubMed Central

Tsotsos, John K.

2017-01-01

Much has been written about how the biological brain might represent and process visual information, and how this might inspire and inform machine vision systems. Indeed, tremendous progress has been made, and especially during the last decade in the latter area. However, a key question seems too often, if not mostly, be ignored. This question is simply: do proposed solutions scale with the reality of the brain's resources? This scaling question applies equally to brain and to machine solutions. A number of papers have examined the inherent computational difficulty of visual information processing using theoretical and empirical methods. The main goal of this activity had three components: to understand the deep nature of the computational problem of visual information processing; to discover how well the computational difficulty of vision matches to the fixed resources of biological seeing systems; and, to abstract from the matching exercise the key principles that lead to the observed characteristics of biological visual performance. This set of components was termed complexity level analysis in Tsotsos (1987) and was proposed as an important complement to Marr's three levels of analysis. This paper revisits that work with the advantage that decades of hindsight can provide. PMID:28848458

Complexity Level Analysis Revisited: What Can 30 Years of Hindsight Tell Us about How the Brain Might Represent Visual Information?

PubMed

Tsotsos, John K

2017-01-01

Much has been written about how the biological brain might represent and process visual information, and how this might inspire and inform machine vision systems. Indeed, tremendous progress has been made, and especially during the last decade in the latter area. However, a key question seems too often, if not mostly, be ignored. This question is simply: do proposed solutions scale with the reality of the brain's resources? This scaling question applies equally to brain and to machine solutions. A number of papers have examined the inherent computational difficulty of visual information processing using theoretical and empirical methods. The main goal of this activity had three components: to understand the deep nature of the computational problem of visual information processing; to discover how well the computational difficulty of vision matches to the fixed resources of biological seeing systems; and, to abstract from the matching exercise the key principles that lead to the observed characteristics of biological visual performance. This set of components was termed complexity level analysis in Tsotsos (1987) and was proposed as an important complement to Marr's three levels of analysis. This paper revisits that work with the advantage that decades of hindsight can provide.

A cascade model of information processing and encoding for retinal prosthesis.

PubMed

Pei, Zhi-Jun; Gao, Guan-Xin; Hao, Bo; Qiao, Qing-Li; Ai, Hui-Jian

2016-04-01

Retinal prosthesis offers a potential treatment for individuals suffering from photoreceptor degeneration diseases. Establishing biological retinal models and simulating how the biological retina convert incoming light signal into spike trains that can be properly decoded by the brain is a key issue. Some retinal models have been presented, ranking from structural models inspired by the layered architecture to functional models originated from a set of specific physiological phenomena. However, Most of these focus on stimulus image compression, edge detection and reconstruction, but do not generate spike trains corresponding to visual image. In this study, based on state-of-the-art retinal physiological mechanism, including effective visual information extraction, static nonlinear rectification of biological systems and neurons Poisson coding, a cascade model of the retina including the out plexiform layer for information processing and the inner plexiform layer for information encoding was brought forward, which integrates both anatomic connections and functional computations of retina. Using MATLAB software, spike trains corresponding to stimulus image were numerically computed by four steps: linear spatiotemporal filtering, static nonlinear rectification, radial sampling and then Poisson spike generation. The simulated results suggested that such a cascade model could recreate visual information processing and encoding functionalities of the retina, which is helpful in developing artificial retina for the retinally blind.

DNA codes for nanoscience.

PubMed

Samorì, Bruno; Zuccheri, Giampaolo

2005-02-11

The nanometer scale is a special place where all sciences meet and develop a particularly strong interdisciplinarity. While biology is a source of inspiration for nanoscientists, chemistry has a central role in turning inspirations and methods from biological systems to nanotechnological use. DNA is the biological molecule by which nanoscience and nanotechnology is mostly fascinated. Nature uses DNA not only as a repository of the genetic information, but also as a controller of the expression of the genes it contains. Thus, there are codes embedded in the DNA sequence that serve to control recognition processes on the atomic scale, such as the base pairing, and others that control processes taking place on the nanoscale. From the chemical point of view, DNA is the supramolecular building block with the highest informational content. Nanoscience has therefore the opportunity of using DNA molecules to increase the level of complexity and efficiency in self-assembling and self-directing processes.

Broadband photon pair generation in green fluorescent proteins through spontaneous four-wave mixing

PubMed Central

Shi, Siyuan; Thomas, Abu; Corzo, Neil V.; Kumar, Prem; Huang, Yuping; Lee, Kim Fook

2016-01-01

Recent studies in quantum biology suggest that quantum mechanics help us to explore quantum processes in biological system. Here, we demonstrate generation of photon pairs through spontaneous four-wave mixing process in naturally occurring fluorescent proteins. We develop a general empirical method for analyzing the relative strength of nonlinear optical interaction processes in five different organic fluorophores. Our results indicate that the generation of photon pairs in green fluorescent proteins is subject to less background noises than in other fluorophores, leading to a coincidence-to-accidental ratio ~145. As such proteins can be genetically engineered and fused to many biological cells, our experiment enables a new platform for quantum information processing in a biological environment such as biomimetic quantum networks and quantum sensors. PMID:27076032

On the analysis of complex biological supply chains: From Process Systems Engineering to Quantitative Systems Pharmacology.

PubMed

Rao, Rohit T; Scherholz, Megerle L; Hartmanshenn, Clara; Bae, Seul-A; Androulakis, Ioannis P

2017-12-05

The use of models in biology has become particularly relevant as it enables investigators to develop a mechanistic framework for understanding the operating principles of living systems as well as in quantitatively predicting their response to both pathological perturbations and pharmacological interventions. This application has resulted in a synergistic convergence of systems biology and pharmacokinetic-pharmacodynamic modeling techniques that has led to the emergence of quantitative systems pharmacology (QSP). In this review, we discuss how the foundational principles of chemical process systems engineering inform the progressive development of more physiologically-based systems biology models.

Attention, biological motion, and action recognition.

PubMed

Thompson, James; Parasuraman, Raja

2012-01-02

Interacting with others in the environment requires that we perceive and recognize their movements and actions. Neuroimaging and neuropsychological studies have indicated that a number of brain regions, particularly the superior temporal sulcus, are involved in a number of processes essential for action recognition, including the processing of biological motion and processing the intentions of actions. We review the behavioral and neuroimaging evidence suggesting that while some aspects of action recognition might be rapid and effective, they are not necessarily automatic. Attention is particularly important when visual information about actions is degraded or ambiguous, or if competing information is present. We present evidence indicating that neural responses associated with the processing of biological motion are strongly modulated by attention. In addition, behavioral and neuroimaging evidence shows that drawing inferences from the actions of others is attentionally demanding. The role of attention in action observation has implications for everyday social interactions and workplace applications that depend on observing, understanding and interpreting actions. Published by Elsevier Inc.

Quantum information processing in the radical-pair mechanism: Haberkorn's theory violates the Ozawa entropy bound

NASA Astrophysics Data System (ADS)

Mouloudakis, K.; Kominis, I. K.

2017-02-01

Radical-ion-pair reactions, central for understanding the avian magnetic compass and spin transport in photosynthetic reaction centers, were recently shown to be a fruitful paradigm of the new synthesis of quantum information science with biological processes. We show here that the master equation so far constituting the theoretical foundation of spin chemistry violates fundamental bounds for the entropy of quantum systems, in particular the Ozawa bound. In contrast, a recently developed theory based on quantum measurements, quantum coherence measures, and quantum retrodiction, thus exemplifying the paradigm of quantum biology, satisfies the Ozawa bound as well as the Lanford-Robinson bound on information extraction. By considering Groenewold's information, the quantum information extracted during the reaction, we reproduce the known and unravel other magnetic-field effects not conveyed by reaction yields.

Biological degradation of wood-plastic composites (WPC) and strategies for improving the resistance of WPC against biological decay

Treesearch

Anke Schirp; Rebecca E. Ibach; David E. Pendleton; Michael P. Wolcott

2008-01-01

Much of the research on wood-plastic composites (WPC) has focused on formulation development and processing while high biological durability of the material was assumed. The gap between assumption and knowledge in biodeterioration of WPC needs to be reduced. Although some information on the short-term resistance of WPC against biological degradation is available, long-...

Two faces of entropy and information in biological systems.

PubMed

Mitrokhin, Yuriy

2014-10-21

The article attempts to overcome the well-known paradox of contradictions between the emerging biological organization and entropy production in biological systems. It is assumed that quality, speculative correlation between entropy and antientropy processes taking place both in the past and today in the metabolic and genetic cellular systems may be perfectly authorized for adequate description of the evolution of biological organization. So far as thermodynamic entropy itself cannot compensate for the high degree of organization which exists in the cell, we discuss the mode of conjunction of positive entropy events (mutations) in the genetic systems of the past generations and the formation of organized structures of current cells. We argue that only the information which is generated in the conditions of the information entropy production (mutations and other genome reorganization) in genetic systems of the past generations provides the physical conjunction of entropy and antientropy processes separated from each other in time generations. It is readily apparent from the requirements of the Second law of thermodynamics. Copyright © 2014 Elsevier Ltd. All rights reserved.

Focused Metabolite Profiling for Dissecting Cellular and Molecular Processes of Living Organisms in Space Environments

NASA Technical Reports Server (NTRS)

2008-01-01

Regulatory control in biological systems is exerted at all levels within the central dogma of biology. Metabolites are the end products of all cellular regulatory processes and reflect the ultimate outcome of potential changes suggested by genomics and proteomics caused by an environmental stimulus or genetic modification. Following on the heels of genomics, transcriptomics, and proteomics, metabolomics has become an inevitable part of complete-system biology because none of the lower "-omics" alone provide direct information about how changes in mRNA or protein are coupled to changes in biological function. The challenges are much greater than those encountered in genomics because of the greater number of metabolites and the greater diversity of their chemical structures and properties. To meet these challenges, much developmental work is needed, including (1) methodologies for unbiased extraction of metabolites and subsequent quantification, (2) algorithms for systematic identification of metabolites, (3) expertise and competency in handling a large amount of information (data set), and (4) integration of metabolomics with other "omics" and data mining (implication of the information). This article reviews the project accomplishments.

Abstracts of Research, July 1975-June 1976.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Computer and Information Science Research Center.

Abstracts of research papers in computer and information science are given for 62 papers in the areas of information storage and retrieval; computer facilities; information analysis; linguistics analysis; artificial intelligence; information processes in physical, biological, and social systems; mathematical technigues; systems programming;…

Silicon photonics for neuromorphic information processing

NASA Astrophysics Data System (ADS)

Bienstman, Peter; Dambre, Joni; Katumba, Andrew; Freiberger, Matthias; Laporte, Floris; Lugnan, Alessio

2018-02-01

We present our latest results on silicon photonics neuromorphic information processing based a.o. on techniques like reservoir computing. We will discuss aspects like scalability, novel architectures for enhanced power efficiency, as well as all-optical readout. Additionally, we will touch upon new machine learning techniques to operate these integrated readouts. Finally, we will show how these systems can be used for high-speed low-power information processing for applications like recognition of biological cells.

The detection and analysis of point processes in biological signals

NASA Technical Reports Server (NTRS)

Anderson, D. J.; Correia, M. J.

1977-01-01

A pragmatic approach to the detection and analysis of discrete events in biomedical signals is taken. Examples from both clinical and basic research are provided. Introductory sections discuss not only discrete events which are easily extracted from recordings by conventional threshold detectors but also events embedded in other information carrying signals. The primary considerations are factors governing event-time resolution and the effects limits to this resolution have on the subsequent analysis of the underlying process. The analysis portion describes tests for qualifying the records as stationary point processes and procedures for providing meaningful information about the biological signals under investigation. All of these procedures are designed to be implemented on laboratory computers of modest computational capacity.

Redox-capacitor to connect electrochemistry to redox-biology.

PubMed

Kim, Eunkyoung; Leverage, W Taylor; Liu, Yi; White, Ian M; Bentley, William E; Payne, Gregory F

2014-01-07

It is well-established that redox-reactions are integral to biology for energy harvesting (oxidative phosphorylation), immune defense (oxidative burst) and drug metabolism (phase I reactions), yet there is emerging evidence that redox may play broader roles in biology (e.g., redox signaling). A critical challenge is the need for tools that can probe biologically-relevant redox interactions simply, rapidly and without the need for a comprehensive suite of analytical methods. We propose that electrochemistry may provide such a tool. In this tutorial review, we describe recent studies with a redox-capacitor film that can serve as a bio-electrode interface that can accept, store and donate electrons from mediators commonly used in electrochemistry and also in biology. Specifically, we (i) describe the fabrication of this redox-capacitor from catechols and the polysaccharide chitosan, (ii) discuss the mechanistic basis for electron exchange, (iii) illustrate the properties of this redox-capacitor and its capabilities for promoting redox-communication between biology and electrodes, and (iv) suggest the potential for enlisting signal processing strategies to "extract" redox information. We believe these initial studies indicate broad possibilities for enlisting electrochemistry and signal processing to acquire "systems level" redox information from biology.

Multi-level and hybrid modelling approaches for systems biology.

PubMed

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

2017-01-01

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

Novel method of extracting motion from natural movies.

PubMed

Suzuki, Wataru; Ichinohe, Noritaka; Tani, Toshiki; Hayami, Taku; Miyakawa, Naohisa; Watanabe, Satoshi; Takeichi, Hiroshige

2017-11-01

The visual system in primates can be segregated into motion and shape pathways. Interaction occurs at multiple stages along these pathways. Processing of shape-from-motion and biological motion is considered to be a higher-order integration process involving motion and shape information. However, relatively limited types of stimuli have been used in previous studies on these integration processes. We propose a new algorithm to extract object motion information from natural movies and to move random dots in accordance with the information. The object motion information is extracted by estimating the dynamics of local normal vectors of the image intensity projected onto the x-y plane of the movie. An electrophysiological experiment on two adult common marmoset monkeys (Callithrix jacchus) showed that the natural and random dot movies generated with this new algorithm yielded comparable neural responses in the middle temporal visual area. In principle, this algorithm provided random dot motion stimuli containing shape information for arbitrary natural movies. This new method is expected to expand the neurophysiological and psychophysical experimental protocols to elucidate the integration processing of motion and shape information in biological systems. The novel algorithm proposed here was effective in extracting object motion information from natural movies and provided new motion stimuli to investigate higher-order motion information processing. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

c-Mantic: A Cytoscape plugin for Semantic Web

EPA Science Inventory

Semantic Web tools can streamline the process of storing, analyzing and sharing biological information. Visualization is important for communicating such complex biological relationships. Here we use the flexibility and speed of the Cytoscape platform to interactively visualize s...

In Silico Dynamics: computer simulation in a Virtual Embryo (SOT)

EPA Science Inventory

Abstract: Utilizing cell biological information to predict higher order biological processes is a significant challenge in predictive toxicology. This is especially true for highly dynamical systems such as the embryo where morphogenesis, growth and differentiation require preci...

A comparison of form processing involved in the perception of biological and nonbiological movements

PubMed Central

Thurman, Steven M.; Lu, Hongjing

2016-01-01

Although there is evidence for specialization in the human brain for processing biological motion per se, few studies have directly examined the specialization of form processing in biological motion perception. The current study was designed to systematically compare form processing in perception of biological (human walkers) to nonbiological (rotating squares) stimuli. Dynamic form-based stimuli were constructed with conflicting form cues (position and orientation), such that the objects were perceived to be moving ambiguously in two directions at once. In Experiment 1, we used the classification image technique to examine how local form cues are integrated across space and time in a bottom-up manner. By comparing with a Bayesian observer model that embodies generic principles of form analysis (e.g., template matching) and integrates form information according to cue reliability, we found that human observers employ domain-general processes to recognize both human actions and nonbiological object movements. Experiments 2 and 3 found differential top-down effects of spatial context on perception of biological and nonbiological forms. When a background does not involve social information, observers are biased to perceive foreground object movements in the direction opposite to surrounding motion. However, when a background involves social cues, such as a crowd of similar objects, perception is biased toward the same direction as the crowd for biological walking stimuli, but not for rotating nonbiological stimuli. The model provided an accurate account of top-down modulations by adjusting the prior probabilities associated with the internal templates, demonstrating the power and flexibility of the Bayesian approach for visual form perception. PMID:26746875

On the Concept of Information and Its Role in Nature

NASA Astrophysics Data System (ADS)

Roederer, Juan G.

2003-03-01

In this article we address some fundamental questions concerning information: Can the existing laws of physics adequately deal with the most striking property of information, namely to cause specific changes in the structure and energy flows of a complex system, without the information in itself representing fields, forces or energy in any of their characteristic forms? Or is information irreducible to the laws of physics and chemistry? Are information and complexity related concepts? Does the Universe, in its evolution, constantly generate new information? Or are information and information-processing exclusive attributes of living systems, related to the very definition of life? If that were the case, what happens with the physical meanings of entropy in statistical mechanics or wave function in quantum mechanics? How many distinct classes of information and information processing do exist in the biological world? How does information appear in Darwinian evolution? Does the human brain have unique properties or capabilities in terms of information processing? In what ways does information processing bring about human self-consciousness? We shall introduce the meaning of "information" in a way that is detached from human technological systems and related algorithms and semantics, and that is not based on any mathematical formula. To accomplish this we turn to the concept of interaction as the basic departing point, and identify two fundamentally different classes, with information and information-processing appearing as the key discriminator: force-field driven interactions between elementary particles and ensembles of particles in the macroscopic physical domain, and information-based interactions between certain kinds of complex systems that form the biological domain. We shall show that in an abiotic world, information plays no role; physical interactions just happen, they are driven by energy exchange between the interacting parts and do not require any operations of information processing. Information only enters the non-living physical world when a living thing interacts with it-and when a scientist extracts information through observation and measurement. But for living organisms, information is the very essence of their existence: to maintain a long-term state of unstable thermodynamic equilibrium with its surroundings, consistently increase its organization and reproduce, an organism has to rely on information-based interactions in which form or pattern, not energy, is the controlling factor. This latter class comprises biomolecular information processes controlling the metabolism, growth, multiplication and differentiation of cells, and neural information processes controlling animal behavior and intelligence. The only way new information can appear is through the process of biological evolution and, in the short term, through sensory acquisition and the manipulation of images in the nervous system. Non-living informational systems such as books, computers, AI systems and other artifacts, as well as living organisms that are the result of breeding or cloning, are planned by human beings and will not be considered here.

The Physical Microbe; An introduction to noise, control, and communication in the prokaryotic cell

NASA Astrophysics Data System (ADS)

Hagen, Stephen J.

2017-10-01

Physical biology is a fusion of biology and physics. This book narrows down the scope of physical biology by focusing on the microbial cell; exploring the physical phenomena of noise, feedback, and variability that arise in the cellular information-processing circuits used by bacteria. It looks at the microbe from a physics perspective, asking how the cell optimizes its function to live within the constraints of physics. It introduces a physical and information-based (as opposed to microbiological) perspective on communication and signalling between microbes.

Fostering synergy between cell biology and systems biology.

PubMed

Eddy, James A; Funk, Cory C; Price, Nathan D

2015-08-01

In the shared pursuit of elucidating detailed mechanisms of cell function, systems biology presents a natural complement to ongoing efforts in cell biology. Systems biology aims to characterize biological systems through integrated and quantitative modeling of cellular information. The process of model building and analysis provides value through synthesizing and cataloging information about cells and molecules, predicting mechanisms and identifying generalizable themes, generating hypotheses and guiding experimental design, and highlighting knowledge gaps and refining understanding. In turn, incorporating domain expertise and experimental data is crucial for building towards whole cell models. An iterative cycle of interaction between cell and systems biologists advances the goals of both fields and establishes a framework for mechanistic understanding of the genome-to-phenome relationship. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Text mining and its potential applications in systems biology.

PubMed

Ananiadou, Sophia; Kell, Douglas B; Tsujii, Jun-ichi

2006-12-01

With biomedical literature increasing at a rate of several thousand papers per week, it is impossible to keep abreast of all developments; therefore, automated means to manage the information overload are required. Text mining techniques, which involve the processes of information retrieval, information extraction and data mining, provide a means of solving this. By adding meaning to text, these techniques produce a more structured analysis of textual knowledge than simple word searches, and can provide powerful tools for the production and analysis of systems biology models.

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

Quantum formalism as an optimisation procedure of information flows for physical and biological systems.

PubMed

Baladrón, Carlos; Khrennikov, Andrei

2016-12-01

The similarities between biological and physical systems as respectively defined in quantum information biology (QIB) and in a Darwinian approach to quantum mechanics (DAQM) have been analysed. In both theories the processing of information is a central feature characterising the systems. The analysis highlights a mutual support on the thesis contended by each theory. On the one hand, DAQM provides a physical basis that might explain the key role played by quantum information at the macroscopic level for bio-systems in QIB. On the other hand, QIB offers the possibility, acting as a macroscopic testing ground, to analyse the emergence of quantumness from classicality in the terms held by DAQM. As an added result of the comparison, a tentative definition of quantum information in terms of classical information flows has been proposed. The quantum formalism would appear from this comparative analysis between QIB and DAQM as an optimal information scheme that would maximise the stability of biological and physical systems at any scale. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

[Comparison study between biological vision and computer vision].

PubMed

Liu, W; Yuan, X G; Yang, C X; Liu, Z Q; Wang, R

2001-08-01

The development and bearing of biology vision in structure and mechanism were discussed, especially on the aspects including anatomical structure of biological vision, tentative classification of reception field, parallel processing of visual information, feedback and conformity effect of visual cortical, and so on. The new advance in the field was introduced through the study of the morphology of biological vision. Besides, comparison between biological vision and computer vision was made, and their similarities and differences were pointed out.

The value of mechanistic biophysical information for systems-level understanding of complex biological processes such as cytokinesis.

PubMed

Pollard, Thomas D

2014-12-02

This review illustrates the value of quantitative information including concentrations, kinetic constants and equilibrium constants in modeling and simulating complex biological processes. Although much has been learned about some biological systems without these parameter values, they greatly strengthen mechanistic accounts of dynamical systems. The analysis of muscle contraction is a classic example of the value of combining an inventory of the molecules, atomic structures of the molecules, kinetic constants for the reactions, reconstitutions with purified proteins and theoretical modeling to account for the contraction of whole muscles. A similar strategy is now being used to understand the mechanism of cytokinesis using fission yeast as a favorable model system. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Low Budget Biology 3: A Collection of Low Cost Labs and Activities.

ERIC Educational Resources Information Center

Wartski, Bert; Wartski, Lynn Marie

This document contains biology labs, demonstrations, and activities that use low budget materials. The goal is to get students involved in the learning process by experiencing biology. Each lab has a teacher preparation section which outlines the purpose of the lab, some basic information, a list of materials , and how to prepare the different…

Information services for comparative analysis of biorhythm research

NASA Technical Reports Server (NTRS)

1972-01-01

References and full text documents are presented in support of continuing research and research planning for the NASA behavioral physiology program. Areas covered include: (1) desynchronosis and performance; (2) effects of alcohol, common colds, drugs, and toxic hazards on performance; (3) effects of stress on rhythm of plasma steroids; (4) data processing of biological rhythms; (5) pharmacology and biological rhythms; (6) mechanisms of biological rhythms; and (7) development of biological rhythms.

75 FR 73091 - Medicare Program; Town Hall Meeting on the Fiscal Year 2012 Applications for Add-on Payments for...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-11-29

... application processes for transitional pass-through status of drugs, biologicals, and devices and assignment... transitional pass-through payment for certain new drugs and biologicals. As background information, we have...

Visual Cortex Inspired CNN Model for Feature Construction in Text Analysis

PubMed Central

Fu, Hongping; Niu, Zhendong; Zhang, Chunxia; Ma, Jing; Chen, Jie

2016-01-01

Recently, biologically inspired models are gradually proposed to solve the problem in text analysis. Convolutional neural networks (CNN) are hierarchical artificial neural networks, which include a various of multilayer perceptrons. According to biological research, CNN can be improved by bringing in the attention modulation and memory processing of primate visual cortex. In this paper, we employ the above properties of primate visual cortex to improve CNN and propose a biological-mechanism-driven-feature-construction based answer recommendation method (BMFC-ARM), which is used to recommend the best answer for the corresponding given questions in community question answering. BMFC-ARM is an improved CNN with four channels respectively representing questions, answers, asker information and answerer information, and mainly contains two stages: biological mechanism driven feature construction (BMFC) and answer ranking. BMFC imitates the attention modulation property by introducing the asker information and answerer information of given questions and the similarity between them, and imitates the memory processing property through bringing in the user reputation information for answerers. Then the feature vector for answer ranking is constructed by fusing the asker-answerer similarities, answerer's reputation and the corresponding vectors of question, answer, asker, and answerer. Finally, the Softmax is used at the stage of answer ranking to get best answers by the feature vector. The experimental results of answer recommendation on the Stackexchange dataset show that BMFC-ARM exhibits better performance. PMID:27471460

Visual Cortex Inspired CNN Model for Feature Construction in Text Analysis.

PubMed

Fu, Hongping; Niu, Zhendong; Zhang, Chunxia; Ma, Jing; Chen, Jie

2016-01-01

Recently, biologically inspired models are gradually proposed to solve the problem in text analysis. Convolutional neural networks (CNN) are hierarchical artificial neural networks, which include a various of multilayer perceptrons. According to biological research, CNN can be improved by bringing in the attention modulation and memory processing of primate visual cortex. In this paper, we employ the above properties of primate visual cortex to improve CNN and propose a biological-mechanism-driven-feature-construction based answer recommendation method (BMFC-ARM), which is used to recommend the best answer for the corresponding given questions in community question answering. BMFC-ARM is an improved CNN with four channels respectively representing questions, answers, asker information and answerer information, and mainly contains two stages: biological mechanism driven feature construction (BMFC) and answer ranking. BMFC imitates the attention modulation property by introducing the asker information and answerer information of given questions and the similarity between them, and imitates the memory processing property through bringing in the user reputation information for answerers. Then the feature vector for answer ranking is constructed by fusing the asker-answerer similarities, answerer's reputation and the corresponding vectors of question, answer, asker, and answerer. Finally, the Softmax is used at the stage of answer ranking to get best answers by the feature vector. The experimental results of answer recommendation on the Stackexchange dataset show that BMFC-ARM exhibits better performance.

Inference of Gene Regulatory Networks Using Bayesian Nonparametric Regression and Topology Information.

PubMed

Fan, Yue; Wang, Xiao; Peng, Qinke

2017-01-01

Gene regulatory networks (GRNs) play an important role in cellular systems and are important for understanding biological processes. Many algorithms have been developed to infer the GRNs. However, most algorithms only pay attention to the gene expression data but do not consider the topology information in their inference process, while incorporating this information can partially compensate for the lack of reliable expression data. Here we develop a Bayesian group lasso with spike and slab priors to perform gene selection and estimation for nonparametric models. B-spline basis functions are used to capture the nonlinear relationships flexibly and penalties are used to avoid overfitting. Further, we incorporate the topology information into the Bayesian method as a prior. We present the application of our method on DREAM3 and DREAM4 datasets and two real biological datasets. The results show that our method performs better than existing methods and the topology information prior can improve the result.

Processing Of Visual Information In Primate Brains

NASA Technical Reports Server (NTRS)

Anderson, Charles H.; Van Essen, David C.

1991-01-01

Report reviews and analyzes information-processing strategies and pathways in primate retina and visual cortex. Of interest both in biological fields and in such related computational fields as artificial neural networks. Focuses on data from macaque, which has superb visual system similar to that of humans. Authors stress concept of "good engineering" in understanding visual system.

Pyramidal neurovision architecture for vision machines

NASA Astrophysics Data System (ADS)

Gupta, Madan M.; Knopf, George K.

1993-08-01

The vision system employed by an intelligent robot must be active; active in the sense that it must be capable of selectively acquiring the minimal amount of relevant information for a given task. An efficient active vision system architecture that is based loosely upon the parallel-hierarchical (pyramidal) structure of the biological visual pathway is presented in this paper. Although the computational architecture of the proposed pyramidal neuro-vision system is far less sophisticated than the architecture of the biological visual pathway, it does retain some essential features such as the converging multilayered structure of its biological counterpart. In terms of visual information processing, the neuro-vision system is constructed from a hierarchy of several interactive computational levels, whereupon each level contains one or more nonlinear parallel processors. Computationally efficient vision machines can be developed by utilizing both the parallel and serial information processing techniques within the pyramidal computing architecture. A computer simulation of a pyramidal vision system for active scene surveillance is presented.

Research on moving object detection based on frog's eyes

NASA Astrophysics Data System (ADS)

Fu, Hongwei; Li, Dongguang; Zhang, Xinyuan

2008-12-01

On the basis of object's information processing mechanism with frog's eyes, this paper discussed a bionic detection technology which suitable for object's information processing based on frog's vision. First, the bionics detection theory by imitating frog vision is established, it is an parallel processing mechanism which including pick-up and pretreatment of object's information, parallel separating of digital image, parallel processing, and information synthesis. The computer vision detection system is described to detect moving objects which has special color, special shape, the experiment indicates that it can scheme out the detecting result in the certain interfered background can be detected. A moving objects detection electro-model by imitating biologic vision based on frog's eyes is established, the video simulative signal is digital firstly in this system, then the digital signal is parallel separated by FPGA. IN the parallel processing, the video information can be caught, processed and displayed in the same time, the information fusion is taken by DSP HPI ports, in order to transmit the data which processed by DSP. This system can watch the bigger visual field and get higher image resolution than ordinary monitor systems. In summary, simulative experiments for edge detection of moving object with canny algorithm based on this system indicate that this system can detect the edge of moving objects in real time, the feasibility of bionic model was fully demonstrated in the engineering system, and it laid a solid foundation for the future study of detection technology by imitating biologic vision.

Biological Information Processing in Single Microtubules

DTIC Science & Technology

2014-03-05

single Microtubule Google Mountain view campus, workshop on quantum biology 22 October 2010 3. Paul Davies Beyond Center at Arizona State University...Phoenix) Phoenix, workshop on quantum biology and cancer research, Experimental studies on single microtubule, 25-27 October 2010, Tempe, Arizona...State University, USA 4. Quantum aspects of microtubule: Direct experimental evidence for the existence of quantum states in microtubule, Towards a

Level of Awareness of Biology and Geography Students Related to Recognizing Some Plants

ERIC Educational Resources Information Center

Aladag, Caner; Kaya, Bastürk; Dinç, Muhittin

2017-01-01

The aim of this study is to investigate the awareness of the geography and biology students about recognizing some plants which they see frequently around them in accordance with the information they gained during their education process. The sample of the study consists of 37 biology and 40 geography students studying at the Ahmet Kelesoglu…

“Gestaltomics”: Systems Biology Schemes for the Study of Neuropsychiatric Diseases

PubMed Central

Gutierrez Najera, Nora A.; Resendis-Antonio, Osbaldo; Nicolini, Humberto

2017-01-01

The integration of different sources of biological information about what defines a behavioral phenotype is difficult to unify in an entity that reflects the arithmetic sum of its individual parts. In this sense, the challenge of Systems Biology for understanding the “psychiatric phenotype” is to provide an improved vision of the shape of the phenotype as it is visualized by “Gestalt” psychology, whose fundamental axiom is that the observed phenotype (behavior or mental disorder) will be the result of the integrative composition of every part. Therefore, we propose the term “Gestaltomics” as a term from Systems Biology to integrate data coming from different sources of information (such as the genome, transcriptome, proteome, epigenome, metabolome, phenome, and microbiome). In addition to this biological complexity, the mind is integrated through multiple brain functions that receive and process complex information through channels and perception networks (i.e., sight, ear, smell, memory, and attention) that in turn are programmed by genes and influenced by environmental processes (epigenetic). Today, the approach of medical research in human diseases is to isolate one disease for study; however, the presence of an additional disease (co-morbidity) or more than one disease (multimorbidity) adds complexity to the study of these conditions. This review will present the challenge of integrating psychiatric disorders at different levels of information (Gestaltomics). The implications of increasing the level of complexity, for example, studying the co-morbidity with another disease such as cancer, will also be discussed. PMID:28536537

A Converter from the Systems Biology Markup Language to the Synthetic Biology Open Language.

PubMed

Nguyen, Tramy; Roehner, Nicholas; Zundel, Zach; Myers, Chris J

2016-06-17

Standards are important to synthetic biology because they enable exchange and reproducibility of genetic designs. This paper describes a procedure for converting between two standards: the Systems Biology Markup Language (SBML) and the Synthetic Biology Open Language (SBOL). SBML is a standard for behavioral models of biological systems at the molecular level. SBOL describes structural and basic qualitative behavioral aspects of a biological design. Converting SBML to SBOL enables a consistent connection between behavioral and structural information for a biological design. The conversion process described in this paper leverages Systems Biology Ontology (SBO) annotations to enable inference of a designs qualitative function.

A visual metaphor describing neural dynamics in schizophrenia.

PubMed

van Beveren, Nico J M; de Haan, Lieuwe

2008-07-09

In many scientific disciplines the use of a metaphor as an heuristic aid is not uncommon. A well known example in somatic medicine is the 'defense army metaphor' used to characterize the immune system. In fact, probably a large part of the everyday work of doctors consists of 'translating' scientific and clinical information (i.e. causes of disease, percentage of success versus risk of side-effects) into information tailored to the needs and capacities of the individual patient. The ability to do so in an effective way is at least partly what makes a clinician a good communicator. Schizophrenia is a severe psychiatric disorder which affects approximately 1% of the population. Over the last two decades a large amount of molecular-biological, imaging and genetic data have been accumulated regarding the biological underpinnings of schizophrenia. However, it remains difficult to understand how the characteristic symptoms of schizophrenia such as hallucinations and delusions are related to disturbances on the molecular-biological level. In general, psychiatry seems to lack a conceptual framework with sufficient explanatory power to link the mental- and molecular-biological domains. Here, we present an essay-like study in which we propose to use visualized concepts stemming from the theory on dynamical complex systems as a 'visual metaphor' to bridge the mental- and molecular-biological domains in schizophrenia. We first describe a computer model of neural information processing; we show how the information processing in this model can be visualized, using concepts from the theory on complex systems. We then describe two computer models which have been used to investigate the primary theory on schizophrenia, the neurodevelopmental model, and show how disturbed information processing in these two computer models can be presented in terms of the visual metaphor previously described. Finally, we describe the effects of dopamine neuromodulation, of which disturbances have been frequently described in schizophrenia, in terms of the same visualized metaphor. The conceptual framework and metaphor described offers a heuristic tool to understand the relationship between the mental- and molecular-biological domains in an intuitive way. The concepts we present may serve to facilitate communication between researchers, clinicians and patients.

An overview of surface radiance and biology studies in FIFE

NASA Astrophysics Data System (ADS)

Blad, B. L.; Schimel, D. S.

1992-11-01

The use of satellite data to study and to understand energy and mass exchanges between the land surface and the atmosphere requires information about various biological processes and how various reflected or emitted spectral radiances are influenced by or manifested in these processes. To obtain such information, studies were conducted by the First ISLSCP Field Experiment (FIFE) surface radiances and biology (SRB) group using surface, near-surface, helicopter, and aircraft measurements. The two primary objectives of this group were to relate radiative fluxes to biophysical parameters and physiological processes and to assess how various management treatments affect important biological processes. This overview paper summarizes the results obtained by various SRB teams working in nine different areas: (1) measurement of bidirectional reflectance and estimation of hemispherical albedo; (2) evaluation of spatial and seasonal variability of spectral reflectance and vegetation indices; (3) determination of surface and radiational factors and their effects on vegetation indices and PAR relationships; (4) use of surface temperatures to estimate sensible heat flux; (5) controls over photosynthesis and respiration at small scales; (6) soil surface CO2 fluxes and grassland carbon budget; (7) landscape variations in controls over gas exchange and energy partitioning; (8) radiometric response of prairie to management and topography; and (9) determination of nitrogen gas exchanges in a tallgrass prairie.

50 CFR 665.18 - Framework adjustments to management measures.

Code of Federal Regulations, 2010 CFR

2010-10-01

... rulemaking if new information demonstrates that there are biological, social, or economic concerns in the..., social, or economic concerns in Permit Areas 1, 2, or 3. The following framework process authorizes the... action (including biological, economic, social, enforcement, administrative, and state/Federal needs...

Risk analysis for biological hazards: What we need to know about invasive species

USGS Publications Warehouse

Stohlgren, T.J.; Schnase, J.L.

2006-01-01

Risk analysis for biological invasions is similar to other types of natural and human hazards. For example, risk analysis for chemical spills requires the evaluation of basic information on where a spill occurs; exposure level and toxicity of the chemical agent; knowledge of the physical processes involved in its rate and direction of spread; and potential impacts to the environment, economy, and human health relative to containment costs. Unlike typical chemical spills, biological invasions can have long lag times from introduction and establishment to successful invasion, they reproduce, and they can spread rapidly by physical and biological processes. We use a risk analysis framework to suggest a general strategy for risk analysis for invasive species and invaded habitats. It requires: (1) problem formation (scoping the problem, defining assessment endpoints); (2) analysis (information on species traits, matching species traits to suitable habitats, estimating exposure, surveys of current distribution and abundance); (3) risk characterization (understanding of data completeness, estimates of the “potential” distribution and abundance; estimates of the potential rate of spread; and probable risks, impacts, and costs); and (4) risk management (containment potential, costs, and opportunity costs; legal mandates and social considerations and information science and technology needs).

Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation and Completion of Episodic Information.

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

Aimone, James Bradley; Bernard, Michael Lewis; Vineyard, Craig Michael

2014-10-01

Adult neurogenesis in the hippocampus region of the brain is a neurobiological process that is believed to contribute to the brain's advanced abilities in complex pattern recognition and cognition. Here, we describe how realistic scale simulations of the neurogenesis process can offer both a unique perspective on the biological relevance of this process and confer computational insights that are suggestive of novel machine learning techniques. First, supercomputer based scaling studies of the neurogenesis process demonstrate how a small fraction of adult-born neurons have a uniquely larger impact in biologically realistic scaled networks. Second, we describe a novel technical approach bymore » which the information content of ensembles of neurons can be estimated. Finally, we illustrate several examples of broader algorithmic impact of neurogenesis, including both extending existing machine learning approaches and novel approaches for intelligent sensing.« less

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.

Statistics of natural scenes and cortical color processing.

PubMed

Cecchi, Guillermo A; Rao, A Ravishankar; Xiao, Youping; Kaplan, Ehud

2010-09-01

We investigate the spatial correlations of orientation and color information in natural images. We find that the correlation of orientation information falls off rapidly with increasing distance, while color information is more highly correlated over longer distances. We show that orientation and color information are statistically independent in natural images and that the spatial correlation of jointly encoded orientation and color information decays faster than that of color alone. Our findings suggest that: (a) orientation and color information should be processed in separate channels and (b) the organization of cortical color and orientation selectivity at low spatial frequencies is a reflection of the cortical adaptation to the statistical structure of the visual world. These findings are in agreement with biological observations, as form and color are thought to be represented by different classes of neurons in the primary visual cortex, and the receptive fields of color-selective neurons are larger than those of orientation-selective neurons. The agreement between our findings and biological observations supports the ecological theory of perception.

Computational systems chemical biology.

PubMed

Oprea, Tudor I; May, Elebeoba E; Leitão, Andrei; Tropsha, Alexander

2011-01-01

There is a critical need for improving the level of chemistry awareness in systems biology. The data and information related to modulation of genes and proteins by small molecules continue to accumulate at the same time as simulation tools in systems biology and whole body physiologically based pharmacokinetics (PBPK) continue to evolve. We called this emerging area at the interface between chemical biology and systems biology systems chemical biology (SCB) (Nat Chem Biol 3: 447-450, 2007).The overarching goal of computational SCB is to develop tools for integrated chemical-biological data acquisition, filtering and processing, by taking into account relevant information related to interactions between proteins and small molecules, possible metabolic transformations of small molecules, as well as associated information related to genes, networks, small molecules, and, where applicable, mutants and variants of those proteins. There is yet an unmet need to develop an integrated in silico pharmacology/systems biology continuum that embeds drug-target-clinical outcome (DTCO) triplets, a capability that is vital to the future of chemical biology, pharmacology, and systems biology. Through the development of the SCB approach, scientists will be able to start addressing, in an integrated simulation environment, questions that make the best use of our ever-growing chemical and biological data repositories at the system-wide level. This chapter reviews some of the major research concepts and describes key components that constitute the emerging area of computational systems chemical biology.

Computational Systems Chemical Biology

PubMed Central

Oprea, Tudor I.; May, Elebeoba E.; Leitão, Andrei; Tropsha, Alexander

2013-01-01

There is a critical need for improving the level of chemistry awareness in systems biology. The data and information related to modulation of genes and proteins by small molecules continue to accumulate at the same time as simulation tools in systems biology and whole body physiologically-based pharmacokinetics (PBPK) continue to evolve. We called this emerging area at the interface between chemical biology and systems biology systems chemical biology, SCB (Oprea et al., 2007). The overarching goal of computational SCB is to develop tools for integrated chemical-biological data acquisition, filtering and processing, by taking into account relevant information related to interactions between proteins and small molecules, possible metabolic transformations of small molecules, as well as associated information related to genes, networks, small molecules and, where applicable, mutants and variants of those proteins. There is yet an unmet need to develop an integrated in silico pharmacology / systems biology continuum that embeds drug-target-clinical outcome (DTCO) triplets, a capability that is vital to the future of chemical biology, pharmacology and systems biology. Through the development of the SCB approach, scientists will be able to start addressing, in an integrated simulation environment, questions that make the best use of our ever-growing chemical and biological data repositories at the system-wide level. This chapter reviews some of the major research concepts and describes key components that constitute the emerging area of computational systems chemical biology. PMID:20838980

Towards a Semantic Lexicon for Biological Language Processing

DOE PAGES

Verspoor, Karin

2005-01-01

This paper explores the use of the resources in the National Library of Medicine's Unified Medical Language System (UMLS) for the construction of a lexicon useful for processing texts in the field of molecular biology. A lexicon is constructed from overlapping terms in the UMLS SPECIALIST lexicon and the UMLS Metathesaurus to obtain both morphosyntactic and semantic information for terms, and the coverage of a domain corpus is assessed. Over 77% of tokens in the domain corpus are found in the constructed lexicon, validating the lexicon's coverage of the most frequent terms in the domain and indicating that the constructedmore » lexicon is potentially an important resource for biological text processing.« less

Improving the forecast for biodiversity under climate change.

PubMed

Urban, M C; Bocedi, G; Hendry, A P; Mihoub, J-B; Pe'er, G; Singer, A; Bridle, J R; Crozier, L G; De Meester, L; Godsoe, W; Gonzalez, A; Hellmann, J J; Holt, R D; Huth, A; Johst, K; Krug, C B; Leadley, P W; Palmer, S C F; Pantel, J H; Schmitz, A; Zollner, P A; Travis, J M J

2016-09-09

New biological models are incorporating the realistic processes underlying biological responses to climate change and other human-caused disturbances. However, these more realistic models require detailed information, which is lacking for most species on Earth. Current monitoring efforts mainly document changes in biodiversity, rather than collecting the mechanistic data needed to predict future changes. We describe and prioritize the biological information needed to inform more realistic projections of species' responses to climate change. We also highlight how trait-based approaches and adaptive modeling can leverage sparse data to make broader predictions. We outline a global effort to collect the data necessary to better understand, anticipate, and reduce the damaging effects of climate change on biodiversity. Copyright © 2016, American Association for the Advancement of Science.

Expanding biological data standards development processes for US IOOS: visual line transect observing community for mammal, bird, and turtle data

USGS Publications Warehouse

Fornwall, M.; Gisiner, R.; Simmons, S. E.; Moustahfid, Hassan; Canonico, G.; Halpin, P.; Goldstein, P.; Fitch, R.; Weise, M.; Cyr, N.; Palka, D.; Price, J.; Collins, D.

2012-01-01

The US Integrated Ocean Observing System (IOOS) has recently adopted standards for biological core variables in collaboration with the US Geological Survey/Ocean Biogeographic Information System (USGS/OBIS-USA) and other federal and non-federal partners. In this Community White Paper (CWP) we provide a process to bring into IOOS a rich new source of biological observing data, visual line transect surveys, and to establish quality data standards for visual line transect observations, an important source of at-sea bird, turtle and marine mammal observation data. The processes developed through this exercise will be useful for other similar biogeographic observing efforts, such as passive acoustic point and line transect observations, tagged animal data, and mark-recapture (photo-identification) methods. Furthermore, we suggest that the processes developed through this exercise will serve as a catalyst for broadening involvement by the larger marine biological data community within the goals and processes of IOOS.

DNA as information.

PubMed

Wills, Peter R

2016-03-13

This article reviews contributions to this theme issue covering the topic 'DNA as information' in relation to the structure of DNA, the measure of its information content, the role and meaning of information in biology and the origin of genetic coding as a transition from uninformed to meaningful computational processes in physical systems. © 2016 The Author(s).

Information security management system planning for CBRN facilities

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

Lenaeu, Joseph D.; O'Neil, Lori Ross; Leitch, Rosalyn M.

The focus of this document is to provide guidance for the development of information security management system planning documents at chemical, biological, radiological, or nuclear (CBRN) facilities. It describes a risk-based approach for planning information security programs based on the sensitivity of the data developed, processed, communicated, and stored on facility information systems.

Gravity receptors and responses

NASA Technical Reports Server (NTRS)

Brown, Allan H.

1989-01-01

The overall process of gravity sensing and response processes in plants may be divided conveniently into at least four components or stages: Stimulus susception (a physical event, characteristically the input to the G receptor system of environmental information about the G force magnitude, its vector direction, or both); information perception (an influence of susception on some biological structure or process that can be described as the transformation of environmental information into a biologicallly meaningful change); information transport (the export, if required, of an influence (often chemical) to cells and organs other than those at the sensor location); and biological response (almost always (in plants) a growth change of some kind). Some analysts of the process identify, between information perception and information transport, an additional stage, transduction, which would emphasize the importance of a transformation from one form of information to another, for example from mechanical statolith displacement to an electric, chemical, or other alteration that was its indirect result. These four (or five) stages are temporally sequential. Even if all that occurs at each stage can not be confidently identified, it seems evident that during transduction and transport, matters dealt with are found relatively late in the information flow rather than at the perception stage. As more and more is learned about the roles played by plant hormones which condition the G responses, the mechanism(s) of perception which should be are not necessarily better understood. However, if by asking the right questions and being lucky with experiments perhaps the discovery of how some process (such as sedimentation of protoplasmic organelles) dictates what happens down stream in the information flow sequence may be made.

Change Is Good: Variations in Common Biological Mechanisms in the Epsilonproteobacterial Genera Campylobacter and Helicobacter

PubMed Central

Gilbreath, Jeremy J.; Cody, William L.; Merrell, D. Scott; Hendrixson, David R.

2011-01-01

Summary: Microbial evolution and subsequent species diversification enable bacterial organisms to perform common biological processes by a variety of means. The epsilonproteobacteria are a diverse class of prokaryotes that thrive in diverse habitats. Many of these environmental niches are labeled as extreme, whereas other niches include various sites within human, animal, and insect hosts. Some epsilonproteobacteria, such as Campylobacter jejuni and Helicobacter pylori, are common pathogens of humans that inhabit specific regions of the gastrointestinal tract. As such, the biological processes of pathogenic Campylobacter and Helicobacter spp. are often modeled after those of common enteric pathogens such as Salmonella spp. and Escherichia coli. While many exquisite biological mechanisms involving biochemical processes, genetic regulatory pathways, and pathogenesis of disease have been elucidated from studies of Salmonella spp. and E. coli, these paradigms often do not apply to the same processes in the epsilonproteobacteria. Instead, these bacteria often display extensive variation in common biological mechanisms relative to those of other prototypical bacteria. In this review, five biological processes of commonly studied model bacterial species are compared to those of the epsilonproteobacteria C. jejuni and H. pylori. Distinct differences in the processes of flagellar biosynthesis, DNA uptake and recombination, iron homeostasis, interaction with epithelial cells, and protein glycosylation are highlighted. Collectively, these studies support a broader view of the vast repertoire of biological mechanisms employed by bacteria and suggest that future studies of the epsilonproteobacteria will continue to provide novel and interesting information regarding prokaryotic cellular biology. PMID:21372321

Change is good: variations in common biological mechanisms in the epsilonproteobacterial genera Campylobacter and Helicobacter.

PubMed

Gilbreath, Jeremy J; Cody, William L; Merrell, D Scott; Hendrixson, David R

2011-03-01

Microbial evolution and subsequent species diversification enable bacterial organisms to perform common biological processes by a variety of means. The epsilonproteobacteria are a diverse class of prokaryotes that thrive in diverse habitats. Many of these environmental niches are labeled as extreme, whereas other niches include various sites within human, animal, and insect hosts. Some epsilonproteobacteria, such as Campylobacter jejuni and Helicobacter pylori, are common pathogens of humans that inhabit specific regions of the gastrointestinal tract. As such, the biological processes of pathogenic Campylobacter and Helicobacter spp. are often modeled after those of common enteric pathogens such as Salmonella spp. and Escherichia coli. While many exquisite biological mechanisms involving biochemical processes, genetic regulatory pathways, and pathogenesis of disease have been elucidated from studies of Salmonella spp. and E. coli, these paradigms often do not apply to the same processes in the epsilonproteobacteria. Instead, these bacteria often display extensive variation in common biological mechanisms relative to those of other prototypical bacteria. In this review, five biological processes of commonly studied model bacterial species are compared to those of the epsilonproteobacteria C. jejuni and H. pylori. Distinct differences in the processes of flagellar biosynthesis, DNA uptake and recombination, iron homeostasis, interaction with epithelial cells, and protein glycosylation are highlighted. Collectively, these studies support a broader view of the vast repertoire of biological mechanisms employed by bacteria and suggest that future studies of the epsilonproteobacteria will continue to provide novel and interesting information regarding prokaryotic cellular biology.

Thermodynamic Costs of Information Processing in Sensory Adaptation

PubMed Central

Sartori, Pablo; Granger, Léo; Lee, Chiu Fan; Horowitz, Jordan M.

2014-01-01

Biological sensory systems react to changes in their surroundings. They are characterized by fast response and slow adaptation to varying environmental cues. Insofar as sensory adaptive systems map environmental changes to changes of their internal degrees of freedom, they can be regarded as computational devices manipulating information. Landauer established that information is ultimately physical, and its manipulation subject to the entropic and energetic bounds of thermodynamics. Thus the fundamental costs of biological sensory adaptation can be elucidated by tracking how the information the system has about its environment is altered. These bounds are particularly relevant for small organisms, which unlike everyday computers, operate at very low energies. In this paper, we establish a general framework for the thermodynamics of information processing in sensing. With it, we quantify how during sensory adaptation information about the past is erased, while information about the present is gathered. This process produces entropy larger than the amount of old information erased and has an energetic cost bounded by the amount of new information written to memory. We apply these principles to the E. coli's chemotaxis pathway during binary ligand concentration changes. In this regime, we quantify the amount of information stored by each methyl group and show that receptors consume energy in the range of the information-theoretic minimum. Our work provides a basis for further inquiries into more complex phenomena, such as gradient sensing and frequency response. PMID:25503948

Advanced biologically plausible algorithms for low-level image processing

NASA Astrophysics Data System (ADS)

Gusakova, Valentina I.; Podladchikova, Lubov N.; Shaposhnikov, Dmitry G.; Markin, Sergey N.; Golovan, Alexander V.; Lee, Seong-Whan

1999-08-01

At present, in computer vision, the approach based on modeling the biological vision mechanisms is extensively developed. However, up to now, real world image processing has no effective solution in frameworks of both biologically inspired and conventional approaches. Evidently, new algorithms and system architectures based on advanced biological motivation should be developed for solution of computational problems related to this visual task. Basic problems that should be solved for creation of effective artificial visual system to process real world imags are a search for new algorithms of low-level image processing that, in a great extent, determine system performance. In the present paper, the result of psychophysical experiments and several advanced biologically motivated algorithms for low-level processing are presented. These algorithms are based on local space-variant filter, context encoding visual information presented in the center of input window, and automatic detection of perceptually important image fragments. The core of latter algorithm are using local feature conjunctions such as noncolinear oriented segment and composite feature map formation. Developed algorithms were integrated into foveal active vision model, the MARR. It is supposed that proposed algorithms may significantly improve model performance while real world image processing during memorizing, search, and recognition.

Towards a semantic lexicon for biological language processing

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

Verspoor, K.

It is well understood that natural language processing (NLP) applications require sophisticated lexical resources to support their processing goals. In the biomedical domain, we are privileged to have access to extensive terminological resources in the form of controlled vocabularies and ontologies, which have been integrated into the framework of the National Library of Medicine's Unified Medical Language System's (UMLS) Metathesaurus. However, the existence of such terminological resources does not guarantee their utility for NLP. In particular, we have two core requirements for lexical resources for NLP in addition to the basic enumeration of important domain terms: representation of morphosyntactic informationmore » about those terms, specifically part of speech information and inflectional patterns to support parsing and lemma assignment, and representation of semantic information indicating general categorical information about terms, and significant relations between terms to support text understanding and inference (Hahn et at, 1999). Biomedical vocabularies by and large commonly leave out morphosyntactic information, and where they address semantic considerations, they often do so in an unprincipled manner, for instance by indicating a relation between two concepts without indicating the type of that relation. But all is not lost. The UMLS knowledge sources include two additional resources which are relevant - the SPECIALIST lexicon, a lexicon addressing our morphosyntactic requirements, and the Semantic Network, a representation of core conceptual categories in the biomedical domain. The coverage of these two knowledge sources with respect to the full coverage of the Metathesaurus is, however, not entirely clear. Furthermore, when our goals are specifically to process biological text - and often more specifically, text in the molecular biology domain - it is difficult to say whether the coverage of these resources is meaningful. The utility of the UMLS knowledge sources for medical language processing (MLP) has been explored (Johnson, 1999; Friedman et al 2001); the time has now come to repeat these experiments with respect to biological language processing (BLP). To that end, this paper presents an analysis of ihe UMLS resources, specifically with an eye towards constructing lexical resources suitable for BLP. We follow the paradigm presented in Johnson (1999) for medical language, exploring overlap between the UMLS Metathesaurus and SPECIALIST lexicon to construct a morphosyntactic and semantically-specified lexicon, and then further explore the overlap with a relevant domain corpus for molecular biology.« less

Biomedical implications of information processing in chemical systems: non-classical approach to photochemistry of coordination compounds.

PubMed

Szaciłowski, Konrad

2007-01-01

Analogies between photoactive nitric oxide generators and various electronic devices: logic gates and operational amplifiers are presented. These analogies have important biological consequences: application of control parameters allows for better targeting and control of nitric oxide drugs. The same methodology may be applied in the future for other therapeutic strategies and at the same time helps to understand natural regulatory and signaling processes in biological systems.

The IND application.

PubMed

Ferkany, John W; Williams, Michael

2008-09-01

Translational biomedical research is often directed to the introduction of a new drug or biologic intended to treat unmet medical need in humans. This unit describes the timing and content of the investigational new drug (IND) application, the primary document required by the U.S. FDA for the initiation of clinical trials in humans with any new chemical entity (NCE) or biologic. The IND application contains all the information necessary for the FDA to make an assessment of the risks and benefits of the proposed clinical trials for the NCE/biologic, containing a detailed but succinct description of the biology, safety, toxicology, chemistry and manufacturing process, and the proposed clinical plan. This unit is geared for those with little or no experience with the IND process and is intended as a global introduction to this, the initial stage of the drug development process for drugs used in humans.

Ultimate computing. Biomolecular consciousness and nano Technology

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

Hameroff, S.R.

1987-01-01

The book advances the premise that the cytoskeleton is the cell's nervous system, the biological controller/computer. If indeed cytoskeletal dynamics in the nanoscale (billionth meter, billionth second) are the texture of intracellular information processing, emerging ''NanoTechnologies'' (scanning tunneling microscopy, Feynman machines, von Neumann replicators, etc.) should enable direct monitoring, decoding and interfacing between biological and technological information devices. This in turn could result in important biomedical applications and perhaps a merger of mind and machine: Ultimate Computing.

Integration of element specific persistent homology and machine learning for protein-ligand binding affinity prediction.

PubMed

Cang, Zixuan; Wei, Guo-Wei

2018-02-01

Protein-ligand binding is a fundamental biological process that is paramount to many other biological processes, such as signal transduction, metabolic pathways, enzyme construction, cell secretion, and gene expression. Accurate prediction of protein-ligand binding affinities is vital to rational drug design and the understanding of protein-ligand binding and binding induced function. Existing binding affinity prediction methods are inundated with geometric detail and involve excessively high dimensions, which undermines their predictive power for massive binding data. Topology provides the ultimate level of abstraction and thus incurs too much reduction in geometric information. Persistent homology embeds geometric information into topological invariants and bridges the gap between complex geometry and abstract topology. However, it oversimplifies biological information. This work introduces element specific persistent homology (ESPH) or multicomponent persistent homology to retain crucial biological information during topological simplification. The combination of ESPH and machine learning gives rise to a powerful paradigm for macromolecular analysis. Tests on 2 large data sets indicate that the proposed topology-based machine-learning paradigm outperforms other existing methods in protein-ligand binding affinity predictions. ESPH reveals protein-ligand binding mechanism that can not be attained from other conventional techniques. The present approach reveals that protein-ligand hydrophobic interactions are extended to 40Å  away from the binding site, which has a significant ramification to drug and protein design. Copyright © 2017 John Wiley & Sons, Ltd.

Bioavailability of antioxidants in extruded products prepared from purple potato and dry pea flours

USDA-ARS?s Scientific Manuscript database

Measuring antioxidant activity using biological relevant assay is unique to understand the role of phytochemicals in vivo than common chemical assays. Cellular antioxidant activity assay could provide more biological relevant information on bioactive compounds in the raw as well as processed food pr...

Economic Analysis of Biological Invasions in Forests

Treesearch

Tomas P. Holmes; Julian Aukema; Jeffrey Englin; Robert G. Haight; Kent Kovacs; Brian Leung

2014-01-01

Biological invasions of native forests by nonnative pests result from complex stochastic processes that are difficult to predict. Although economic optimization models describe efficient controls across the stages of an invasion, the ability to calibrate such models is constrained by lack of information on pest population dynamics and consequent economic damages. Here...

78 FR 18814 - Amendment to the Export Administration Regulations: List of Items Classified Under Export Control...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-28

... RIN 0694-AF73. FOR FURTHER INFORMATION CONTACT: Elizabeth Sangine, Director, Chemical and Biological... detection, identification, warning or monitoring of biological agents that is subject to the licensing... approved collections: (1) The Simplified Network Application Processing + System (control number 0694-0088...

The Graduate Training Program in Pharmacology at the University of Kansas School of Pharmacy

ERIC Educational Resources Information Center

Rutledge, Charles O.

1976-01-01

A multidisciplinary approach is used to teach the chemical mechanisms of biological processes and of drug action. Program prerequisites and objectives emphasize the training of creative scientists who are qualified to perform interesting and informative research on the interaction of drugs with biological systems. (LBH)

Residual perception of biological motion in cortical blindness.

PubMed

Ruffieux, Nicolas; Ramon, Meike; Lao, Junpeng; Colombo, Françoise; Stacchi, Lisa; Borruat, François-Xavier; Accolla, Ettore; Annoni, Jean-Marie; Caldara, Roberto

2016-12-01

From birth, the human visual system shows a remarkable sensitivity for perceiving biological motion. This visual ability relies on a distributed network of brain regions and can be preserved even after damage of high-level ventral visual areas. However, it remains unknown whether this critical biological skill can withstand the loss of vision following bilateral striate damage. To address this question, we tested the categorization of human and animal biological motion in BC, a rare case of cortical blindness after anoxia-induced bilateral striate damage. The severity of his impairment, encompassing various aspects of vision (i.e., color, shape, face, and object recognition) and causing blind-like behavior, contrasts with a residual ability to process motion. We presented BC with static or dynamic point-light displays (PLDs) of human or animal walkers. These stimuli were presented either individually, or in pairs in two alternative forced choice (2AFC) tasks. When confronted with individual PLDs, the patient was unable to categorize the stimuli, irrespective of whether they were static or dynamic. In the 2AFC task, BC exhibited appropriate eye movements towards diagnostic information, but performed at chance level with static PLDs, in stark contrast to his ability to efficiently categorize dynamic biological agents. This striking ability to categorize biological motion provided top-down information is important for at least two reasons. Firstly, it emphasizes the importance of assessing patients' (visual) abilities across a range of task constraints, which can reveal potential residual abilities that may in turn represent a key feature for patient rehabilitation. Finally, our findings reinforce the view that the neural network processing biological motion can efficiently operate despite severely impaired low-level vision, positing our natural predisposition for processing dynamicity in biological agents as a robust feature of human vision. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Kyle, Jennifer E.; Zhang, Xing; Weitz, Karl K.

Understanding how biological molecules are generated, metabolized and eliminated in living systems is important for interpreting processes such as immune response and disease pathology. While genomic and proteomic studies have provided vast amounts of information over the last several decades, interest in lipidomics has also grown due to improved analytical technologies revealing altered lipid metabolism in type 2 diabetes, cancer, and lipid storage disease. Liquid chromatography and mass spectrometry (LC-MS) measurements are currently the dominant approach for characterizing the lipidome by providing detailed information on the spatial and temporal composition of lipids. However, interpreting lipids’ biological roles is challenging duemore » to the existence of numerous structural and stereoisomers (i.e. distinct acyl chain and double-bond positions), which are unresolvable using present LC-MS approaches. Here we show that combining structurally-based ion mobility spectrometry (IMS) with LC-MS measurements distinguishes lipid isomers and allows insight into biological and disease processes.« less

Harnessing glycomics technologies: integrating structure with function for glycan characterization

PubMed Central

Robinson, Luke N.; Artpradit, Charlermchai; Raman, Rahul; Shriver, Zachary H.; Ruchirawat, Mathuros; Sasisekharan, Ram

2013-01-01

Glycans, or complex carbohydrates, are a ubiquitous class of biological molecules which impinge on a variety of physiological processes ranging from signal transduction to tissue development and microbial pathogenesis. In comparison to DNA and proteins, glycans present unique challenges to the study of their structure and function owing to their complex and heterogeneous structures and the dominant role played by multivalency in their sequence-specific biological interactions. Arising from these challenges, there is a need to integrate information from multiple complementary methods to decode structure-function relationships. Focusing on acidic glycans, we describe here key glycomics technologies for characterizing their structural attributes, including linkage, modifications, and topology, as well as for elucidating their role in biological processes. Two cases studies, one involving sialylated branched glycans and the other sulfated glycosaminoglycans, are used to highlight how integration of orthogonal information from diverse datasets enables rapid convergence of glycan characterization for development of robust structure-function relationships. PMID:22522536

Stable Isotope Tracers of Process in Great Lakes Food Webs

EPA Science Inventory

Stable isotope analyses of biota are now commonly used to discern trophic pathways between consumers and their foods. However, those same isotope data also hold information about processes that influence the physicochemical setting of food webs as well as biological processes ope...

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.

Impaired global, and compensatory local, biological motion processing in people with high levels of autistic traits.

PubMed

van Boxtel, Jeroen J A; Lu, Hongjing

2013-01-01

People with Autism Spectrum Disorder (ASD) are hypothesized to have poor high-level processing but superior low-level processing, causing impaired social recognition, and a focus on non-social stimulus contingencies. Biological motion perception provides an ideal domain to investigate exactly how ASD modulates the interaction between low and high-level processing, because it involves multiple processing stages, and carries many important social cues. We investigated individual differences among typically developing observers in biological motion processing, and whether such individual differences associate with the number of autistic traits. In Experiment 1, we found that individuals with fewer autistic traits were automatically and involuntarily attracted to global biological motion information, whereas individuals with more autistic traits did not show this pre-attentional distraction. We employed an action adaptation paradigm in the second study to show that individuals with more autistic traits were able to compensate for deficits in global processing with an increased involvement in local processing. Our findings can be interpreted within a predictive coding framework, which characterizes the functional relationship between local and global processing stages, and explains how these stages contribute to the perceptual difficulties associated with ASD.

Impaired Global, and Compensatory Local, Biological Motion Processing in People with High Levels of Autistic Traits

PubMed Central

van Boxtel, Jeroen J. A.; Lu, Hongjing

2013-01-01

People with Autism Spectrum Disorder (ASD) are hypothesized to have poor high-level processing but superior low-level processing, causing impaired social recognition, and a focus on non-social stimulus contingencies. Biological motion perception provides an ideal domain to investigate exactly how ASD modulates the interaction between low and high-level processing, because it involves multiple processing stages, and carries many important social cues. We investigated individual differences among typically developing observers in biological motion processing, and whether such individual differences associate with the number of autistic traits. In Experiment 1, we found that individuals with fewer autistic traits were automatically and involuntarily attracted to global biological motion information, whereas individuals with more autistic traits did not show this pre-attentional distraction. We employed an action adaptation paradigm in the second study to show that individuals with more autistic traits were able to compensate for deficits in global processing with an increased involvement in local processing. Our findings can be interpreted within a predictive coding framework, which characterizes the functional relationship between local and global processing stages, and explains how these stages contribute to the perceptual difficulties associated with ASD. PMID:23630514

Developing Rational-Empirical Views of Intelligent Adaptive Behavior

DTIC Science & Technology

2004-08-01

biological frame to the information processing model and outline our understanding of intentions and beliefs that co-exist with rational and...notion that the evolution of cognition has produced memory/ knowledge systems that specialize in the processing of particular types of information ...1 PERMIS 2004 Developing Rational-Empirical Views of Intelligent Adaptive Behavior Gary Berg-Cross, Knowledge Strategies Potomac, Maryland

An information-based approach to change-point analysis with applications to biophysics and cell biology.

PubMed

Wiggins, Paul A

2015-07-21

This article describes the application of a change-point algorithm to the analysis of stochastic signals in biological systems whose underlying state dynamics consist of transitions between discrete states. Applications of this analysis include molecular-motor stepping, fluorophore bleaching, electrophysiology, particle and cell tracking, detection of copy number variation by sequencing, tethered-particle motion, etc. We present a unified approach to the analysis of processes whose noise can be modeled by Gaussian, Wiener, or Ornstein-Uhlenbeck processes. To fit the model, we exploit explicit, closed-form algebraic expressions for maximum-likelihood estimators of model parameters and estimated information loss of the generalized noise model, which can be computed extremely efficiently. We implement change-point detection using the frequentist information criterion (which, to our knowledge, is a new information criterion). The frequentist information criterion specifies a single, information-based statistical test that is free from ad hoc parameters and requires no prior probability distribution. We demonstrate this information-based approach in the analysis of simulated and experimental tethered-particle-motion data. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Corrections to chance fluctuations: quantum mind in biological evolution?

PubMed

Damiani, Giuseppe

2009-01-01

According to neo-Darwinian theory, biological evolution is produced by natural selection of random hereditary variations. This assumption stems from the idea of a mechanical and deterministic world based on the laws of classic physics. However, the increased knowledge of relationships between metabolism, epigenetic systems, and editing of nucleic acids suggests the existence of self-organized processes of adaptive evolution in response to environmental stresses. Living organisms are open thermodynamic systems which use entropic decay of external source of electromagnetic energy to increase their internal dynamic order and to generate new genetic and epigenetic information with a high degree of coherency and teleonomic creativity. Sensing, information processing, and decision making of biological systems might be mainly quantum phenomena. Amplification of microscopic quantum events using the long-range correlation of fractal structures, at the borderline between deterministic order and unpredictable chaos, may be used to direct a reproducible transition of the biological systems towards a defined macroscopic state. The discoveries of many natural genetic engineering systems, the ability to choose the most effective solutions, and the emergence of complex forms of consciousness at different levels confirm the importance of mind-action directed processes in biological evolution, as suggested by Alfred Russel Wallace. Although the main Darwinian principles will remain a crucial component of our understanding of evolution, a radical rethinking of the conceptual structure of the neo-Darwinian theory is needed.

A simplified computational memory model from information processing.

PubMed

Zhang, Lanhua; Zhang, Dongsheng; Deng, Yuqin; Ding, Xiaoqian; Wang, Yan; Tang, Yiyuan; Sun, Baoliang

2016-11-23

This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracting memory function and simulating memory information processing. At first meta-memory is defined to express the neuron or brain cortices based on the biology and graph theories, and we develop an intra-modular network with the modeling algorithm by mapping the node and edge, and then the bi-modular network is delineated with intra-modular and inter-modular. At last a polynomial retrieval algorithm is introduced. In this paper we simulate the memory phenomena and functions of memorization and strengthening by information processing algorithms. The theoretical analysis and the simulation results show that the model is in accordance with the memory phenomena from information processing view.

People and Decisions: Meeting the Information Needs of Managers

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

Blake, J.I.; LeMaster, E.

2000-10-01

The information needs of managers with respect to avian species at the SRS are identified. The process by which information is integrated into decision making are discussed. Numerous studies of upland bird species at SRS were conducted as part of the DOE Biodiversity Program. This information is being incorporated into biological assessments and plan through modeling and geographic information systems.

Disappearance of the inversion effect during memory-guided tracking of scrambled biological motion.

PubMed

Jiang, Changhao; Yue, Guang H; Chen, Tingting; Ding, Jinhong

2016-08-01

The human visual system is highly sensitive to biological motion. Even when a point-light walker is temporarily occluded from view by other objects, our eyes are still able to maintain tracking continuity. To investigate how the visual system establishes a correspondence between the biological-motion stimuli visible before and after the disruption, we used the occlusion paradigm with biological-motion stimuli that were intact or scrambled. The results showed that during visually guided tracking, both the observers' predicted times and predictive smooth pursuit were more accurate for upright biological motion (intact and scrambled) than for inverted biological motion. During memory-guided tracking, however, the processing advantage for upright as compared with inverted biological motion was not found in the scrambled condition, but in the intact condition only. This suggests that spatial location information alone is not sufficient to build and maintain the representational continuity of the biological motion across the occlusion, and that the object identity may act as an important information source in visual tracking. The inversion effect disappeared when the scrambled biological motion was occluded, which indicates that when biological motion is temporarily occluded and there is a complete absence of visual feedback signals, an oculomotor prediction is executed to maintain the tracking continuity, which is established not only by updating the target's spatial location, but also by the retrieval of identity information stored in long-term memory.

Antibodies and antimatter: the resurgence of immuno-PET.

PubMed

Wu, Anna M

2009-01-01

The completion of the human genome, coupled with parallel major research efforts in proteomics and systems biology, has led to a flood of information on the roles of individual genes and proteins in normal physiologic processes and their disruptions in disease. In practical terms, this information has opened the door to increasingly targeted therapies as specific molecular markers are identified and validated. The ongoing transition from empiric to molecular medicine has engendered a need for corresponding molecular diagnostics, including noninvasive molecular imaging. Convergence of knowledge regarding key biomarkers that define normal biologic processes and disease with protein and imaging technology makes this an opportune time to revisit the combination of antibodies and PET, or immuno-PET.

The spatial and temporal organization of ubiquitin networks

PubMed Central

Grabbe, Caroline; Husnjak, Koraljka; Dikic, Ivan

2013-01-01

In the past decade, the diversity of signals generated by the ubiquitin system has emerged as a dominant regulator of biological processes and propagation of information in the eukaryotic cell. A wealth of information has been gained about the crucial role of spatial and temporal regulation of ubiquitin species of different lengths and linkages in the nuclear factor-κB (NF-κB) pathway, endocytic trafficking, protein degradation and DNA repair. This spatiotemporal regulation is achieved through sophisticated mechanisms of compartmentalization and sequential series of ubiquitylation events and signal decoding, which control diverse biological processes not only in the cell but also during the development of tissues and entire organisms. PMID:21448225

Design and analysis of large-scale biological rhythm studies: a comparison of algorithms for detecting periodic signals in biological data

PubMed Central

Deckard, Anastasia; Anafi, Ron C.; Hogenesch, John B.; Haase, Steven B.; Harer, John

2013-01-01

Motivation: To discover and study periodic processes in biological systems, we sought to identify periodic patterns in their gene expression data. We surveyed a large number of available methods for identifying periodicity in time series data and chose representatives of different mathematical perspectives that performed well on both synthetic data and biological data. Synthetic data were used to evaluate how each algorithm responds to different curve shapes, periods, phase shifts, noise levels and sampling rates. The biological datasets we tested represent a variety of periodic processes from different organisms, including the cell cycle and metabolic cycle in Saccharomyces cerevisiae, circadian rhythms in Mus musculus and the root clock in Arabidopsis thaliana. Results: From these results, we discovered that each algorithm had different strengths. Based on our findings, we make recommendations for selecting and applying these methods depending on the nature of the data and the periodic patterns of interest. Additionally, these results can also be used to inform the design of large-scale biological rhythm experiments so that the resulting data can be used with these algorithms to detect periodic signals more effectively. Contact: anastasia.deckard@duke.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24058056

Quantitative proteomics in biological research.

PubMed

Wilm, Matthias

2009-10-01

Proteomics has enabled the direct investigation of biological material, at first through the analysis of individual proteins, then of lysates from cell cultures, and finally of extracts from tissues and biopsies from entire organisms. Its latest manifestation - quantitative proteomics - allows deeper insight into biological systems. This article reviews the different methods used to extract quantitative information from mass spectra. It follows the technical developments aimed toward global proteomics, the attempt to characterize every expressed protein in a cell by at least one peptide. When applications of the technology are discussed, the focus is placed on yeast biology. In particular, differential quantitative proteomics, the comparison between an experiment and its control, is very discriminating for proteins involved in the process being studied. When trying to understand biological processes on a molecular level, differential quantitative proteomics tends to give a clearer picture than global transcription analyses. As a result, MS has become an even more indispensable tool for biochemically motivated biological research.

More than who eats who: Discerning ecological processes from stable isotopes data

EPA Science Inventory

Stable isotope analyses of biota are now commonly used to discern trophic pathways between consumers and their foods. However, those same isotope data also hold information about processes that influence the physicochemical setting of food webs as well as biological processes ope...

Systems Biology and Biomarkers of Early Effects for Occupational Exposure Limit Setting

PubMed Central

DeBord, D. Gayle; Burgoon, Lyle; Edwards, Stephen W.; Haber, Lynne T.; Kanitz, M. Helen; Kuempel, Eileen; Thomas, Russell S.; Yucesoy, Berran

2015-01-01

In a recent National Research Council document, new strategies for risk assessment were described to enable more accurate and quicker assessments.( 1 ) This report suggested that evaluating individual responses through increased use of bio-monitoring could improve dose-response estimations. Identi-fication of specific biomarkers may be useful for diagnostics or risk prediction as they have the potential to improve exposure assessments. This paper discusses systems biology, biomarkers of effect, and computational toxicology approaches and their relevance to the occupational exposure limit setting process. The systems biology approach evaluates the integration of biological processes and how disruption of these processes by chemicals or other hazards affects disease outcomes. This type of approach could provide information used in delineating the mode of action of the response or toxicity, and may be useful to define the low adverse and no adverse effect levels. Biomarkers of effect are changes measured in biological systems and are considered to be preclinical in nature. Advances in computational methods and experimental -omics methods that allow the simultaneous measurement of families of macromolecules such as DNA, RNA, and proteins in a single analysis have made these systems approaches feasible for broad application. The utility of the information for risk assessments from -omics approaches has shown promise and can provide information on mode of action and dose-response relationships. As these techniques evolve, estimation of internal dose and response biomarkers will be a critical test of these new technologies for application in risk assessment strategies. While proof of concept studies have been conducted that provide evidence of their value, challenges with standardization and harmonization still need to be overcome before these methods are used routinely. PMID:26132979

Systems Biology and Biomarkers of Early Effects for Occupational Exposure Limit Setting.

PubMed

DeBord, D Gayle; Burgoon, Lyle; Edwards, Stephen W; Haber, Lynne T; Kanitz, M Helen; Kuempel, Eileen; Thomas, Russell S; Yucesoy, Berran

2015-01-01

In a recent National Research Council document, new strategies for risk assessment were described to enable more accurate and quicker assessments. This report suggested that evaluating individual responses through increased use of bio-monitoring could improve dose-response estimations. Identification of specific biomarkers may be useful for diagnostics or risk prediction as they have the potential to improve exposure assessments. This paper discusses systems biology, biomarkers of effect, and computational toxicology approaches and their relevance to the occupational exposure limit setting process. The systems biology approach evaluates the integration of biological processes and how disruption of these processes by chemicals or other hazards affects disease outcomes. This type of approach could provide information used in delineating the mode of action of the response or toxicity, and may be useful to define the low adverse and no adverse effect levels. Biomarkers of effect are changes measured in biological systems and are considered to be preclinical in nature. Advances in computational methods and experimental -omics methods that allow the simultaneous measurement of families of macromolecules such as DNA, RNA, and proteins in a single analysis have made these systems approaches feasible for broad application. The utility of the information for risk assessments from -omics approaches has shown promise and can provide information on mode of action and dose-response relationships. As these techniques evolve, estimation of internal dose and response biomarkers will be a critical test of these new technologies for application in risk assessment strategies. While proof of concept studies have been conducted that provide evidence of their value, challenges with standardization and harmonization still need to be overcome before these methods are used routinely.

The potential of text mining in data integration and network biology for plant research: a case study on Arabidopsis.

PubMed

Van Landeghem, Sofie; De Bodt, Stefanie; Drebert, Zuzanna J; Inzé, Dirk; Van de Peer, Yves

2013-03-01

Despite the availability of various data repositories for plant research, a wealth of information currently remains hidden within the biomolecular literature. Text mining provides the necessary means to retrieve these data through automated processing of texts. However, only recently has advanced text mining methodology been implemented with sufficient computational power to process texts at a large scale. In this study, we assess the potential of large-scale text mining for plant biology research in general and for network biology in particular using a state-of-the-art text mining system applied to all PubMed abstracts and PubMed Central full texts. We present extensive evaluation of the textual data for Arabidopsis thaliana, assessing the overall accuracy of this new resource for usage in plant network analyses. Furthermore, we combine text mining information with both protein-protein and regulatory interactions from experimental databases. Clusters of tightly connected genes are delineated from the resulting network, illustrating how such an integrative approach is essential to grasp the current knowledge available for Arabidopsis and to uncover gene information through guilt by association. All large-scale data sets, as well as the manually curated textual data, are made publicly available, hereby stimulating the application of text mining data in future plant biology studies.

Specifications of Standards in Systems and Synthetic Biology.

PubMed

Schreiber, Falk; Bader, Gary D; Golebiewski, Martin; Hucka, Michael; Kormeier, Benjamin; Le Novère, Nicolas; Myers, Chris; Nickerson, David; Sommer, Björn; Waltemath, Dagmar; Weise, Stephan

2015-09-04

Standards shape our everyday life. From nuts and bolts to electronic devices and technological processes, standardised products and processes are all around us. Standards have technological and economic benefits, such as making information exchange, production, and services more efficient. However, novel, innovative areas often either lack proper standards, or documents about standards in these areas are not available from a centralised platform or formal body (such as the International Standardisation Organisation). Systems and synthetic biology is a relatively novel area, and it is only in the last decade that the standardisation of data, information, and models related to systems and synthetic biology has become a community-wide effort. Several open standards have been established and are under continuous development as a community initiative. COMBINE, the ‘COmputational Modeling in BIology’ NEtwork has been established as an umbrella initiative to coordinate and promote the development of the various community standards and formats for computational models. There are yearly two meeting, HARMONY (Hackathons on Resources for Modeling in Biology), Hackathon-type meetings with a focus on development of the support for standards, and COMBINE forums, workshop-style events with oral presentations, discussion, poster, and breakout sessions for further developing the standards. For more information see http://co.mbine.org/. So far the different standards were published and made accessible through the standards’ web- pages or preprint services. The aim of this special issue is to provide a single, easily accessible and citable platform for the publication of standards in systems and synthetic biology. This special issue is intended to serve as a central access point to standards and related initiatives in systems and synthetic biology, it will be published annually to provide an opportunity for standard development groups to communicate updated specifications.

Dynamics of intracellular processes in live-cell systems unveiled by fluorescence correlation microscopy.

PubMed

González Bardeci, Nicolás; Angiolini, Juan Francisco; De Rossi, María Cecilia; Bruno, Luciana; Levi, Valeria

2017-01-01

Fluorescence fluctuation-based methods are non-invasive microscopy tools especially suited for the study of dynamical aspects of biological processes. These methods examine spontaneous intensity fluctuations produced by fluorescent molecules moving through the small, femtoliter-sized observation volume defined in confocal and multiphoton microscopes. The quantitative analysis of the intensity trace provides information on the processes producing the fluctuations that include diffusion, binding interactions, chemical reactions and photophysical phenomena. In this review, we present the basic principles of the most widespread fluctuation-based methods, discuss their implementation in standard confocal microscopes and briefly revise some examples of their applications to address relevant questions in living cells. The ultimate goal of these methods in the Cell Biology field is to observe biomolecules as they move, interact with targets and perform their biological action in the natural context. © 2016 IUBMB Life, 69(1):8-15, 2017. © 2016 International Union of Biochemistry and Molecular Biology.

Invited review liquid crystal models of biological materials and silk spinning.

PubMed

Rey, Alejandro D; Herrera-Valencia, Edtson E

2012-06-01

A review of thermodynamic, materials science, and rheological liquid crystal models is presented and applied to a wide range of biological liquid crystals, including helicoidal plywoods, biopolymer solutions, and in vivo liquid crystals. The distinguishing characteristics of liquid crystals (self-assembly, packing, defects, functionalities, processability) are discussed in relation to biological materials and the strong correspondence between different synthetic and biological materials is established. Biological polymer processing based on liquid crystalline precursors includes viscoelastic flow to form and shape fibers. Viscoelastic models for nematic and chiral nematics are reviewed and discussed in terms of key parameters that facilitate understanding and quantitative information from optical textures and rheometers. It is shown that viscoelastic modeling the silk spinning process using liquid crystal theories sheds light on textural transitions in the duct of spiders and silk worms as well as on tactoidal drops and interfacial structures. The range and consistency of the predictions demonstrates that the use of mesoscopic liquid crystal models is another tool to develop the science and biomimetic applications of mesogenic biological soft matter. Copyright © 2011 Wiley Periodicals, Inc.

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.

Soft x rays as a tool to investigate radiation-sensitive sites in mammalian cells

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

Brenner, D.J.; Zaider, M.

1983-01-01

It is now clear that the initial geometrical distribution of primary radiation products in irradiated biological matter is fundamental to the observed end point (cell killing, mutation induction, chromosome aberrations, etc.). In recent years much evidence has accumulated indicating that for all radiations, physical quantities averaged over cellular dimensions (micrometers) are not good predictors of biological effect, and that energy-deposition processes at the nanometer level are critical. Thus irradiation of cells with soft x rays whose secondary electrons have ranges of the order of nanometers is a unique tool for investigating different models for predicting the biological effects of radiation.more » We demonstrate techniques whereby the biological response of the cell and the physical details of the energy deposition processes may be separated or factorized, so that given the response of a cellular system to, say, soft x rays, the response of the cell to any other radiation may be predicted. The special advantages of soft x rays for eliciting this information and also information concerning the geometry of the radiation sensitive structures within the cell are discussed.« less

Inherit the policy: A sociocultural approach to understanding evolutionary biology policy in South Carolina

NASA Astrophysics Data System (ADS)

Moore, Gregory D.

South Carolina biology Indicator 5.6 calls for students to "Summarize ways that scientists use data from a variety of sources to investigate and critically analyze aspects of evolutionary theory" (South Carolina Department of Education, 2006). Levinson and Sutton (2001) offered a sociocultural approach to policy that considers cultural and historical influences at all levels of the policy process. Lipsky (1980/2010) and others have identified teachers as de facto policy makers, exercising broad discretion in the execution of their work. This study looks to Ajzen's Theory of Planned Behavior as an initial framework to inform how evolutionary biology policy in South Carolina is conceptualized and understood at different levels of the policy process. The results of this study indicate that actors in the state's evolutionary biology policy process draw upon a myriad of Discourses (Gee, 1999/2005). These Discourses shape cultural dynamics and the agency of the policy actors as they navigate conflicting messages between testing mandates and evolutionary biology policy. There indeed exist gaps between how evolutionary biology policy in South Carolina is conceptualized and understood at the different levels of the policy process. Evidence from this study suggests that appropriation-level policy actors must be brought into the Discourse related to the critical analysis of evolutionary biology and academic freedom legislation must be enacted if South Carolina biology Indicator 5.6 is to realize practical significance in educational policy.

iBiology: communicating the process of science

PubMed Central

Goodwin, Sarah S.

2014-01-01

The Internet hosts an abundance of science video resources aimed at communicating scientific knowledge, including webinars, massive open online courses, and TED talks. Although these videos are efficient at disseminating information for diverse types of users, they often do not demonstrate the process of doing science, the excitement of scientific discovery, or how new scientific knowledge is developed. iBiology (www.ibiology.org), a project that creates open-access science videos about biology research and science-related topics, seeks to fill this need by producing videos by science leaders that make their ideas, stories, and experiences available to anyone with an Internet connection. PMID:25080124

Simulating complex intracellular processes using object-oriented computational modelling.

PubMed

Johnson, Colin G; Goldman, Jacki P; Gullick, William J

2004-11-01

The aim of this paper is to give an overview of computer modelling and simulation in cellular biology, in particular as applied to complex biochemical processes within the cell. This is illustrated by the use of the techniques of object-oriented modelling, where the computer is used to construct abstractions of objects in the domain being modelled, and these objects then interact within the computer to simulate the system and allow emergent properties to be observed. The paper also discusses the role of computer simulation in understanding complexity in biological systems, and the kinds of information which can be obtained about biology via simulation.

DNA as information: at the crossroads between biology, mathematics, physics and chemistry

PubMed Central

2016-01-01

On the one hand, biology, chemistry and also physics tell us how the process of translating the genetic information into life could possibly work, but we are still very far from a complete understanding of this process. On the other hand, mathematics and statistics give us methods to describe such natural systems—or parts of them—within a theoretical framework. Also, they provide us with hints and predictions that can be tested at the experimental level. Furthermore, there are peculiar aspects of the management of genetic information that are intimately related to information theory and communication theory. This theme issue is aimed at fostering the discussion on the problem of genetic coding and information through the presentation of different innovative points of view. The aim of the editors is to stimulate discussions and scientific exchange that will lead to new research on why and how life can exist from the point of view of the coding and decoding of genetic information. The present introduction represents the point of view of the editors on the main aspects that could be the subject of future scientific debate. PMID:26857674

Towards Engineering Biological Systems in a Broader Context.

PubMed

Venturelli, Ophelia S; Egbert, Robert G; Arkin, Adam P

2016-02-27

Significant advances have been made in synthetic biology to program information processing capabilities in cells. While these designs can function predictably in controlled laboratory environments, the reliability of these devices in complex, temporally changing environments has not yet been characterized. As human society faces global challenges in agriculture, human health and energy, synthetic biology should develop predictive design principles for biological systems operating in complex environments. Natural biological systems have evolved mechanisms to overcome innumerable and diverse environmental challenges. Evolutionary design rules should be extracted and adapted to engineer stable and predictable ecological function. We highlight examples of natural biological responses spanning the cellular, population and microbial community levels that show promise in synthetic biology contexts. We argue that synthetic circuits embedded in host organisms or designed ecologies informed by suitable measurement of biotic and abiotic environmental parameters could be used as engineering substrates to achieve target functions in complex environments. Successful implementation of these methods will broaden the context in which synthetic biological systems can be applied to solve important problems. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Default Mode Network Differentiates Biological From Non-Biological Motion

PubMed Central

Dayan, Eran; Sella, Irit; Mukovskiy, Albert; Douek, Yehonatan; Giese, Martin A.; Malach, Rafael; Flash, Tamar

2016-01-01

The default mode network (DMN) has been implicated in an array of social-cognitive functions, including self-referential processing, theory of mind, and mentalizing. Yet, the properties of the external stimuli that elicit DMN activity in relation to these domains remain unknown. Previous studies suggested that motion kinematics is utilized by the brain for social-cognitive processing. Here, we used functional MRI to examine whether the DMN is sensitive to parametric manipulations of observed motion kinematics. Preferential responses within core DMN structures differentiating non-biological from biological kinematics were observed for the motion of a realistically looking, human-like avatar, but not for an abstract object devoid of human form. Differences in connectivity patterns during the observation of biological versus non-biological kinematics were additionally observed. Finally, the results additionally suggest that the DMN is coupled more strongly with key nodes in the action observation network, namely the STS and the SMA, when the observed motion depicts human rather than abstract form. These findings are the first to implicate the DMN in the perception of biological motion. They may reflect the type of information used by the DMN in social-cognitive processing. PMID:25217472

A simplified computational memory model from information processing

PubMed Central

Zhang, Lanhua; Zhang, Dongsheng; Deng, Yuqin; Ding, Xiaoqian; Wang, Yan; Tang, Yiyuan; Sun, Baoliang

2016-01-01

This paper is intended to propose a computational model for memory from the view of information processing. The model, called simplified memory information retrieval network (SMIRN), is a bi-modular hierarchical functional memory network by abstracting memory function and simulating memory information processing. At first meta-memory is defined to express the neuron or brain cortices based on the biology and graph theories, and we develop an intra-modular network with the modeling algorithm by mapping the node and edge, and then the bi-modular network is delineated with intra-modular and inter-modular. At last a polynomial retrieval algorithm is introduced. In this paper we simulate the memory phenomena and functions of memorization and strengthening by information processing algorithms. The theoretical analysis and the simulation results show that the model is in accordance with the memory phenomena from information processing view. PMID:27876847

Skill Assessment in Ocean Biological Data Assimilation

NASA Technical Reports Server (NTRS)

Gregg, Watson W.; Friedrichs, Marjorie A. M.; Robinson, Allan R.; Rose, Kenneth A.; Schlitzer, Reiner; Thompson, Keith R.; Doney, Scott C.

2008-01-01

There is growing recognition that rigorous skill assessment is required to understand the ability of ocean biological models to represent ocean processes and distributions. Statistical analysis of model results with observations represents the most quantitative form of skill assessment, and this principle serves as well for data assimilation models. However, skill assessment for data assimilation requires special consideration. This is because there are three sets of information in the free-run model, data, and the assimilation model, which uses Data assimilation information from both the flee-run model and the data. Intercom parison of results among the three sets of information is important and useful for assessment, but is not conclusive since the three information sets are intertwined. An independent data set is necessary for an objective determination. Other useful measures of ocean biological data assimilation assessment include responses of unassimilated variables to the data assimilation, performance outside the prescribed region/time of interest, forecasting, and trend analysis. Examples of each approach from the literature are provided. A comprehensive list of ocean biological data assimilation and their applications of skill assessment, in both ecosystem/biogeochemical and fisheries efforts, is summarized.

Social networks to biological networks: systems biology of Mycobacterium tuberculosis.

PubMed

Vashisht, Rohit; Bhardwaj, Anshu; Osdd Consortium; Brahmachari, Samir K

2013-07-01

Contextualizing relevant information to construct a network that represents a given biological process presents a fundamental challenge in the network science of biology. The quality of network for the organism of interest is critically dependent on the extent of functional annotation of its genome. Mostly the automated annotation pipelines do not account for unstructured information present in volumes of literature and hence large fraction of genome remains poorly annotated. However, if used, this information could substantially enhance the functional annotation of a genome, aiding the development of a more comprehensive network. Mining unstructured information buried in volumes of literature often requires manual intervention to a great extent and thus becomes a bottleneck for most of the automated pipelines. In this review, we discuss the potential of scientific social networking as a solution for systematic manual mining of data. Focusing on Mycobacterium tuberculosis, as a case study, we discuss our open innovative approach for the functional annotation of its genome. Furthermore, we highlight the strength of such collated structured data in the context of drug target prediction based on systems level analysis of pathogen.

Information Processing in Living Systems

NASA Astrophysics Data System (ADS)

Tkačik, Gašper; Bialek, William

2016-03-01

Life depends as much on the flow of information as on the flow of energy. Here we review the many efforts to make this intuition precise. Starting with the building blocks of information theory, we explore examples where it has been possible to measure, directly, the flow of information in biological networks, or more generally where information-theoretic ideas have been used to guide the analysis of experiments. Systems of interest range from single molecules (the sequence diversity in families of proteins) to groups of organisms (the distribution of velocities in flocks of birds), and all scales in between. Many of these analyses are motivated by the idea that biological systems may have evolved to optimize the gathering and representation of information, and we review the experimental evidence for this optimization, again across a wide range of scales.

Advances in downstream processing of biologics - Spectroscopy: An emerging process analytical technology.

PubMed

Rüdt, Matthias; Briskot, Till; Hubbuch, Jürgen

2017-03-24

Process analytical technologies (PAT) for the manufacturing of biologics have drawn increased interest in the last decade. Besides being encouraged by the Food and Drug Administration's (FDA's) PAT initiative, PAT promises to improve process understanding, reduce overall production costs and help to implement continuous manufacturing. This article focuses on spectroscopic tools for PAT in downstream processing (DSP). Recent advances and future perspectives will be reviewed. In order to exploit the full potential of gathered data, chemometric tools are widely used for the evaluation of complex spectroscopic information. Thus, an introduction into the field will be given. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Biological network extraction from scientific literature: state of the art and challenges.

PubMed

Li, Chen; Liakata, Maria; Rebholz-Schuhmann, Dietrich

2014-09-01

Networks of molecular interactions explain complex biological processes, and all known information on molecular events is contained in a number of public repositories including the scientific literature. Metabolic and signalling pathways are often viewed separately, even though both types are composed of interactions involving proteins and other chemical entities. It is necessary to be able to combine data from all available resources to judge the functionality, complexity and completeness of any given network overall, but especially the full integration of relevant information from the scientific literature is still an ongoing and complex task. Currently, the text-mining research community is steadily moving towards processing the full body of the scientific literature by making use of rich linguistic features such as full text parsing, to extract biological interactions. The next step will be to combine these with information from scientific databases to support hypothesis generation for the discovery of new knowledge and the extension of biological networks. The generation of comprehensive networks requires technologies such as entity grounding, coordination resolution and co-reference resolution, which are not fully solved and are required to further improve the quality of results. Here, we analyse the state of the art for the extraction of network information from the scientific literature and the evaluation of extraction methods against reference corpora, discuss challenges involved and identify directions for future research. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Status and trends of the nation's biological resources

USGS Publications Warehouse

Mac, Michael J.; Opler, Paul A.; Puckett Haecker, Catherine E.; Doran, Peter D.

1998-01-01

This report is a comprehensive summary of the status and trends of our nation’s biological resources. The report describes the major processes and factors affecting biological resources, and it treats regional status and trends. Authors of the chapters and boxes in this two-volume report were drawn from federal and state agencies, universities, and private organizations, reflecting the U.S. Geological Survey’s national partnership approach to providing comprehensive, reliable information about our biological resources. Following scientific tradition, each chapter and box was peer-reviewed by anonymous scientific reviewers.

Mass Spectrometry: A Technique of Many Faces

PubMed Central

Olshina, Maya A.; Sharon, Michal

2016-01-01

Protein complexes form the critical foundation for a wide range of biological process, however understanding the intricate details of their activities is often challenging. In this review we describe how mass spectrometry plays a key role in the analysis of protein assemblies and the cellular pathways which they are involved in. Specifically, we discuss how the versatility of mass spectrometric approaches provides unprecedented information on multiple levels. We demonstrate this on the ubiquitin-proteasome proteolytic pathway, a process that is responsible for protein turnover. We follow the various steps of this degradation route and illustrate the different mass spectrometry workflows that were applied for elucidating molecular information. Overall, this review aims to stimulate the integrated use of multiple mass spectrometry approaches for analyzing complex biological systems. PMID:28100928

Emergence of biological organization through thermodynamic inversion.

PubMed

Kompanichenko, Vladimir

2014-01-01

Biological organization arises under thermodynamic inversion in prebiotic systems that provide the prevalence of free energy and information contribution over the entropy contribution. The inversion might occur under specific far-from-equilibrium conditions in prebiotic systems oscillating around the bifurcation point. At the inversion moment, (physical) information characteristic of non-biological systems acquires the new features: functionality, purposefulness, and control over the life processes, which transform it into biological information. Random sequences of amino acids and nucleotides, spontaneously synthesized in the prebiotic microsystem, in the primary living unit (probiont) re-assemble into functional sequences, involved into bioinformation circulation through nucleoprotein interaction, resulted in the genetic code emergence. According to the proposed concept, oscillating three-dimensional prebiotic microsystems transformed into probionts in the changeable hydrothermal medium of the early Earth. The inversion concept states that spontaneous (accidental, random) transformations in prebiotic systems cannot produce life; it is only non-spontaneous (perspective, purposeful) transformations, which are the result of thermodynamic inversion, that lead to the negentropy conversion of prebiotic systems into initial living units.

The Value of Animations in Biology Teaching: A Study of Long-Term Memory Retention

PubMed Central

2007-01-01

Previous work has established that a narrated animation is more effective at communicating a complex biological process (signal transduction) than the equivalent graphic with figure legend. To my knowledge, no study has been done in any subject area on the effectiveness of animations versus graphics in the long-term retention of information, a primary and critical issue in studies of teaching and learning. In this study, involving 393 student responses, three different animations and two graphics—one with and one lacking a legend—were used to determine the long-term retention of information. The results show that students retain more information 21 d after viewing an animation without narration compared with an equivalent graphic whether or not that graphic had a legend. Students' comments provide additional insight into the value of animations in the pedagogical process, and suggestions for future work are proposed. PMID:17785404

The value of animations in biology teaching: a study of long-term memory retention.

PubMed

O'Day, Danton H

2007-01-01

Previous work has established that a narrated animation is more effective at communicating a complex biological process (signal transduction) than the equivalent graphic with figure legend. To my knowledge, no study has been done in any subject area on the effectiveness of animations versus graphics in the long-term retention of information, a primary and critical issue in studies of teaching and learning. In this study, involving 393 student responses, three different animations and two graphics-one with and one lacking a legend-were used to determine the long-term retention of information. The results show that students retain more information 21 d after viewing an animation without narration compared with an equivalent graphic whether or not that graphic had a legend. Students' comments provide additional insight into the value of animations in the pedagogical process, and suggestions for future work are proposed.

Energy coding in biological neural networks

PubMed Central

Zhang, Zhikang

2007-01-01

According to the experimental result of signal transmission and neuronal energetic demands being tightly coupled to information coding in the cerebral cortex, we present a brand new scientific theory that offers an unique mechanism for brain information processing. We demonstrate that the neural coding produced by the activity of the brain is well described by our theory of energy coding. Due to the energy coding model’s ability to reveal mechanisms of brain information processing based upon known biophysical properties, we can not only reproduce various experimental results of neuro-electrophysiology, but also quantitatively explain the recent experimental results from neuroscientists at Yale University by means of the principle of energy coding. Due to the theory of energy coding to bridge the gap between functional connections within a biological neural network and energetic consumption, we estimate that the theory has very important consequences for quantitative research of cognitive function. PMID:19003513

Recent Developments in the Application of Biologically Inspired Computation to Chemical Sensing

NASA Astrophysics Data System (ADS)

Marco, S.; Gutierrez-Gálvez, A.

2009-05-01

Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. In this work, the state of the art concerning biologically inspired computation for chemical sensing will be reviewed. Instead of reviewing the whole body of computational neuroscience of olfaction, we restrict this review to the application of models to the processing of real chemical sensor data.

The biology/disease-driven human proteome project (B/D-HPP): enabling protein research for the life sciences community.

PubMed

Aebersold, Ruedi; Bader, Gary D; Edwards, Aled M; van Eyk, Jennifer E; Kussmann, Martin; Qin, Jun; Omenn, Gilbert S

2013-01-04

The biology and disease oriented branch of the Human Proteome Project (B/D-HPP) was established by the Human Proteome Organization (HUPO) with the main goal of supporting the broad application of state-of the-art measurements of proteins and proteomes by life scientists studying the molecular mechanisms of biological processes and human disease. This will be accomplished through the generation of research and informational resources that will support the routine and definitive measurement of the process or disease relevant proteins. The B/D-HPP is highly complementary to the C-HPP and will provide datasets and biological characterization useful to the C-HPP teams. In this manuscript we describe the goals, the plans, and the current status of the of the B/D-HPP.

Can a biologist fix a smartphone?-Just hack it!

PubMed

Kamoun, Sophien

2017-05-08

Biological systems integrate multiscale processes and networks and are, therefore, viewed as difficult to dissect. However, because of the clear-cut separation between the software code (the information encoded in the genome sequence) and hardware (organism), genome editors can operate as software engineers to hack biological systems without any particularly deep understanding of the complexity of the systems.

A Model System for the Study of Gene Expression in the Undergraduate Laboratory

ERIC Educational Resources Information Center

Hargadon, Kristian M.

2016-01-01

The flow of genetic information from DNA to RNA to protein, otherwise known as the "central dogma" of biology, is one of the most basic and overarching concepts in the biological sciences. Nevertheless, numerous studies have reported student misconceptions at the undergraduate level of this fundamental process of gene expression. This…

The Perception of Biological and Mechanical Motion in Female Fragile X Premutation Carriers

ERIC Educational Resources Information Center

Keri, Szabolcs; Benedek, Gyorgy

2010-01-01

Previous studies reported impaired visual information processing in patients with fragile x syndrome and in premutation carriers. In this study, we assessed the perception of biological motion (a walking point-light character) and mechanical motion (a rotating shape) in 25 female fragile x premutation carriers and in 20 healthy non-carrier…

Information Fluency for Undergraduate Biology Majors: Applications of Inquiry-based Learning in a Developmental Biology Course

ERIC Educational Resources Information Center

Gehring, Kathleen M.; Eastman, Deborah A.

2008-01-01

Many initiatives for the improvement of undergraduate science education call for inquiry-based learning that emphasizes investigative projects and reading of the primary literature. These approaches give students an understanding of science as a process and help them integrate content presented in courses. At the same time, general initiatives to…

Microscopy Images as Interactive Tools in Cell Modeling and Cell Biology Education

ERIC Educational Resources Information Center

Araujo-Jorge, Tania C.; Cardona, Tania S.; Mendes, Claudia L. S.; Henriques-Pons, Andrea; Meirelles, Rosane M. S.; Coutinho, Claudia M. L. M.; Aguiar, Luiz Edmundo V.; Meirelles, Maria de Nazareth L.; de Castro, Solange L.; Barbosa, Helene S.; Luz, Mauricio R. M. P.

2004-01-01

The advent of genomics, proteomics, and microarray technology has brought much excitement to science, both in teaching and in learning. The public is eager to know about the processes of life. In the present context of the explosive growth of scientific information, a major challenge of modern cell biology is to popularize basic concepts of…

Moving beyond a descriptive aquatic toxicology: the value of biological process and trait information.

PubMed

Segner, Helmut

2011-10-01

In order to improve the ability to link chemical exposure to toxicological and ecological effects, aquatic toxicology will have to move from observing what chemical concentrations induce adverse effects to more explanatory approaches, that are concepts which build on knowledge of biological processes and pathways leading from exposure to adverse effects, as well as on knowledge on stressor vulnerability as given by the genetic, physiological and ecological (e.g., life history) traits of biota. Developing aquatic toxicology in this direction faces a number of challenges, including (i) taking into account species differences in toxicant responses on the basis of the evolutionarily developed diversity of phenotypic vulnerability to environmental stressors, (ii) utilizing diversified biological response profiles to serve as biological read across for prioritizing chemicals, categorizing them according to modes of action, and for guiding targeted toxicity evaluation; (iii) prediction of ecological consequences of toxic exposure from knowledge of how biological processes and phenotypic traits lead to effect propagation across the levels of biological hierarchy; and (iv) the search for concepts to assess the cumulative impact of multiple stressors. An underlying theme in these challenges is that, in addition to the question of what the chemical does to the biological receptor, we should give increasing emphasis to the question how the biological receptor handles the chemicals, i.e., through which pathways the initial chemical-biological interaction extends to the adverse effects, how this extension is modulated by adaptive or compensatory processes as well as by phenotypic traits of the biological receptor. 2011 Elsevier B.V. All rights reserved.

Free Radicals in Chemical Biology: from Chemical Behavior to Biomarker Development

PubMed Central

Chatgilialoglu, Chryssostomos; Ferreri, Carla; Masi, Annalisa; Melchiorre, Michele; Sansone, Anna; Terzidis, Michael A.; Torreggiani, Armida

2013-01-01

The involvement of free radicals in life sciences has constantly increased with time and has been connected to several physiological and pathological processes. This subject embraces diverse scientific areas, spanning from physical, biological and bioorganic chemistry to biology and medicine, with applications to the amelioration of quality of life, health and aging. Multidisciplinary skills are required for the full investigation of the many facets of radical processes in the biological environment and chemical knowledge plays a crucial role in unveiling basic processes and mechanisms. We developed a chemical biology approach able to connect free radical chemical reactivity with biological processes, providing information on the mechanistic pathways and products. The core of this approach is the design of biomimetic models to study biomolecule behavior (lipids, nucleic acids and proteins) in aqueous systems, obtaining insights of the reaction pathways as well as building up molecular libraries of the free radical reaction products. This context can be successfully used for biomarker discovery and examples are provided with two classes of compounds: mono-trans isomers of cholesteryl esters, which are synthesized and used as references for detection in human plasma, and purine 5',8-cyclo-2'-deoxyribonucleosides, prepared and used as reference in the protocol for detection of such lesions in DNA samples, after ionizing radiations or obtained from different health conditions. PMID:23629513

A Biopsychological Model of Anti-drug PSA Processing: Developing Effective Persuasive Messages.

PubMed

Hohman, Zachary P; Keene, Justin Robert; Harris, Breanna N; Niedbala, Elizabeth M; Berke, Collin K

2017-11-01

For the current study, we developed and tested a biopsychological model to combine research on psychological tension, the Limited Capacity Model of Motivated Mediated Message Processing, and the endocrine system to predict and understand how people process anti-drug PSAs. We predicted that co-presentation of pleasant and unpleasant information, vs. solely pleasant or unpleasant, will trigger evaluative tension about the target behavior in persuasive messages and result in a biological response (increase in cortisol, alpha amylase, and heart rate). In experiment 1, we assessed the impact of co-presentation of pleasant and unpleasant information in persuasive messages on evaluative tension (conceptualized as attitude ambivalence), in experiment 2, we explored the impact of co-presentation on endocrine system responses (salivary cortisol and alpha amylase), and in experiment 3, we assessed the impact of co-presentation on heart rate. Across all experiments, we demonstrated that co-presentation of pleasant and unpleasant information, vs. solely pleasant or unpleasant, in persuasive communications leads to increases in attitude ambivalence, salivary cortisol, salivary alpha amylase, and heart rate. Taken together, the results support the initial paths of our biopsychological model of persuasive message processing and indicate that including both pleasant and unpleasant information in a message impacts the viewer. We predict that increases in evaluative tension and biological responses will aid in memory and cognitive processing of the message. However, future research is needed to test that hypothesis.

Controlled membrane translocation provides a mechanism for signal transduction and amplification

NASA Astrophysics Data System (ADS)

Langton, Matthew J.; Keymeulen, Flore; Ciaccia, Maria; Williams, Nicholas H.; Hunter, Christopher A.

2017-05-01

Transmission and amplification of chemical signals across lipid bilayer membranes is of profound significance in many biological processes, from the development of multicellular organisms to information processing in the nervous system. In biology, membrane-spanning proteins are responsible for the transmission of chemical signals across membranes, and signal transduction is often associated with an amplified signalling cascade. The ability to reproduce such processes in artificial systems has potential applications in sensing, controlled drug delivery and communication between compartments in tissue-like constructs of synthetic vesicles. Here we describe a mechanism for transmitting a chemical signal across a membrane based on the controlled translocation of a synthetic molecular transducer from one side of a lipid bilayer membrane to the other. The controlled molecular motion has been coupled to the activation of a catalyst on the inside of a vesicle, which leads to a signal-amplification process analogous to the biological counterpart.

Dupuytren's: a systems biology disease

PubMed Central

2011-01-01

Dupuytren's disease (DD) is an ill-defined fibroproliferative disorder of the palm of the hands leading to digital contracture. DD commonly occurs in individuals of northern European extraction. Cellular components and processes associated with DD pathogenesis include altered gene and protein expression of cytokines, growth factors, adhesion molecules, and extracellular matrix components. Histology has shown increased but varying levels of particular types of collagen, myofibroblasts and myoglobin proteins in DD tissue. Free radicals and localised ischaemia have been suggested to trigger the proliferation of DD tissue. Although the existing available biological information on DD may contain potentially valuable (though largely uninterpreted) information, the precise aetiology of DD remains unknown. Systems biology combines mechanistic modelling with quantitative experimentation in studies of networks and better understanding of the interaction of multiple components in disease processes. Adopting systems biology may be the ideal approach for future research in order to improve understanding of complex diseases of multifactorial origin. In this review, we propose that DD is a disease of several networks rather than of a single gene, and show that this accounts for the experimental observations obtained to date from a variety of sources. We outline how DD may be investigated more effectively by employing a systems biology approach that considers the disease network as a whole rather than focusing on any specific single molecule. PMID:21943049

Nanopipettes as Monitoring Probes for the Single Living Cell: State of the Art and Future Directions in Molecular Biology.

PubMed

Bulbul, Gonca; Chaves, Gepoliano; Olivier, Joseph; Ozel, Rifat Emrah; Pourmand, Nader

2018-06-06

Examining the behavior of a single cell within its natural environment is valuable for understanding both the biological processes that control the function of cells and how injury or disease lead to pathological change of their function. Single-cell analysis can reveal information regarding the causes of genetic changes, and it can contribute to studies on the molecular basis of cell transformation and proliferation. By contrast, whole tissue biopsies can only yield information on a statistical average of several processes occurring in a population of different cells. Electrowetting within a nanopipette provides a nanobiopsy platform for the extraction of cellular material from single living cells. Additionally, functionalized nanopipette sensing probes can differentiate analytes based on their size, shape or charge density, making the technology uniquely suited to sensing changes in single-cell dynamics. In this review, we highlight the potential of nanopipette technology as a non-destructive analytical tool to monitor single living cells, with particular attention to integration into applications in molecular biology.

Evidence for auditory-visual processing specific to biological motion.

PubMed

Wuerger, Sophie M; Crocker-Buque, Alexander; Meyer, Georg F

2012-01-01

Biological motion is usually associated with highly correlated sensory signals from more than one modality: an approaching human walker will not only have a visual representation, namely an increase in the retinal size of the walker's image, but also a synchronous auditory signal since the walker's footsteps will grow louder. We investigated whether the multisensorial processing of biological motion is subject to different constraints than ecologically invalid motion. Observers were presented with a visual point-light walker and/or synchronised auditory footsteps; the walker was either approaching the observer (looming motion) or walking away (receding motion). A scrambled point-light walker served as a control. Observers were asked to detect the walker's motion as quickly and as accurately as possible. In Experiment 1 we tested whether the reaction time advantage due to redundant information in the auditory and visual modality is specific for biological motion. We found no evidence for such an effect: the reaction time reduction was accounted for by statistical facilitation for both biological and scrambled motion. In Experiment 2, we dissociated the auditory and visual information and tested whether inconsistent motion directions across the auditory and visual modality yield longer reaction times in comparison to consistent motion directions. Here we find an effect specific to biological motion: motion incongruency leads to longer reaction times only when the visual walker is intact and recognisable as a human figure. If the figure of the walker is abolished by scrambling, motion incongruency has no effect on the speed of the observers' judgments. In conjunction with Experiment 1 this suggests that conflicting auditory-visual motion information of an intact human walker leads to interference and thereby delaying the response.

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.

The R-spondin family of proteins: emerging regulators of WNT signaling

PubMed Central

Jin, Yong-Ri; Yoon, Jeong Kyo

2012-01-01

Recently, the R-spondin (RSPO) family of proteins has emerged as important regulators of WNT signaling. Considering the wide spectrum of WNT signaling functions in normal biological processes and disease conditions, there has been a significantly growing interest in understanding the functional roles of RSPOs in multiple biological processes and determining the molecular mechanisms by which RSPOs regulate the WNT signaling pathway. Recent advances in the RSPO research field revealed some of the in vivo functions of RSPOs and provided new information regarding the mechanistic roles of RSPO activity in regulation of WNT signaling. Herein, we review recent progress in RSPO research with an emphasis on signaling mechanisms and biological functions. PMID:22982762

The Potential of Text Mining in Data Integration and Network Biology for Plant Research: A Case Study on Arabidopsis[C][W

PubMed Central

Van Landeghem, Sofie; De Bodt, Stefanie; Drebert, Zuzanna J.; Inzé, Dirk; Van de Peer, Yves

2013-01-01

Despite the availability of various data repositories for plant research, a wealth of information currently remains hidden within the biomolecular literature. Text mining provides the necessary means to retrieve these data through automated processing of texts. However, only recently has advanced text mining methodology been implemented with sufficient computational power to process texts at a large scale. In this study, we assess the potential of large-scale text mining for plant biology research in general and for network biology in particular using a state-of-the-art text mining system applied to all PubMed abstracts and PubMed Central full texts. We present extensive evaluation of the textual data for Arabidopsis thaliana, assessing the overall accuracy of this new resource for usage in plant network analyses. Furthermore, we combine text mining information with both protein–protein and regulatory interactions from experimental databases. Clusters of tightly connected genes are delineated from the resulting network, illustrating how such an integrative approach is essential to grasp the current knowledge available for Arabidopsis and to uncover gene information through guilt by association. All large-scale data sets, as well as the manually curated textual data, are made publicly available, hereby stimulating the application of text mining data in future plant biology studies. PMID:23532071

Parallel workflow manager for non-parallel bioinformatic applications to solve large-scale biological problems on a supercomputer.

PubMed

Suplatov, Dmitry; Popova, Nina; Zhumatiy, Sergey; Voevodin, Vladimir; Švedas, Vytas

2016-04-01

Rapid expansion of online resources providing access to genomic, structural, and functional information associated with biological macromolecules opens an opportunity to gain a deeper understanding of the mechanisms of biological processes due to systematic analysis of large datasets. This, however, requires novel strategies to optimally utilize computer processing power. Some methods in bioinformatics and molecular modeling require extensive computational resources. Other algorithms have fast implementations which take at most several hours to analyze a common input on a modern desktop station, however, due to multiple invocations for a large number of subtasks the full task requires a significant computing power. Therefore, an efficient computational solution to large-scale biological problems requires both a wise parallel implementation of resource-hungry methods as well as a smart workflow to manage multiple invocations of relatively fast algorithms. In this work, a new computer software mpiWrapper has been developed to accommodate non-parallel implementations of scientific algorithms within the parallel supercomputing environment. The Message Passing Interface has been implemented to exchange information between nodes. Two specialized threads - one for task management and communication, and another for subtask execution - are invoked on each processing unit to avoid deadlock while using blocking calls to MPI. The mpiWrapper can be used to launch all conventional Linux applications without the need to modify their original source codes and supports resubmission of subtasks on node failure. We show that this approach can be used to process huge amounts of biological data efficiently by running non-parallel programs in parallel mode on a supercomputer. The C++ source code and documentation are available from http://biokinet.belozersky.msu.ru/mpiWrapper .

A stable biologically motivated learning mechanism for visual feature extraction to handle facial categorization.

PubMed

Rajaei, Karim; Khaligh-Razavi, Seyed-Mahdi; Ghodrati, Masoud; Ebrahimpour, Reza; Shiri Ahmad Abadi, Mohammad Ebrahim

2012-01-01

The brain mechanism of extracting visual features for recognizing various objects has consistently been a controversial issue in computational models of object recognition. To extract visual features, we introduce a new, biologically motivated model for facial categorization, which is an extension of the Hubel and Wiesel simple-to-complex cell hierarchy. To address the synaptic stability versus plasticity dilemma, we apply the Adaptive Resonance Theory (ART) for extracting informative intermediate level visual features during the learning process, which also makes this model stable against the destruction of previously learned information while learning new information. Such a mechanism has been suggested to be embedded within known laminar microcircuits of the cerebral cortex. To reveal the strength of the proposed visual feature learning mechanism, we show that when we use this mechanism in the training process of a well-known biologically motivated object recognition model (the HMAX model), it performs better than the HMAX model in face/non-face classification tasks. Furthermore, we demonstrate that our proposed mechanism is capable of following similar trends in performance as humans in a psychophysical experiment using a face versus non-face rapid categorization task.

Selected papers from the Fourth Annual q-bio Conference on Cellular Information Processing.

PubMed

Nemenman, Ilya; Faeder, James R; Hlavacek, William S; Jiang, Yi; Wall, Michael E; Zilman, Anton

2011-10-01

This special issue consists of 11 original papers that elaborate on work presented at the Fourth Annual q-bio Conference on Cellular Information Processing, which was held on the campus of St John's College in Santa Fe, New Mexico, USA, 11-14 August 2010. Now in its fourth year, the q-bio conference has changed considerably over time. It is now well established and a major event in systems biology. The 2010 conference saw attendees from all continents (except Antarctica!) sharing novel results and participating in lively discussions at both the oral and poster sessions. The conference was oversubscribed and grew to 27 contributed talks, 16 poster spotlights and 137 contributed posters. We deliberately decreased the number of invited speakers to 21 to leave more space for contributed presentations, and the attendee feedback confirmed that the choice was a success. Although the q-bio conference has grown and matured, it has remained true to the original goal of being an intimate and dynamic event that brings together modeling, theory and quantitative experimentation for the study of cell regulation and information processing. Funded in part by a grant from NIGMS and by DOE funds through the Los Alamos National Laboratory Directed Research and Development program, the conference has continued to exhibit youth and vigor by attracting (and partially supporting) over 100 undergraduate, graduate and postdoctoral researchers. The associated q-bio summer school, which precedes the conference each year, further emphasizes the development of junior scientists and makes q-bio a singular event in its impact on the future of quantitative biology. In addition to an increased international presence, the conference has notably diversified its demographic representation within the USA, including increased participation from the southeastern corner of the country. One big change in the conference this year is our new publication partner, Physical Biology. Although we are very grateful to our previous partner, IET Systems Biology, for their help over the years in publicizing the work presented at the conference, we felt that the changing needs of our participants required that we find a new partner. We are thrilled that Physical Biology is publishing the q-bio proceedings this year. It has been a great collaboration, as evidenced by the high quality of this special issue. What's next for q-bio? We are happy to report that NIGMS has recently extended the q-bio conference grant for the next three years, ensuring strong support for junior researchers who need financial assistance to participate in the event. The conference will retain its emphasis on cellular information processing, but will also build connections to other areas of modern biology and biotechnology, focusing specifically on ecology and evolutionary biology next year. Indeed, to fully understand biological information processing systems, they must be studied in their ecological contexts. We will continue to honor distinguished contributors to the field in our opening banquets; the tradition started with Howard Berg, Bruce Alberts and Michael Savageau in previous years, and continues with Dennis Bray at the upcoming 2011 event. Starting in 2011, the conference will also venture into exploration of the social aspects of science. The future is bright for q-bio! We will see you at the Fifth Annual q-bio Conference on 10-13 August 2011, in Santa Fe, New Mexico, USA and at the Sixth Annual q-bio Conference in early August 2012.

The Diamond Light Source and the challenges ahead for structural biology: some informal remarks.

PubMed

Ramakrishnan, V

2015-03-06

The remarkable advances in structural biology in the past three decades have led to the determination of increasingly complex structures that lie at the heart of many important biological processes. Many of these advances have been made possible by the use of X-ray crystallography using synchrotron radiation. In this short article, some of the challenges and prospects that lie ahead will be summarized. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

An optimized workflow for the integration of biological information into radiotherapy planning: experiences with T1w DCE-MRI

NASA Astrophysics Data System (ADS)

Neff, T.; Kiessling, F.; Brix, G.; Baudendistel, K.; Zechmann, C.; Giesel, F. L.; Bendl, R.

2005-09-01

Planning of radiotherapy is often difficult due to restrictions on morphological images. New imaging techniques enable the integration of biological information into treatment planning and help to improve the detection of vital and aggressive tumour areas. This might improve clinical outcome. However, nowadays morphological data sets are still the gold standard in the planning of radiotherapy. In this paper, we introduce an in-house software platform enabling us to combine images from different imaging modalities yielding biological and morphological information in a workflow driven approach. This is demonstrated for the combination of morphological CT, MRI, functional DCE-MRI and PET data. Data of patients with a tumour of the prostate and with a meningioma were examined with DCE-MRI by applying pharmacokinetic two-compartment models for post-processing. The results were compared with the clinical plans for radiation therapy. Generated parameter maps give additional information about tumour spread, which can be incorporated in the definition of safety margins.

Teaching the Fundamentals of Biological Research with Primary Literature: Learning from the Discovery of the Gastric Proton Pump

ERIC Educational Resources Information Center

Zhu, Lixin

2011-01-01

For the purpose of teaching collegians the fundamentals of biological research, literature explaining the discovery of the gastric proton pump was presented in a 50-min lecture. The presentation included detailed information pertaining to the discovery process. This study was chosen because it demonstrates the importance of having a broad range of…

[The information principle in physiology: an analysis from the position of the general theory of functional systems].

PubMed

Sudakov, K V

1995-01-01

Information principle of the organism functional systems creation is formulated in the article. Transformation of organism biological needs on various levels into dominant motivation, behaviour and processes of basis needs satisfaction without loss in information sense is shown. Information role of emotions is analysed. On the base of experimental data is formulated concept of information environment of organism. Specially analysed the information basis of human psychological activity.

The Default Mode Network Differentiates Biological From Non-Biological Motion.

PubMed

Dayan, Eran; Sella, Irit; Mukovskiy, Albert; Douek, Yehonatan; Giese, Martin A; Malach, Rafael; Flash, Tamar

2016-01-01

The default mode network (DMN) has been implicated in an array of social-cognitive functions, including self-referential processing, theory of mind, and mentalizing. Yet, the properties of the external stimuli that elicit DMN activity in relation to these domains remain unknown. Previous studies suggested that motion kinematics is utilized by the brain for social-cognitive processing. Here, we used functional MRI to examine whether the DMN is sensitive to parametric manipulations of observed motion kinematics. Preferential responses within core DMN structures differentiating non-biological from biological kinematics were observed for the motion of a realistically looking, human-like avatar, but not for an abstract object devoid of human form. Differences in connectivity patterns during the observation of biological versus non-biological kinematics were additionally observed. Finally, the results additionally suggest that the DMN is coupled more strongly with key nodes in the action observation network, namely the STS and the SMA, when the observed motion depicts human rather than abstract form. These findings are the first to implicate the DMN in the perception of biological motion. They may reflect the type of information used by the DMN in social-cognitive processing. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Application of remote sensors in coastal zone observations

NASA Technical Reports Server (NTRS)

Caillat, J. M.; Elachi, C.; Brown, W. E., Jr.

1975-01-01

A review of processes taking place along coastlines and their biological consideration led to the determination of the elements which are required in the study of coastal structures and which are needed for better utilization of the resources from the oceans. The processes considered include waves, currents, and their influence on the erosion of coastal structures. Biological considerations include coastal fisheries, estuaries, and tidal marshes. Various remote sensors were analyzed for the information which they can provide and sites were proposed where a general ocean-observation plan could be tested.

Metal stable isotopes in low-temperature systems: A primer

USGS Publications Warehouse

Bullen, T.D.; Eisenhauer, A.

2009-01-01

Recent advances in mass spectrometry have allowed isotope scientists to precisely determine stable isotope variations in the metallic elements. Biologically infl uenced and truly inorganic isotope fractionation processes have been demonstrated over the mass range of metals. This Elements issue provides an overview of the application of metal stable isotopes to low-temperature systems, which extend across the borders of several science disciplines: geology, hydrology, biology, environmental science, and biomedicine. Information on instrumentation, fractionation processes, data-reporting terminology, and reference materials presented here will help the reader to better understand this rapidly evolving field.

Data-intensive drug development in the information age: applications of Systems Biology/Pharmacology/Toxicology.

PubMed

Kiyosawa, Naoki; Manabe, Sunao

2016-01-01

Pharmaceutical companies continuously face challenges to deliver new drugs with true medical value. R&D productivity of drug development projects depends on 1) the value of the drug concept and 2) data and in-depth knowledge that are used rationally to evaluate the drug concept's validity. A model-based data-intensive drug development approach is a key competitive factor used by innovative pharmaceutical companies to reduce information bias and rationally demonstrate the value of drug concepts. Owing to the accumulation of publicly available biomedical information, our understanding of the pathophysiological mechanisms of diseases has developed considerably; it is the basis for identifying the right drug target and creating a drug concept with true medical value. Our understanding of the pathophysiological mechanisms of disease animal models can also be improved; it can thus support rational extrapolation of animal experiment results to clinical settings. The Systems Biology approach, which leverages publicly available transcriptome data, is useful for these purposes. Furthermore, applying Systems Pharmacology enables dynamic simulation of drug responses, from which key research questions to be addressed in the subsequent studies can be adequately informed. Application of Systems Biology/Pharmacology to toxicology research, namely Systems Toxicology, should considerably improve the predictability of drug-induced toxicities in clinical situations that are difficult to predict from conventional preclinical toxicology studies. Systems Biology/Pharmacology/Toxicology models can be continuously improved using iterative learn-confirm processes throughout preclinical and clinical drug discovery and development processes. Successful implementation of data-intensive drug development approaches requires cultivation of an adequate R&D culture to appreciate this approach.

openBIS: a flexible framework for managing and analyzing complex data in biology research

PubMed Central

2011-01-01

Background Modern data generation techniques used in distributed systems biology research projects often create datasets of enormous size and diversity. We argue that in order to overcome the challenge of managing those large quantitative datasets and maximise the biological information extracted from them, a sound information system is required. Ease of integration with data analysis pipelines and other computational tools is a key requirement for it. Results We have developed openBIS, an open source software framework for constructing user-friendly, scalable and powerful information systems for data and metadata acquired in biological experiments. openBIS enables users to collect, integrate, share, publish data and to connect to data processing pipelines. This framework can be extended and has been customized for different data types acquired by a range of technologies. Conclusions openBIS is currently being used by several SystemsX.ch and EU projects applying mass spectrometric measurements of metabolites and proteins, High Content Screening, or Next Generation Sequencing technologies. The attributes that make it interesting to a large research community involved in systems biology projects include versatility, simplicity in deployment, scalability to very large data, flexibility to handle any biological data type and extensibility to the needs of any research domain. PMID:22151573

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

PubMed

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

2016-01-01

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

DNA as information: at the crossroads between biology, mathematics, physics and chemistry.

PubMed

Cartwright, Julyan H E; Giannerini, Simone; González, Diego L

2016-03-13

On the one hand, biology, chemistry and also physics tell us how the process of translating the genetic information into life could possibly work, but we are still very far from a complete understanding of this process. On the other hand, mathematics and statistics give us methods to describe such natural systems-or parts of them-within a theoretical framework. Also, they provide us with hints and predictions that can be tested at the experimental level. Furthermore, there are peculiar aspects of the management of genetic information that are intimately related to information theory and communication theory. This theme issue is aimed at fostering the discussion on the problem of genetic coding and information through the presentation of different innovative points of view. The aim of the editors is to stimulate discussions and scientific exchange that will lead to new research on why and how life can exist from the point of view of the coding and decoding of genetic information. The present introduction represents the point of view of the editors on the main aspects that could be the subject of future scientific debate. © 2016 The Author(s).

College Students' Understanding of the Carbon Cycle: Contrasting Principle-Based and Informal Reasoning

ERIC Educational Resources Information Center

Hartley, Laurel M.; Wilke, Brook J.; Schramm, Jonathon W.; D'Avanzo, Charlene; Anderson, Charles W.

2011-01-01

Processes that transform carbon (e.g., photosynthesis) play a prominent role in college biology courses. Our goals were to learn about student reasoning related to these processes and provide faculty with tools for instruction and assessment. We created a framework illustrating how carbon-transforming processes can be related to one another during…

The role of the Drosophila lateral horn in olfactory information processing and behavioral response.

PubMed

Schultzhaus, Janna N; Saleem, Sehresh; Iftikhar, Hina; Carney, Ginger E

2017-04-01

Animals must rapidly and accurately process environmental information to produce the correct behavioral responses. Reactions to previously encountered as well as to novel but biologically important stimuli are equally important, and one understudied region in the insect brain plays a role in processing both types of stimuli. The lateral horn is a higher order processing center that mainly processes olfactory information and is linked via olfactory projection neurons to another higher order learning center, the mushroom body. This review focuses on the lateral horn of Drosophila where most functional studies have been performed. We discuss connectivity between the primary olfactory center, the antennal lobe, and the lateral horn and mushroom body. We also present evidence for the lateral horn playing roles in innate behavioral responses by encoding biological valence to novel odor cues and in learned responses to previously encountered odors by modulating neural activity within the mushroom body. We describe how these processes contribute to acceptance or avoidance of appropriate or inappropriate mates and food, as well as the identification of predators. The lateral horn is a sexually dimorphic and plastic region of the brain that modulates other regions of the brain to ensure that insects produce rapid and effective behavioral responses to both novel and learned stimuli, yet multiple gaps exist in our knowledge of this important center. We anticipate that future studies on olfactory processing, learning, and innate behavioral responses will include the lateral horn in their examinations, leading to a more comprehensive understanding of olfactory information relay and resulting behaviors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Repurposing High-Throughput Image Assays Enables Biological Activity Prediction for Drug Discovery.

PubMed

Simm, Jaak; Klambauer, Günter; Arany, Adam; Steijaert, Marvin; Wegner, Jörg Kurt; Gustin, Emmanuel; Chupakhin, Vladimir; Chong, Yolanda T; Vialard, Jorge; Buijnsters, Peter; Velter, Ingrid; Vapirev, Alexander; Singh, Shantanu; Carpenter, Anne E; Wuyts, Roel; Hochreiter, Sepp; Moreau, Yves; Ceulemans, Hugo

2018-05-17

In both academia and the pharmaceutical industry, large-scale assays for drug discovery are expensive and often impractical, particularly for the increasingly important physiologically relevant model systems that require primary cells, organoids, whole organisms, or expensive or rare reagents. We hypothesized that data from a single high-throughput imaging assay can be repurposed to predict the biological activity of compounds in other assays, even those targeting alternate pathways or biological processes. Indeed, quantitative information extracted from a three-channel microscopy-based screen for glucocorticoid receptor translocation was able to predict assay-specific biological activity in two ongoing drug discovery projects. In these projects, repurposing increased hit rates by 50- to 250-fold over that of the initial project assays while increasing the chemical structure diversity of the hits. Our results suggest that data from high-content screens are a rich source of information that can be used to predict and replace customized biological assays. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2018-01-01

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

An Overview of Biofield Devices

PubMed Central

Muehsam, David; Chevalier, Gaétan; Barsotti, Tiffany

2015-01-01

Advances in biophysics, biology, functional genomics, neuroscience, psychology, psychoneuroimmunology, and other fields suggest the existence of a subtle system of “biofield” interactions that organize biological processes from the subatomic, atomic, molecular, cellular, and organismic to the interpersonal and cosmic levels. Biofield interactions may bring about regulation of biochemical, cellular, and neurological processes through means related to electromagnetism, quantum fields, and perhaps other means of modulating biological activity and information flow. The biofield paradigm, in contrast to a reductionist, chemistry-centered viewpoint, emphasizes the informational content of biological processes; biofield interactions are thought to operate in part via low-energy or “subtle” processes such as weak, nonthermal electromagnetic fields (EMFs) or processes potentially related to consciousness and nonlocality. Biofield interactions may also operate through or be reflected in more well-understood informational processes found in electroencephalographic (EEG) and electrocardiographic (ECG) data. Recent advances have led to the development of a wide variety of therapeutic and diagnostic biofield devices, defined as physical instruments best understood from the viewpoint of a biofield paradigm. Here, we provide a broad overview of biofield devices, with emphasis on those devices for which solid, peer-reviewed evidence exists. A subset of these devices, such as those based upon EEG- and ECG-based heart rate variability, function via mechanisms that are well understood and are widely employed in clinical settings. Other device modalities, such a gas discharge visualization and biophoton emission, appear to operate through incompletely understood mechanisms and have unclear clinical significance. Device modes of operation include EMF-light, EMF-heat, EMF-nonthermal, electrical current, vibration and sound, physical and mechanical, intentionality and nonlocality, gas and plasma, and other (mode of operation not well-understood). Methodological issues in device development and interfaces for future interdisciplinary research are discussed. Devices play prominent cultural and scientific roles in our society, and it is likely that device technologies will be one of the most influential access points for the furthering of biofield research and the dissemination of biofield concepts. This developing field of study presents new areas of research that have many important implications for both basic science and clinical medicine. PMID:26665041

An Overview of Biofield Devices.

PubMed

Muehsam, David; Chevalier, Gaétan; Barsotti, Tiffany; Gurfein, Blake T

2015-11-01

Advances in biophysics, biology, functional genomics, neuroscience, psychology, psychoneuroimmunology, and other fields suggest the existence of a subtle system of "biofield" interactions that organize biological processes from the subatomic, atomic, molecular, cellular, and organismic to the interpersonal and cosmic levels. Biofield interactions may bring about regulation of biochemical, cellular, and neurological processes through means related to electromagnetism, quantum fields, and perhaps other means of modulating biological activity and information flow. The biofield paradigm, in contrast to a reductionist, chemistry-centered viewpoint, emphasizes the informational content of biological processes; biofield interactions are thought to operate in part via low-energy or "subtle" processes such as weak, nonthermal electromagnetic fields (EMFs) or processes potentially related to consciousness and nonlocality. Biofield interactions may also operate through or be reflected in more well-understood informational processes found in electroencephalographic (EEG) and electrocardiographic (ECG) data. Recent advances have led to the development of a wide variety of therapeutic and diagnostic biofield devices, defined as physical instruments best understood from the viewpoint of a biofield paradigm. Here, we provide a broad overview of biofield devices, with emphasis on those devices for which solid, peer-reviewed evidence exists. A subset of these devices, such as those based upon EEG- and ECG-based heart rate variability, function via mechanisms that are well understood and are widely employed in clinical settings. Other device modalities, such a gas discharge visualization and biophoton emission, appear to operate through incompletely understood mechanisms and have unclear clinical significance. Device modes of operation include EMF-light, EMF-heat, EMF-nonthermal, electrical current, vibration and sound, physical and mechanical, intentionality and nonlocality, gas and plasma, and other (mode of operation not well-understood). Methodological issues in device development and interfaces for future interdisciplinary research are discussed. Devices play prominent cultural and scientific roles in our society, and it is likely that device technologies will be one of the most influential access points for the furthering of biofield research and the dissemination of biofield concepts. This developing field of study presents new areas of research that have many important implications for both basic science and clinical medicine.

Bioanalytical applications of SERS (surface-enhanced Raman spectroscopy).

PubMed

Hudson, Stephen D; Chumanov, George

2009-06-01

Surface-enhanced Raman scattering (SERS) is a powerful technique for analyzing biological samples as it can rapidly and nondestructively provide chemical and, in some cases, structural information about molecules in aqueous environments. In the Raman scattering process, both visible and near-infrared (NIR) wavelengths of light can be used to induce polarization of Raman-active molecules, leading to inelastic light scattering that yields specific molecular vibrational information. The development of surface enhancement has enabled Raman scattering to be an effective tool for qualitative as well as quantitative measurements with high sensitivity and specificity. Recent advances have led to many novel applications of SERS for biological analyses, resulting in new insights for biochemistry and molecular biology, the detection of biological warfare agents, and medical diagnostics for cancer, diabetes, and other diseases. This trend article highlights many of these recent investigations and provides a brief outlook in order to assess possible future directions of SERS as a bioanalytical tool.

Leaf LIMS: A Flexible Laboratory Information Management System with a Synthetic Biology Focus.

PubMed

Craig, Thomas; Holland, Richard; D'Amore, Rosalinda; Johnson, James R; McCue, Hannah V; West, Anthony; Zulkower, Valentin; Tekotte, Hille; Cai, Yizhi; Swan, Daniel; Davey, Robert P; Hertz-Fowler, Christiane; Hall, Anthony; Caddick, Mark

2017-12-15

This paper presents Leaf LIMS, a flexible laboratory information management system (LIMS) designed to address the complexity of synthetic biology workflows. At the project's inception there was a lack of a LIMS designed specifically to address synthetic biology processes, with most systems focused on either next generation sequencing or biobanks and clinical sample handling. Leaf LIMS implements integrated project, item, and laboratory stock tracking, offering complete sample and construct genealogy, materials and lot tracking, and modular assay data capture. Hence, it enables highly configurable task-based workflows and supports data capture from project inception to completion. As such, in addition to it supporting synthetic biology it is ideal for many laboratory environments with multiple projects and users. The system is deployed as a web application through Docker and is provided under a permissive MIT license. It is freely available for download at https://leaflims.github.io .

Promoting a structural view of biology for varied audiences: an overview of RCSB PDB resources and experiences.

PubMed

Dutta, Shuchismita; Zardecki, Christine; Goodsell, David S; Berman, Helen M

2010-10-01

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) supports scientific research and education worldwide by providing an essential resource of information on biomolecular structures. In addition to serving as a deposition, data-processing and distribution center for PDB data, the RCSB PDB offers resources and online materials that different audiences can use to customize their structural biology instruction. These include resources for general audiences that present macromolecular structure in the context of a biological theme, method-based materials for researchers who take a more traditional approach to the presentation of structural science, and materials that mix theme-based and method-based approaches for educators and students. Through these efforts the RCSB PDB aims to enable optimal use of structural data by researchers, educators and students designing and understanding experiments in biology, chemistry and medicine, and by general users making informed decisions about their life and health.

Methods and Apparatus for Autonomous Robotic Control

NASA Technical Reports Server (NTRS)

Gorshechnikov, Anatoly (Inventor); Livitz, Gennady (Inventor); Versace, Massimiliano (Inventor); Palma, Jesse (Inventor)

2017-01-01

Sensory processing of visual, auditory, and other sensor information (e.g., visual imagery, LIDAR, RADAR) is conventionally based on "stovepiped," or isolated processing, with little interactions between modules. Biological systems, on the other hand, fuse multi-sensory information to identify nearby objects of interest more quickly, more efficiently, and with higher signal-to-noise ratios. Similarly, examples of the OpenSense technology disclosed herein use neurally inspired processing to identify and locate objects in a robot's environment. This enables the robot to navigate its environment more quickly and with lower computational and power requirements.

Integrative mental health care: from theory to practice, Part 2.

PubMed

Lake, James

2008-01-01

Integrative approaches will lead to more accurate and different understandings of mental illness. Beneficial responses to complementary and alternative therapies provide important clues about the phenomenal nature of the human body in space-time and disparate biological, informational, and energetic factors associated with normal and abnormal psychological functioning. The conceptual framework of contemporary Western psychiatry includes multiple theoretical viewpoints, and there is no single best explanatory model of mental illness. Future theories of mental illness causation will not depend exclusively on empirical verification of strictly biological processes but will take into account both classically described biological processes and non-classical models, including complexity theory, resulting in more complete explanations of the characteristics and causes of symptoms and mechanisms of action that result in beneficial responses to treatments. Part 1 of this article examined the limitations of the theory and contemporary clinical methods employed in Western psychiatry and discussed implications of emerging paradigms in physics and the biological sciences for the future of psychiatry. In part 2, a practical methodology, for planning integrative assessment and treatment strategies in mental health care is proposed. Using this methodology the integrative management of moderate and severe psychiatric symptoms is reviewed in detail. As the conceptual framework of Western medicine evolves toward an increasingly integrative perspective, novel understanding of complex relationships between biological, informational, and energetic processes associated with normal psychological functioning and mental illness will lead to more effective integrative assessment and treatment strategies addressing the causes or meanings of symptoms at multiple hierarchic levels of body-brain-mind.

Integrative mental health care: from theory to practice, part 1.

PubMed

Lake, James

2007-01-01

Integrative approaches will lead to more accurate and different understandings of mental illness. Beneficial responses to complementary and alternative therapies provide important clues about the phenomenal nature of the human body in space-time and disparate biological, informational, and energetic factors associated with normal and abnormal psychological functioning. The conceptual framework of contemporary Western psychiatry includes multiple theoretical viewpoints, and there is no single best explanatory model of mental illness. Future theories of mental illness causation will not depend exclusively on empirical verification of strictly biological processes but will take into account both classically described biological processes and non-classical models, including complexity theory, resulting in more complete explanations of the characteristics and causes of symptoms and mechanisms of action that result in beneficial responses to treatments. Part 1 of this article examines the limitations of the theory and contemporary clinical methods employed in Western psychiatry and discusses implications of emerging paradigms in physics and the biological sciences for the future of psychiatry. In part 2, a practical methodology for planning integrative assessment and treatment strategies in mental health care is proposed. Using this methodology the integrative management of moderate and severe psychiatric symptoms is reviewed in detail. As the conceptual framework of Western medicine evolves toward an increasingly integrative perspective, novel understandings of complex relationships between biological, informational, and energetic processes associated with normal psychological functioning and mental illness will lead to more effective integrative assessment and treatment strategies addressing the causes or meanings of symptoms at multiple hierarchic levels of body-brain-mind.

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system

PubMed Central

2010-01-01

Background The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the “in silico” stochastic event based modeling approach to find the molecular dynamics of the system. Results In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Conclusions Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics. PMID:21143785

Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system.

PubMed

Ghosh, Preetam; Ghosh, Samik; Basu, Kalyan; Das, Sajal K; Zhang, Chaoyang

2010-12-01

The challenge today is to develop a modeling and simulation paradigm that integrates structural, molecular and genetic data for a quantitative understanding of physiology and behavior of biological processes at multiple scales. This modeling method requires techniques that maintain a reasonable accuracy of the biological process and also reduces the computational overhead. This objective motivates the use of new methods that can transform the problem from energy and affinity based modeling to information theory based modeling. To achieve this, we transform all dynamics within the cell into a random event time, which is specified through an information domain measure like probability distribution. This allows us to use the "in silico" stochastic event based modeling approach to find the molecular dynamics of the system. In this paper, we present the discrete event simulation concept using the example of the signal transduction cascade triggered by extra-cellular Mg2+ concentration in the two component PhoPQ regulatory system of Salmonella Typhimurium. We also present a model to compute the information domain measure of the molecular transport process by estimating the statistical parameters of inter-arrival time between molecules/ions coming to a cell receptor as external signal. This model transforms the diffusion process into the information theory measure of stochastic event completion time to get the distribution of the Mg2+ departure events. Using these molecular transport models, we next study the in-silico effects of this external trigger on the PhoPQ system. Our results illustrate the accuracy of the proposed diffusion models in explaining the molecular/ionic transport processes inside the cell. Also, the proposed simulation framework can incorporate the stochasticity in cellular environments to a certain degree of accuracy. We expect that this scalable simulation platform will be able to model more complex biological systems with reasonable accuracy to understand their temporal dynamics.

DISCO-SCA and Properly Applied GSVD as Swinging Methods to Find Common and Distinctive Processes

PubMed Central

Van Deun, Katrijn; Van Mechelen, Iven; Thorrez, Lieven; Schouteden, Martijn; De Moor, Bart; van der Werf, Mariët J.; De Lathauwer, Lieven; Smilde, Age K.; Kiers, Henk A. L.

2012-01-01

Background In systems biology it is common to obtain for the same set of biological entities information from multiple sources. Examples include expression data for the same set of orthologous genes screened in different organisms and data on the same set of culture samples obtained with different high-throughput techniques. A major challenge is to find the important biological processes underlying the data and to disentangle therein processes common to all data sources and processes distinctive for a specific source. Recently, two promising simultaneous data integration methods have been proposed to attain this goal, namely generalized singular value decomposition (GSVD) and simultaneous component analysis with rotation to common and distinctive components (DISCO-SCA). Results Both theoretical analyses and applications to biologically relevant data show that: (1) straightforward applications of GSVD yield unsatisfactory results, (2) DISCO-SCA performs well, (3) provided proper pre-processing and algorithmic adaptations, GSVD reaches a performance level similar to that of DISCO-SCA, and (4) DISCO-SCA is directly generalizable to more than two data sources. The biological relevance of DISCO-SCA is illustrated with two applications. First, in a setting of comparative genomics, it is shown that DISCO-SCA recovers a common theme of cell cycle progression and a yeast-specific response to pheromones. The biological annotation was obtained by applying Gene Set Enrichment Analysis in an appropriate way. Second, in an application of DISCO-SCA to metabolomics data for Escherichia coli obtained with two different chemical analysis platforms, it is illustrated that the metabolites involved in some of the biological processes underlying the data are detected by one of the two platforms only; therefore, platforms for microbial metabolomics should be tailored to the biological question. Conclusions Both DISCO-SCA and properly applied GSVD are promising integrative methods for finding common and distinctive processes in multisource data. Open source code for both methods is provided. PMID:22693578

A three-way approach for protein function classification

PubMed Central

2017-01-01

The knowledge of protein functions plays an essential role in understanding biological cells and has a significant impact on human life in areas such as personalized medicine, better crops and improved therapeutic interventions. Due to expense and inherent difficulty of biological experiments, intelligent methods are generally relied upon for automatic assignment of functions to proteins. The technological advancements in the field of biology are improving our understanding of biological processes and are regularly resulting in new features and characteristics that better describe the role of proteins. It is inevitable to neglect and overlook these anticipated features in designing more effective classification techniques. A key issue in this context, that is not being sufficiently addressed, is how to build effective classification models and approaches for protein function prediction by incorporating and taking advantage from the ever evolving biological information. In this article, we propose a three-way decision making approach which provides provisions for seeking and incorporating future information. We considered probabilistic rough sets based models such as Game-Theoretic Rough Sets (GTRS) and Information-Theoretic Rough Sets (ITRS) for inducing three-way decisions. An architecture of protein functions classification with probabilistic rough sets based three-way decisions is proposed and explained. Experiments are carried out on Saccharomyces cerevisiae species dataset obtained from Uniprot database with the corresponding functional classes extracted from the Gene Ontology (GO) database. The results indicate that as the level of biological information increases, the number of deferred cases are reduced while maintaining similar level of accuracy. PMID:28234929

A three-way approach for protein function classification.

PubMed

Ur Rehman, Hafeez; Azam, Nouman; Yao, JingTao; Benso, Alfredo

2017-01-01

The knowledge of protein functions plays an essential role in understanding biological cells and has a significant impact on human life in areas such as personalized medicine, better crops and improved therapeutic interventions. Due to expense and inherent difficulty of biological experiments, intelligent methods are generally relied upon for automatic assignment of functions to proteins. The technological advancements in the field of biology are improving our understanding of biological processes and are regularly resulting in new features and characteristics that better describe the role of proteins. It is inevitable to neglect and overlook these anticipated features in designing more effective classification techniques. A key issue in this context, that is not being sufficiently addressed, is how to build effective classification models and approaches for protein function prediction by incorporating and taking advantage from the ever evolving biological information. In this article, we propose a three-way decision making approach which provides provisions for seeking and incorporating future information. We considered probabilistic rough sets based models such as Game-Theoretic Rough Sets (GTRS) and Information-Theoretic Rough Sets (ITRS) for inducing three-way decisions. An architecture of protein functions classification with probabilistic rough sets based three-way decisions is proposed and explained. Experiments are carried out on Saccharomyces cerevisiae species dataset obtained from Uniprot database with the corresponding functional classes extracted from the Gene Ontology (GO) database. The results indicate that as the level of biological information increases, the number of deferred cases are reduced while maintaining similar level of accuracy.

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

Objects and processes: Two notions for understanding biological information.

PubMed

Mercado-Reyes, Agustín; Padilla-Longoria, Pablo; Arroyo-Santos, Alfonso

2015-09-07

In spite of being ubiquitous in life sciences, the concept of information is harshly criticized. Uses of the concept other than those derived from Shannon׳s theory are denounced as metaphoric. We perform a computational experiment to explore whether Shannon׳s information is adequate to describe the uses of said concept in commonplace scientific practice. Our results show that semantic sequences do not have unique complexity values different from the value of meaningless sequences. This result suggests that quantitative theoretical frameworks do not account fully for the complex phenomenon that the term "information" refers to. We propose a restructuring of the concept into two related, but independent notions, and conclude that a complete theory of biological information must account completely not only for both notions, but also for the relationship between them. Copyright © 2015 Elsevier Ltd. All rights reserved.

Critical review of real-time methods for solid waste characterisation: Informing material recovery and fuel production.

PubMed

Vrancken, C; Longhurst, P J; Wagland, S T

2017-03-01

Waste management processes generally represent a significant loss of material, energy and economic resources, so legislation and financial incentives are being implemented to improve the recovery of these valuable resources whilst reducing contamination levels. Material recovery and waste derived fuels are potentially valuable options being pursued by industry, using mechanical and biological processes incorporating sensor and sorting technologies developed and optimised for recycling plants. In its current state, waste management presents similarities to other industries that could improve their efficiencies using process analytical technology tools. Existing sensor technologies could be used to measure critical waste characteristics, providing data required by existing legislation, potentially aiding waste treatment processes and assisting stakeholders in decision making. Optical technologies offer the most flexible solution to gather real-time information applicable to each of the waste mechanical and biological treatment processes used by industry. In particular, combinations of optical sensors in the visible and the near-infrared range from 800nm to 2500nm of the spectrum, and different mathematical techniques, are able to provide material information and fuel properties with typical performance levels between 80% and 90%. These sensors not only could be used to aid waste processes, but to provide most waste quality indicators required by existing legislation, whilst offering better tools to the stakeholders. Copyright © 2017 Elsevier Ltd. All rights reserved.

A biologically inspired model of bat echolocation in a cluttered environment with inputs designed from field Recordings

NASA Astrophysics Data System (ADS)

Loncich, Kristen Teczar

Bat echolocation strategies and neural processing of acoustic information, with a focus on cluttered environments, is investigated in this study. How a bat processes the dense field of echoes received while navigating and foraging in the dark is not well understood. While several models have been developed to describe the mechanisms behind bat echolocation, most are based in mathematics rather than biology, and focus on either peripheral or neural processing---not exploring how these two levels of processing are vitally connected. Current echolocation models also do not use habitat specific acoustic input, or account for field observations of echolocation strategies. Here, a new approach to echolocation modeling is described capturing the full picture of echolocation from signal generation to a neural picture of the acoustic scene. A biologically inspired echolocation model is developed using field research measurements of the interpulse interval timing used by a frequency modulating (FM) bat in the wild, with a whole method approach to modeling echolocation including habitat specific acoustic inputs, a biologically accurate peripheral model of sound processing by the outer, middle, and inner ear, and finally a neural model incorporating established auditory pathways and neuron types with echolocation adaptations. Field recordings analyzed underscore bat sonar design differences observed in the laboratory and wild, and suggest a correlation between interpulse interval groupings and increased clutter. The scenario model provides habitat and behavior specific echoes and is a useful tool for both modeling and behavioral studies, and the peripheral and neural model show that spike-time information and echolocation specific neuron types can produce target localization in the midbrain.

Biophysical mechanisms complementing "classical" cell biology.

PubMed

Funk, Richard H W

2018-01-01

This overview addresses phenomena in cell- and molecular biology which are puzzling by their fast and highly coordinated way of organization. Generally, it appears that informative processes probably involved are more on the biophysical than on the classical biochemical side. The coordination problem is explained within the first part of the review by the topic of endogenous electrical phenomena. These are found e.g. in fast tissue organization and reorganization processes like development, wound healing and regeneration. Here, coupling into classical biochemical signaling and reactions can be shown by modern microscopy, electronics and bioinformatics. Further, one can follow the triggered reactions seamlessly via molecular biology till into genetics. Direct observation of intracellular electric processes is very difficult because of e.g. shielding through the cell membrane and damping by other structures. Therefore, we have to rely on photonic and photon - phonon coupling phenomena like molecular vibrations, which are addressed within the second part. Molecules normally possess different charge moieties and thus small electromagnetic (EMF) patterns arise during molecular vibration. These patterns can now be measured best within the optical part of the spectrum - much less in the lower terahertz till kHz and lower Hz part (third part of this review). Finally, EMFs facilitate quantum informative processes in coherent domains of molecular, charge and electron spin motion. This helps to coordinate such manifold and intertwined processes going on within cells, tissues and organs (part 4). Because the phenomena described in part 3 and 4 of the review still await really hard proofs we need concerted efforts and a combination of biophysics, molecular biology and informatics to unravel the described mysteries in "physics of life".

Quantum biology of the retina.

PubMed

Sia, Paul Ikgan; Luiten, André N; Stace, Thomas M; Wood, John Pm; Casson, Robert J

2014-08-01

The emerging field of quantum biology has led to a greater understanding of biological processes at the microscopic level. There is recent evidence to suggest that non-trivial quantum features such as entanglement, tunnelling and coherence have evolved in living systems. These quantum features are particularly evident in supersensitive light-harvesting systems such as in photosynthesis and photoreceptors. A biomimetic strategy utilizing biological quantum phenomena might allow new advances in the field of quantum engineering, particularly in quantum information systems. In addition, a better understanding of quantum biological features may lead to novel medical diagnostic and therapeutic developments. In the present review, we discuss the role of quantum physics in biological systems with an emphasis on the retina. © 2014 Royal Australian and New Zealand College of Ophthalmologists.

Biologically inspired information theory: Adaptation through construction of external reality models by living systems.

PubMed

Nakajima, Toshiyuki

2015-12-01

Higher animals act in the world using their external reality models to cope with the uncertain environment. Organisms that have not developed such information-processing organs may also have external reality models built in the form of their biochemical, physiological, and behavioral structures, acquired by natural selection through successful models constructed internally. Organisms subject to illusions would fail to survive in the material universe. How can organisms, or living systems in general, determine the external reality from within? This paper starts with a phenomenological model, in which the self constitutes a reality model developed through the mental processing of phenomena. Then, the it-from-bit concept is formalized using a simple mathematical model. For this formalization, my previous work on an algorithmic process is employed to constitute symbols referring to the external reality, called the inverse causality, with additional improvements to the previous work. Finally, as an extension of this model, the cognizers system model is employed to describe the self as one of many material entities in a world, each of which acts as a subject by responding to the surrounding entities. This model is used to propose a conceptual framework of information theory that can deal with both the qualitative (semantic) and quantitative aspects of the information involved in biological processes. Copyright © 2015 Elsevier Ltd. All rights reserved.

Top-down causation by information control: from a philosophical problem to a scientific research programme

PubMed Central

Auletta, G; Ellis, G.F.R; Jaeger, L

2008-01-01

It has been claimed that different types of causes must be considered in biological systems, including top-down as well as same-level and bottom-up causation, thus enabling the top levels to be causally efficacious in their own right. To clarify this issue, the important distinctions between information and signs are introduced here and the concepts of information control and functional equivalence classes in those systems are rigorously defined and used to characterize when top-down causation by feedback control happens, in a way that is testable. The causally significant elements we consider are equivalence classes of lower level processes, realized in biological systems through different operations having the same outcome within the context of information control and networks. PMID:18319208

A Focus on Polarity: Investigating the Role of Orientation Cues in Mediating Student Performance on mRNA Synthesis Tasks in an Introductory Cell and Molecular Biology Course

ERIC Educational Resources Information Center

Olimpo, Jeffrey T.; Quijas, Daniel A.; Quintana, Anita M.

2017-01-01

The central dogma has served as a foundational model for information flow, exchange, and storage in the biological sciences for several decades. Despite its continued importance, however, recent research suggests that novices in the domain possess several misconceptions regarding the aforementioned processes, including those pertaining…

Developing a Teacher Identity: TAs' Perspectives about Learning to Teach Inquiry-Based Biology Labs

ERIC Educational Resources Information Center

Gormally, Cara

2016-01-01

Becoming a teacher involves a continual process of identity development and negotiation. Expectations and norms for particular pedagogies impact and inform this development. In inquiry based classes, instructors are expected to act as learning facilitators rather than information providers. For novice inquiry instructors, developing a teacher…

Geospatial Technology Applications and Infrastructure in the Biological Resources Division

USGS Publications Warehouse

D'Erchia, Frank; Getter, James; D'Erchia, Terry D.; Root, Ralph; Stitt, Susan; White, Barbara

1998-01-01

Executive Summary -- Automated spatial processing technology such as geographic information systems (GIS), telemetry, and satellite-based remote sensing are some of the more recent developments in the long history of geographic inquiry. For millennia, humankind has endeavored to map the Earth's surface and identify spatial relationships. But the precision with which we can locate geographic features has increased exponentially with satellite positioning systems. Remote sensing, GIS, thematic mapping, telemetry, and satellite positioning systems such as the Global Positioning System (GPS) are tools that greatly enhance the quality and rapidity of analysis of biological resources. These technologies allow researchers, planners, and managers to more quickly and accurately determine appropriate strategies and actions. Researchers and managers can view information from new and varying perspectives using GIS and remote sensing, and GPS receivers allow the researcher or manager to identify the exact location of interest. These geospatial technologies support the mission of the U.S. Geological Survey (USGS) Biological Resources Division (BRD) and the Strategic Science Plan (BRD 1996) by providing a cost-effective and efficient method for collection, analysis, and display of information. The BRD mission is 'to work with others to provide the scientific understanding and technologies needed to support the sound management and conservation of our Nation's biological resources.' A major responsibility of the BRD is to develop and employ advanced technologies needed to synthesize, analyze, and disseminate biological and ecological information. As the Strategic Science Plan (BRD 1996) states, 'fulfilling this mission depends on effectively balancing the immediate need for information to guide management of biological resources with the need for technical assistance and long-range, strategic information to understand and predict emerging patterns and trends in ecological systems.' Information sharing plays a key role in nearly everything BRD does. The Strategic Science Plan discusses the need to (1) develop tools and standards for information transfer, (2) disseminate information, and (3) facilitate effective use of information. This effort centers around the National Biological Information Infrastructure (NBII) and the National Spatial Data Infrastructure (NSDI), components of the National Information Infrastructure. The NBII and NSDI are distributed electronic networks of biological and geographical data and information, as well as tools to help users around the world easily find and retrieve the biological and geographical data and information they need. The BRD is responsible for developing scientifically and statistically reliable methods and protocols to assess the status and trends of the Nation's biological resources. Scientists also conduct important inventory and monitoring studies to maintain baseline information on these same resources. Research on those species for which the Department of the Interior (DOI) has trust responsibilities (including endangered species and migratory species) involves laboratory and field studies of individual animals and the environments in which they live. Researchboth tactical and strategicis conducted at the BRD's 17 science centers and 81 field stations, 54 Cooperative Fish and Wildlife Research Units in 40 states, and at 11 former Cooperative Park Study Units. Studies encompass fish, birds, mammals, and plants, as well as their ecosystems and the surrounding landscape. Biological Resources Division researchers use a variety of scientific tools in their endeavors to understand the causes of biological and ecological trends. Research results are used by managers to predict environmental changes and to help them take appropriate measures to manage resources effectively. The BRD Geospatial Technology Program facilitates the collection, analysis, and dissemination of data and informat

Integrated omics for the identification of key functionalities in biological wastewater treatment microbial communities.

PubMed

Narayanasamy, Shaman; Muller, Emilie E L; Sheik, Abdul R; Wilmes, Paul

2015-05-01

Biological wastewater treatment plants harbour diverse and complex microbial communities which prominently serve as models for microbial ecology and mixed culture biotechnological processes. Integrated omic analyses (combined metagenomics, metatranscriptomics, metaproteomics and metabolomics) are currently gaining momentum towards providing enhanced understanding of community structure, function and dynamics in situ as well as offering the potential to discover novel biological functionalities within the framework of Eco-Systems Biology. The integration of information from genome to metabolome allows the establishment of associations between genetic potential and final phenotype, a feature not realizable by only considering single 'omes'. Therefore, in our opinion, integrated omics will become the future standard for large-scale characterization of microbial consortia including those underpinning biological wastewater treatment processes. Systematically obtained time and space-resolved omic datasets will allow deconvolution of structure-function relationships by identifying key members and functions. Such knowledge will form the foundation for discovering novel genes on a much larger scale compared with previous efforts. In general, these insights will allow us to optimize microbial biotechnological processes either through better control of mixed culture processes or by use of more efficient enzymes in bioengineering applications. © 2015 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Fusing Sensor Paradigms to Acquire Chemical Information: An Integrative Role for Smart Biopolymeric Hydrogels

PubMed Central

Kim, Eunkyoung; Liu, Yi; Ben-Yoav, Hadar; Winkler, Thomas E.; Yan, Kun; Shi, Xiaowen; Shen, Jana; Kelly, Deanna L.; Ghodssi, Reza; Bentley, William E.

2017-01-01

The Information Age transformed our lives but it has had surprisingly little impact on the way chemical information (e.g., from our biological world) is acquired, analyzed and communicated. Sensor systems are poised to change this situation by providing rapid access to chemical information. This access will be enabled by technological advances from various fields: biology enables the synthesis, design and discovery of molecular recognition elements as well as the generation of cell-based signal processors; physics and chemistry are providing nano-components that facilitate the transmission and transduction of signals rich with chemical information; microfabrication is yielding sensors capable of receiving these signals through various modalities; and signal processing analysis enhances the extraction of chemical information. The authors contend that integral to the development of functional sensor systems will be materials that (i) enable the integrative and hierarchical assembly of various sensing components (for chemical recognition and signal transduction) and (ii) facilitate meaningful communication across modalities. It is suggested that stimuli-responsive self-assembling biopolymers can perform such integrative functions, and redox provides modality-spanning communication capabilities. Recent progress toward the development of electrochemical sensors to manage schizophrenia is used to illustrate the opportunities and challenges for enlisting sensors for chemical information processing. PMID:27616350

Can biological motion research provide insight on how to reduce friendly fire incidents?

PubMed

Steel, Kylie A; Baxter, David; Dogramaci, Sera; Cobley, Stephen; Ellem, Eathan

2016-10-01

The ability to accurately detect, perceive, and recognize biological motion can be associated with a fundamental drive for survival, and it is a significant interest for perception researchers. This field examines various perceptual features of motion and has been assessed and applied in several real-world contexts (e.g., biometric, sport). Unexplored applications still exist however, including the military issue of friendly fire. There are many causes and processes leading to friendly fire and specific challenges that are associated with visual information extraction during engagement, such as brief glimpses, low acuity, camouflage, and uniform deception. Furthermore, visual information must often be processed under highly stressful (potentially threatening), time-constrained conditions that present a significant problem for soldiers. Biological motion research and anecdotal evidence from experienced combatants suggests that intentions, emotions, identities of human motion can be identified and discriminated, even when visual display is degraded or limited. Furthermore, research suggests that perceptual discriminatory capability of movement under visually constrained conditions is trainable. Therefore, given the limited military research linked to biological motion and friendly fire, an opportunity for cross-disciplinary investigations exists. The focus of this paper is twofold: first, to provide evidence for the possible link between biological motion factors and friendly fire, and second, to propose conceptual and methodological considerations and recommendations for perceptual-cognitive training within current military programs.

Advancing the State of the Art in Applying Network Science to C2

DTIC Science & Technology

2014-06-01

technological networks to include information , cognitive and social networks, they have yet to apply the full range of theoretical instruments now...robustness, and processes. While NEC researchers extended their coverage from technological networks to include information , cognitive and social networks...can be found in a wide variety of domains. For example, Newman (2003) surveys work on biological, technological , information , and social networks

When galectins recognize glycans: from biochemistry to physiology and back again.

PubMed

Di Lella, Santiago; Sundblad, Victoria; Cerliani, Juan P; Guardia, Carlos M; Estrin, Dario A; Vasta, Gerardo R; Rabinovich, Gabriel A

2011-09-20

In the past decade, increasing efforts have been devoted to the study of galectins, a family of evolutionarily conserved glycan-binding proteins with multifunctional properties. Galectins function, either intracellularly or extracellularly, as key biological mediators capable of monitoring changes occurring on the cell surface during fundamental biological processes such as cellular communication, inflammation, development, and differentiation. Their highly conserved structures, exquisite carbohydrate specificity, and ability to modulate a broad spectrum of biological processes have captivated a wide range of scientists from a wide spectrum of disciplines, including biochemistry, biophysics, cell biology, and physiology. However, in spite of enormous efforts to dissect the functions and properties of these glycan-binding proteins, limited information about how structural and biochemical aspects of these proteins can influence biological functions is available. In this review, we aim to integrate structural, biochemical, and functional aspects of this bewildering and ancient family of glycan-binding proteins and discuss their implications in physiologic and pathologic settings. © 2011 American Chemical Society

Functional model of biological neural networks.

PubMed

Lo, James Ting-Ho

2010-12-01

A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate neurons of the first type, supervised and unsupervised Hebbian learning mechanisms for easy learning and retrieving, an arrangement of dendritic trees for maximizing generalization, hardwiring for rotation-translation-scaling invariance, and feedback connections with different delay durations for neurons to make full use of present and past informations generated by neurons in the same and higher layers. These functional models and their processing operations have many functions of biological neural networks that have not been achieved by other models in the open literature and provide logically coherent answers to many long-standing neuroscientific questions. However, biological justifications of these functional models and their processing operations are required for THPAM to qualify as a macroscopic model (or low-order approximate) of biological neural networks.

iBiology: communicating the process of science.

PubMed

Goodwin, Sarah S

2014-08-01

The Internet hosts an abundance of science video resources aimed at communicating scientific knowledge, including webinars, massive open online courses, and TED talks. Although these videos are efficient at disseminating information for diverse types of users, they often do not demonstrate the process of doing science, the excitement of scientific discovery, or how new scientific knowledge is developed. iBiology (www.ibiology.org), a project that creates open-access science videos about biology research and science-related topics, seeks to fill this need by producing videos by science leaders that make their ideas, stories, and experiences available to anyone with an Internet connection. © 2014 Goodwin. This article is distributed by The American Society for Cell Biology under license from the author(s). Two months after publication 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).

DESIGN MANUAL: PHOSPHORUS REMOVAL

EPA Science Inventory

This manual summarizes process design information for the best developed methods for removing phosphorus from wastewater. his manual discusses several proven phosphorus removal methods, including phosphorus removal obtainable through biological activity as well as chemical precip...

Keeping Signals Straight: How Cells Process Information and Make Decisions

PubMed Central

Laub, Michael T.

2016-01-01

As we become increasingly dependent on electronic information-processing systems at home and work, it’s easy to lose sight of the fact that our very survival depends on highly complex biological information-processing systems. Each of the trillions of cells that form the human body has the ability to detect and respond to a wide range of stimuli and inputs, using an extraordinary set of signaling proteins to process this information and make decisions accordingly. Indeed, cells in all organisms rely on these signaling proteins to survive and proliferate in unpredictable and sometimes rapidly changing environments. But how exactly do these proteins relay information within cells, and how do they keep a multitude of incoming signals straight? Here, I describe recent efforts to understand the fidelity of information flow inside cells. This work is providing fundamental insight into how cells function. Additionally, it may lead to the design of novel antibiotics that disrupt the signaling of pathogenic bacteria or it could help to guide the treatment of cancer, which often involves information-processing gone awry inside human cells. PMID:27427909

Cochlea-inspired sensing node for compressive sensing

NASA Astrophysics Data System (ADS)

Peckens, Courtney A.; Lynch, Jerome P.

2013-04-01

While sensing technologies for structural monitoring applications have made significant advances over the last several decades, there is still room for improvement in terms of computational efficiency, as well as overall energy consumption. The biological nervous system can offer a potential solution to address these current deficiencies. The nervous system is capable of sensing and aggregating information about the external environment through very crude processing units known as neurons. Neurons effectively communicate in an extremely condensed format by encoding information into binary electrical spike trains, thereby reducing the amount of raw information sent throughout a neural network. Due to its unique signal processing capabilities, the mammalian cochlea and its interaction with the biological nervous system is of particular interest for devising compressive sensing strategies for dynamic engineered systems. The cochlea uses a novel method of place theory and frequency decomposition, thereby allowing for rapid signal processing within the nervous system. In this study, a low-power sensing node is proposed that draws inspiration from the mechanisms employed by the cochlea and the biological nervous system. As such, the sensor is able to perceive and transmit a compressed representation of the external stimulus with minimal distortion. Each sensor represents a basic building block, with function similar to the neuron, and can form a network with other sensors, thus enabling a system that can convey input stimulus in an extremely condensed format. The proposed sensor is validated through a structural monitoring application of a single degree of freedom structure excited by seismic ground motion.

Advances in biologically inspired on/near sensor processing

NASA Astrophysics Data System (ADS)

McCarley, Paul L.

1999-07-01

As electro-optic sensors increase in size and frame rate, the data transfer and digital processing resource requirements also increase. In many missions, the spatial area of interest is but a small fraction of the available field of view. Choosing the right region of interest, however, is a challenge and still requires an enormous amount of downstream digital processing resources. In order to filter this ever-increasing amount of data, we look at how nature solves the problem. The Advanced Guidance Division of the Munitions Directorate, Air Force Research Laboratory at Elgin AFB, Florida, has been pursuing research in the are of advanced sensor and image processing concepts based on biologically inspired sensory information processing. A summary of two 'neuromorphic' processing efforts will be presented along with a seeker system concept utilizing this innovative technology. The Neuroseek program is developing a 256 X 256 2-color dual band IRFPA coupled to an optimized silicon CMOS read-out and processing integrated circuit that provides simultaneous full-frame imaging in MWIR/LWIR wavebands along with built-in biologically inspired sensor image processing functions. Concepts and requirements for future such efforts will also be discussed.

Towards human-computer synergetic analysis of large-scale biological data.

PubMed

Singh, Rahul; Yang, Hui; Dalziel, Ben; Asarnow, Daniel; Murad, William; Foote, David; Gormley, Matthew; Stillman, Jonathan; Fisher, Susan

2013-01-01

Advances in technology have led to the generation of massive amounts of complex and multifarious biological data in areas ranging from genomics to structural biology. The volume and complexity of such data leads to significant challenges in terms of its analysis, especially when one seeks to generate hypotheses or explore the underlying biological processes. At the state-of-the-art, the application of automated algorithms followed by perusal and analysis of the results by an expert continues to be the predominant paradigm for analyzing biological data. This paradigm works well in many problem domains. However, it also is limiting, since domain experts are forced to apply their instincts and expertise such as contextual reasoning, hypothesis formulation, and exploratory analysis after the algorithm has produced its results. In many areas where the organization and interaction of the biological processes is poorly understood and exploratory analysis is crucial, what is needed is to integrate domain expertise during the data analysis process and use it to drive the analysis itself. In context of the aforementioned background, the results presented in this paper describe advancements along two methodological directions. First, given the context of biological data, we utilize and extend a design approach called experiential computing from multimedia information system design. This paradigm combines information visualization and human-computer interaction with algorithms for exploratory analysis of large-scale and complex data. In the proposed approach, emphasis is laid on: (1) allowing users to directly visualize, interact, experience, and explore the data through interoperable visualization-based and algorithmic components, (2) supporting unified query and presentation spaces to facilitate experimentation and exploration, (3) providing external contextual information by assimilating relevant supplementary data, and (4) encouraging user-directed information visualization, data exploration, and hypotheses formulation. Second, to illustrate the proposed design paradigm and measure its efficacy, we describe two prototype web applications. The first, called XMAS (Experiential Microarray Analysis System) is designed for analysis of time-series transcriptional data. The second system, called PSPACE (Protein Space Explorer) is designed for holistic analysis of structural and structure-function relationships using interactive low-dimensional maps of the protein structure space. Both these systems promote and facilitate human-computer synergy, where cognitive elements such as domain knowledge, contextual reasoning, and purpose-driven exploration, are integrated with a host of powerful algorithmic operations that support large-scale data analysis, multifaceted data visualization, and multi-source information integration. The proposed design philosophy, combines visualization, algorithmic components and cognitive expertise into a seamless processing-analysis-exploration framework that facilitates sense-making, exploration, and discovery. Using XMAS, we present case studies that analyze transcriptional data from two highly complex domains: gene expression in the placenta during human pregnancy and reaction of marine organisms to heat stress. With PSPACE, we demonstrate how complex structure-function relationships can be explored. These results demonstrate the novelty, advantages, and distinctions of the proposed paradigm. Furthermore, the results also highlight how domain insights can be combined with algorithms to discover meaningful knowledge and formulate evidence-based hypotheses during the data analysis process. Finally, user studies against comparable systems indicate that both XMAS and PSPACE deliver results with better interpretability while placing lower cognitive loads on the users. XMAS is available at: http://tintin.sfsu.edu:8080/xmas. PSPACE is available at: http://pspace.info/.

Towards human-computer synergetic analysis of large-scale biological data

PubMed Central

2013-01-01

Background Advances in technology have led to the generation of massive amounts of complex and multifarious biological data in areas ranging from genomics to structural biology. The volume and complexity of such data leads to significant challenges in terms of its analysis, especially when one seeks to generate hypotheses or explore the underlying biological processes. At the state-of-the-art, the application of automated algorithms followed by perusal and analysis of the results by an expert continues to be the predominant paradigm for analyzing biological data. This paradigm works well in many problem domains. However, it also is limiting, since domain experts are forced to apply their instincts and expertise such as contextual reasoning, hypothesis formulation, and exploratory analysis after the algorithm has produced its results. In many areas where the organization and interaction of the biological processes is poorly understood and exploratory analysis is crucial, what is needed is to integrate domain expertise during the data analysis process and use it to drive the analysis itself. Results In context of the aforementioned background, the results presented in this paper describe advancements along two methodological directions. First, given the context of biological data, we utilize and extend a design approach called experiential computing from multimedia information system design. This paradigm combines information visualization and human-computer interaction with algorithms for exploratory analysis of large-scale and complex data. In the proposed approach, emphasis is laid on: (1) allowing users to directly visualize, interact, experience, and explore the data through interoperable visualization-based and algorithmic components, (2) supporting unified query and presentation spaces to facilitate experimentation and exploration, (3) providing external contextual information by assimilating relevant supplementary data, and (4) encouraging user-directed information visualization, data exploration, and hypotheses formulation. Second, to illustrate the proposed design paradigm and measure its efficacy, we describe two prototype web applications. The first, called XMAS (Experiential Microarray Analysis System) is designed for analysis of time-series transcriptional data. The second system, called PSPACE (Protein Space Explorer) is designed for holistic analysis of structural and structure-function relationships using interactive low-dimensional maps of the protein structure space. Both these systems promote and facilitate human-computer synergy, where cognitive elements such as domain knowledge, contextual reasoning, and purpose-driven exploration, are integrated with a host of powerful algorithmic operations that support large-scale data analysis, multifaceted data visualization, and multi-source information integration. Conclusions The proposed design philosophy, combines visualization, algorithmic components and cognitive expertise into a seamless processing-analysis-exploration framework that facilitates sense-making, exploration, and discovery. Using XMAS, we present case studies that analyze transcriptional data from two highly complex domains: gene expression in the placenta during human pregnancy and reaction of marine organisms to heat stress. With PSPACE, we demonstrate how complex structure-function relationships can be explored. These results demonstrate the novelty, advantages, and distinctions of the proposed paradigm. Furthermore, the results also highlight how domain insights can be combined with algorithms to discover meaningful knowledge and formulate evidence-based hypotheses during the data analysis process. Finally, user studies against comparable systems indicate that both XMAS and PSPACE deliver results with better interpretability while placing lower cognitive loads on the users. XMAS is available at: http://tintin.sfsu.edu:8080/xmas. PSPACE is available at: http://pspace.info/. PMID:24267485

Structure and formation of ant transportation networks

PubMed Central

Latty, Tanya; Ramsch, Kai; Ito, Kentaro; Nakagaki, Toshiyuki; Sumpter, David J. T.; Middendorf, Martin; Beekman, Madeleine

2011-01-01

Many biological systems use extensive networks for the transport of resources and information. Ants are no exception. How do biological systems achieve efficient transportation networks in the absence of centralized control and without global knowledge of the environment? Here, we address this question by studying the formation and properties of inter-nest transportation networks in the Argentine ant (Linepithema humile). We find that the formation of inter-nest networks depends on the number of ants involved in the construction process. When the number of ants is sufficient and networks do form, they tend to have short total length but a low level of robustness. These networks are topologically similar to either minimum spanning trees or Steiner networks. The process of network formation involves an initial construction of multiple links followed by a pruning process that reduces the number of trails. Our study thus illuminates the conditions under and the process by which minimal biological transport networks can be constructed. PMID:21288958

Resolving molecule-specific information in dynamic lipid membrane processes with multi-resonant infrared metasurfaces.

PubMed

Rodrigo, Daniel; Tittl, Andreas; Ait-Bouziad, Nadine; John-Herpin, Aurelian; Limaj, Odeta; Kelly, Christopher; Yoo, Daehan; Wittenberg, Nathan J; Oh, Sang-Hyun; Lashuel, Hilal A; Altug, Hatice

2018-06-04

A multitude of biological processes are enabled by complex interactions between lipid membranes and proteins. To understand such dynamic processes, it is crucial to differentiate the constituent biomolecular species and track their individual time evolution without invasive labels. Here, we present a label-free mid-infrared biosensor capable of distinguishing multiple analytes in heterogeneous biological samples with high sensitivity. Our technology leverages a multi-resonant metasurface to simultaneously enhance the different vibrational fingerprints of multiple biomolecules. By providing up to 1000-fold near-field intensity enhancement over both amide and methylene bands, our sensor resolves the interactions of lipid membranes with different polypeptides in real time. Significantly, we demonstrate that our label-free chemically specific sensor can analyze peptide-induced neurotransmitter cargo release from synaptic vesicle mimics. Our sensor opens up exciting possibilities for gaining new insights into biological processes such as signaling or transport in basic research as well as provides a valuable toolkit for bioanalytical and pharmaceutical applications.

hydropower biological evaluation tools

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

This software is a set of analytical tools to evaluate the physical and biological performance of existing, refurbished, or newly installed conventional hydro-turbines nationwide where fish passage is a regulatory concern. The current version is based on information collected by the Sensor Fish. Future version will include other technologies. The tool set includes data acquisition, data processing, and biological response tools with applications to various turbine designs and other passage alternatives. The associated database is centralized, and can be accessed remotely. We have demonstrated its use for various applications including both turbines and spillways

Process modeling of a HLA research lab

NASA Astrophysics Data System (ADS)

Ribeiro, Bruna G. C.; Sena, Alexandre C.; Silva, Dilson; Marzulo, Leandro A. J.

2017-11-01

Bioinformatics has provided tremendous breakthroughs in the field of molecular biology. All this evolution has generated a large volume of biological data that increasingly require the use of computing for analysis and storage of this information. The identification of the human leukocyte antigen (HLA) genotypes is critical to the success of organ transplants in humans. HLA typing involves not only laboratory tests but also DNA sequencing, with the participation of several professionals responsible for different stages of the process. Thus, the objective of this paper is to map the main steps in HLA typing in a laboratory specialized in performing such procedures, analyzing each process and proposing solutions to speed up the these steps, avoiding mistakes.

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

USGS Publications Warehouse

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

1995-01-01

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

Transient Dissipation and Structural Costs of Physical Information Transduction

NASA Astrophysics Data System (ADS)

Boyd, Alexander B.; Mandal, Dibyendu; Riechers, Paul M.; Crutchfield, James P.

2017-06-01

A central result that arose in applying information theory to the stochastic thermodynamics of nonlinear dynamical systems is the information-processing second law (IPSL): the physical entropy of the Universe can decrease if compensated by the Shannon-Kolmogorov-Sinai entropy change of appropriate information-carrying degrees of freedom. In particular, the asymptotic-rate IPSL precisely delineates the thermodynamic functioning of autonomous Maxwellian demons and information engines. How do these systems begin to function as engines, Landauer erasers, and error correctors? We identify a minimal, and thus inescapable, transient dissipation of physical information processing, which is not captured by asymptotic rates, but is critical to adaptive thermodynamic processes such as those found in biological systems. A component of transient dissipation, we also identify an implementation-dependent cost that varies from one physical substrate to another for the same information processing task. Applying these results to producing structured patterns from a structureless information reservoir, we show that "retrodictive" generators achieve the minimal costs. The results establish the thermodynamic toll imposed by a physical system's structure as it comes to optimally transduce information.

Mathematical manipulative models: in defense of "beanbag biology".

PubMed

Jungck, John R; Gaff, Holly; Weisstein, Anton E

2010-01-01

Mathematical manipulative models have had a long history of influence in biological research and in secondary school education, but they are frequently neglected in undergraduate biology education. By linking mathematical manipulative models in a four-step process-1) use of physical manipulatives, 2) interactive exploration of computer simulations, 3) derivation of mathematical relationships from core principles, and 4) analysis of real data sets-we demonstrate a process that we have shared in biological faculty development workshops led by staff from the BioQUEST Curriculum Consortium over the past 24 yr. We built this approach based upon a broad survey of literature in mathematical educational research that has convincingly demonstrated the utility of multiple models that involve physical, kinesthetic learning to actual data and interactive simulations. Two projects that use this approach are introduced: The Biological Excel Simulations and Tools in Exploratory, Experiential Mathematics (ESTEEM) Project (http://bioquest.org/esteem) and Numerical Undergraduate Mathematical Biology Education (NUMB3R5 COUNT; http://bioquest.org/numberscount). Examples here emphasize genetics, ecology, population biology, photosynthesis, cancer, and epidemiology. Mathematical manipulative models help learners break through prior fears to develop an appreciation for how mathematical reasoning informs problem solving, inference, and precise communication in biology and enhance the diversity of quantitative biology education.

The Legacy of Hobbs and Gray: Research on the Development and Prevention of Conduct Problems.

ERIC Educational Resources Information Center

Dodge, Kenneth A.

1996-01-01

Describes research on the development of chronic conduct problems in childhood and adolescence, examining a multiple risk-factor model that includes biological predispositions, ecological context, family processes, peer influences, academic performance, and social information processing as factors leading to conduct problems. The paper describes a…

Meaning Making: What Reflective Essays Reveal about Biology Students' Conceptions about Natural Selection

ERIC Educational Resources Information Center

Balgopal, Meena M.; Montplaisir, Lisa M.

2011-01-01

The process of reflective writing can play a central role in making meaning as learners process new information and connect it to prior knowledge. An examination of the written discourse can therefore be revealing of learners' cognitive understanding and affective (beliefs, feelings, motivation to learn) responses to concepts. Despite reflective…

Predicting forest successional stages using mutitemporal Landsat imagery with forest inventory and analysis data

Treesearch

Weiguo Liu; Conghe Song; Todd A. Schroeder; Warren B. Cohen

2008-01-01

Forest succession is an important ecological process that has profound biophysical, biological and biogeochemical implications in terrestrial ecosystems. Therefore, information on forest successional stages over an extensive forested landscape is crucial for us to understand ecosystem processes, such as carbon assimilation and energy interception. This study explored...

75 FR 61502 - Cooperative Agreement With the Pan American Health Organization for the Development of an...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-05

... Medical Products and Related Regulatory Processes and Systems in the Americas Region AGENCY: Food and Drug... Health Organization (PAHO) for the development of an information hub in the areas of medical products and related regulatory processes and systems (e.g., including drugs, biologics, vaccines, medical devices, and...

Fluorescence Resonance Energy Transfer-Based Photonic Circuits Using Single-Stranded Tile Self-Assembly and DNA Strand Displacement.

PubMed

Zhang, Xuncai; Ying, Niu; Shen, Chaonan; Cui, Guangzhao

2017-02-01

Structural DNA nanotechnology has great potential in the fabrication of complicated nanostructures and devices capable of bio-sensing and logic function. A variety of nanostructures with desired shapes have been created in the past few decades. But the application of nanostructures remains to be fully studied. Here, we present a novel biological information processing system constructed on a self-assembled, spatially addressable single-stranded tile (SST) nanostructure as DNA nano-manipulation platform that created by SST self-assembly technology. Utilizing DNA strand displacement technology, the fluorescent dye that is pre-assembled in the nano-manipulation platform is transferred from the original position to the destination, which can achieve photonic logic circuits by FRET signal cascades, including logic AND, OR, and NOT gates. And this transfer process is successfully validated by visual DSD software. The transfer process proposed in this study may provide a novel method to design complicated biological information processing system constructed on a SST nanostructure, and can be further used to develop intelligent delivery of drug molecules in vivo.

Dichotomy in the definition of prescriptive information suggests both prescribed data and prescribed algorithms: biosemiotics applications in genomic systems.

PubMed

D'Onofrio, David J; Abel, David L; Johnson, Donald E

2012-03-14

The fields of molecular biology and computer science have cooperated over recent years to create a synergy between the cybernetic and biosemiotic relationship found in cellular genomics to that of information and language found in computational systems. Biological information frequently manifests its "meaning" through instruction or actual production of formal bio-function. Such information is called prescriptive information (PI). PI programs organize and execute a prescribed set of choices. Closer examination of this term in cellular systems has led to a dichotomy in its definition suggesting both prescribed data and prescribed algorithms are constituents of PI. This paper looks at this dichotomy as expressed in both the genetic code and in the central dogma of protein synthesis. An example of a genetic algorithm is modeled after the ribosome, and an examination of the protein synthesis process is used to differentiate PI data from PI algorithms.

Optical properties of dissolved organic matter (DOM): Effects of biological and photolytic degradation

USGS Publications Warehouse

Hansen, Angela; Kraus, Tamara; Pellerin, Brian; Fleck, Jacob; Downing, Bryan D.; Bergamaschi, Brian

2016-01-01

Advances in spectroscopic techniques have led to an increase in the use of optical properties (absorbance and fluorescence) to assess dissolved organic matter (DOM) composition and infer sources and processing. However, little information is available to assess the impact of biological and photolytic processing on the optical properties of original DOM source materials. We measured changes in commonly used optical properties and indices in DOM leached from peat soil, plants, and algae following biological and photochemical degradation to determine whether they provide unique signatures that can be linked to original DOM source. Changes in individual optical parameters varied by source material and process, with biodegradation and photodegradation often causing values to shift in opposite directions. Although values for different source materials overlapped at the end of the 111-day lab experiment, multivariate statistical analyses showed that unique optical signatures could be linked to original DOM source material even after degradation, with 17 optical properties determined by discriminant analysis to be significant (p<0.05) in distinguishing between DOM source and environmental processing. These results demonstrate that inferring the source material from optical properties is possible when parameters are evaluated in combination even after extensive biological and photochemical alteration.

Discovery informatics in biological and biomedical sciences: research challenges and opportunities.

PubMed

Honavar, Vasant

2015-01-01

New discoveries in biological, biomedical and health sciences are increasingly being driven by our ability to acquire, share, integrate and analyze, and construct and simulate predictive models of biological systems. While much attention has focused on automating routine aspects of management and analysis of "big data", realizing the full potential of "big data" to accelerate discovery calls for automating many other aspects of the scientific process that have so far largely resisted automation: identifying gaps in the current state of knowledge; generating and prioritizing questions; designing studies; designing, prioritizing, planning, and executing experiments; interpreting results; forming hypotheses; drawing conclusions; replicating studies; validating claims; documenting studies; communicating results; reviewing results; and integrating results into the larger body of knowledge in a discipline. Against this background, the PSB workshop on Discovery Informatics in Biological and Biomedical Sciences explores the opportunities and challenges of automating discovery or assisting humans in discovery through advances (i) Understanding, formalization, and information processing accounts of, the entire scientific process; (ii) Design, development, and evaluation of the computational artifacts (representations, processes) that embody such understanding; and (iii) Application of the resulting artifacts and systems to advance science (by augmenting individual or collective human efforts, or by fully automating science).

Self-Organized Information Processing in Neuronal Networks: Replacing Layers in Deep Networks by Dynamics

NASA Astrophysics Data System (ADS)

Kirst, Christoph

It is astonishing how the sub-parts of a brain co-act to produce coherent behavior. What are mechanism that coordinate information processing and communication and how can those be changed flexibly in order to cope with variable contexts? Here we show that when information is encoded in the deviations around a collective dynamical reference state of a recurrent network the propagation of these fluctuations is strongly dependent on precisely this underlying reference. Information here 'surfs' on top of the collective dynamics and switching between states enables fast and flexible rerouting of information. This in turn affects local processing and consequently changes in the global reference dynamics that re-regulate the distribution of information. This provides a generic mechanism for self-organized information processing as we demonstrate with an oscillatory Hopfield network that performs contextual pattern recognition. Deep neural networks have proven to be very successful recently. Here we show that generating information channels via collective reference dynamics can effectively compress a deep multi-layer architecture into a single layer making this mechanism a promising candidate for the organization of information processing in biological neuronal networks.

BioCore Guide: A Tool for Interpreting the Core Concepts of Vision and Change for Biology Majors

PubMed Central

Freeman, Scott; Wenderoth, Mary Pat; Crowe, Alison J.

2014-01-01

Vision and Change in Undergraduate Biology Education outlined five core concepts intended to guide undergraduate biology education: 1) evolution; 2) structure and function; 3) information flow, exchange, and storage; 4) pathways and transformations of energy and matter; and 5) systems. We have taken these general recommendations and created a Vision and Change BioCore Guide—a set of general principles and specific statements that expand upon the core concepts, creating a framework that biology departments can use to align with the goals of Vision and Change. We used a grassroots approach to generate the BioCore Guide, beginning with faculty ideas as the basis for an iterative process that incorporated feedback from more than 240 biologists and biology educators at a diverse range of academic institutions throughout the United States. The final validation step in this process demonstrated strong national consensus, with more than 90% of respondents agreeing with the importance and scientific accuracy of the statements. It is our hope that the BioCore Guide will serve as an agent of change for biology departments as we move toward transforming undergraduate biology education. PMID:26086653

Biocuration at the Saccharomyces genome database.

PubMed

Skrzypek, Marek S; Nash, Robert S

2015-08-01

Saccharomyces Genome Database is an online resource dedicated to managing information about the biology and genetics of the model organism, yeast (Saccharomyces cerevisiae). This information is derived primarily from scientific publications through a process of human curation that involves manual extraction of data and their organization into a comprehensive system of knowledge. This system provides a foundation for further analysis of experimental data coming from research on yeast as well as other organisms. In this review we will demonstrate how biocuration and biocurators add a key component, the biological context, to our understanding of how genes, proteins, genomes and cells function and interact. We will explain the role biocurators play in sifting through the wealth of biological data to incorporate and connect key information. We will also discuss the many ways we assist researchers with their various research needs. We hope to convince the reader that manual curation is vital in converting the flood of data into organized and interconnected knowledge, and that biocurators play an essential role in the integration of scientific information into a coherent model of the cell. © 2015 Wiley Periodicals, Inc.

Biocuration at the Saccharomyces Genome Database

PubMed Central

Skrzypek, Marek S.; Nash, Robert S.

2015-01-01

Saccharomyces Genome Database is an online resource dedicated to managing information about the biology and genetics of the model organism, yeast (Saccharomyces cerevisiae). This information is derived primarily from scientific publications through a process of human curation that involves manual extraction of data and their organization into a comprehensive system of knowledge. This system provides a foundation for further analysis of experimental data coming from research on yeast as well as other organisms. In this review we will demonstrate how biocuration and biocurators add a key component, the biological context, to our understanding of how genes, proteins, genomes and cells function and interact. We will explain the role biocurators play in sifting through the wealth of biological data to incorporate and connect key information. We will also discuss the many ways we assist researchers with their various research needs. We hope to convince the reader that manual curation is vital in converting the flood of data into organized and interconnected knowledge, and that biocurators play an essential role in the integration of scientific information into a coherent model of the cell. PMID:25997651

MOPED enables discoveries through consistently processed proteomics data

PubMed Central

Higdon, Roger; Stewart, Elizabeth; Stanberry, Larissa; Haynes, Winston; Choiniere, John; Montague, Elizabeth; Anderson, Nathaniel; Yandl, Gregory; Janko, Imre; Broomall, William; Fishilevich, Simon; Lancet, Doron; Kolker, Natali; Kolker, Eugene

2014-01-01

The Model Organism Protein Expression Database (MOPED, http://moped.proteinspire.org), is an expanding proteomics resource to enable biological and biomedical discoveries. MOPED aggregates simple, standardized and consistently processed summaries of protein expression and metadata from proteomics (mass spectrometry) experiments from human and model organisms (mouse, worm and yeast). The latest version of MOPED adds new estimates of protein abundance and concentration, as well as relative (differential) expression data. MOPED provides a new updated query interface that allows users to explore information by organism, tissue, localization, condition, experiment, or keyword. MOPED supports the Human Proteome Project’s efforts to generate chromosome and diseases specific proteomes by providing links from proteins to chromosome and disease information, as well as many complementary resources. MOPED supports a new omics metadata checklist in order to harmonize data integration, analysis and use. MOPED’s development is driven by the user community, which spans 90 countries guiding future development that will transform MOPED into a multi-omics resource. MOPED encourages users to submit data in a simple format. They can use the metadata a checklist generate a data publication for this submission. As a result, MOPED will provide even greater insights into complex biological processes and systems and enable deeper and more comprehensive biological and biomedical discoveries. PMID:24350770

Lost at sea: ocean acidification undermines larval fish orientation via altered hearing and marine soundscape modification

PubMed Central

Rossi, Tullio; Nagelkerken, Ivan; Connell, Sean D.

2016-01-01

The dispersal of larvae and their settlement to suitable habitat is fundamental to the replenishment of marine populations and the communities in which they live. Sound plays an important role in this process because for larvae of various species, it acts as an orientational cue towards suitable settlement habitat. Because marine sounds are largely of biological origin, they not only carry information about the location of potential habitat, but also information about the quality of habitat. While ocean acidification is known to affect a wide range of marine organisms and processes, its effect on marine soundscapes and its reception by navigating oceanic larvae remains unknown. Here, we show that ocean acidification causes a switch in role of present-day soundscapes from attractor to repellent in the auditory preferences in a temperate larval fish. Using natural CO2 vents as analogues of future ocean conditions, we further reveal that ocean acidification can impact marine soundscapes by profoundly diminishing their biological sound production. An altered soundscape poorer in biological cues indirectly penalizes oceanic larvae at settlement stage because both control and CO2-treated fish larvae showed lack of any response to such future soundscapes. These indirect and direct effects of ocean acidification put at risk the complex processes of larval dispersal and settlement. PMID:26763221

Developing and establishing bee species as crop pollinators: the example of Osmia spp. (Hymenoptera: Megachilidae) and fruit trees.

PubMed

Bosch, J; Bosch, J; Kemp, W P

2002-02-01

The development of a bee species as a new crop pollinator starts with the identification of a pollination-limited crop production deficit and the selection of one or more candidate pollinator species. The process continues with a series of studies on the developmental biology, pollinating efficacy, nesting behaviour, preference for different nesting substrates, and population dynamics of the candidate pollinator. Parallel studies investigate the biology of parasites, predators and pathogens. The information gained in these studies is combined with information on the reproductive biology of the crop to design a management system. Complete management systems should provide guidelines on rearing and releasing methods, bee densities required for adequate pollination, nesting materials, and control against parasites, predators and pathogens. Management systems should also provide methods to ensure a reliable pollinator supply. Pilot tests on a commercial scale are then conducted to test and eventually refine the management system. The process culminates with the delivery of a viable system to manage and sustain the new pollinator on a commercial scale. The process is illustrated by the development of three mason bees, Osmia cornifrons (Radoszkowski), O. lignaria Say and O. cornuta (Latreille) as orchard pollinators in Japan, the USA and Europe, respectively.

Weighted similarity-based clustering of chemical structures and bioactivity data in early drug discovery.

PubMed

Perualila-Tan, Nolen Joy; Shkedy, Ziv; Talloen, Willem; Göhlmann, Hinrich W H; Moerbeke, Marijke Van; Kasim, Adetayo

2016-08-01

The modern process of discovering candidate molecules in early drug discovery phase includes a wide range of approaches to extract vital information from the intersection of biology and chemistry. A typical strategy in compound selection involves compound clustering based on chemical similarity to obtain representative chemically diverse compounds (not incorporating potency information). In this paper, we propose an integrative clustering approach that makes use of both biological (compound efficacy) and chemical (structural features) data sources for the purpose of discovering a subset of compounds with aligned structural and biological properties. The datasets are integrated at the similarity level by assigning complementary weights to produce a weighted similarity matrix, serving as a generic input in any clustering algorithm. This new analysis work flow is semi-supervised method since, after the determination of clusters, a secondary analysis is performed wherein it finds differentially expressed genes associated to the derived integrated cluster(s) to further explain the compound-induced biological effects inside the cell. In this paper, datasets from two drug development oncology projects are used to illustrate the usefulness of the weighted similarity-based clustering approach to integrate multi-source high-dimensional information to aid drug discovery. Compounds that are structurally and biologically similar to the reference compounds are discovered using this proposed integrative approach.

76 FR 66311 - Draft Documents To Support Submission of an Electronic Common Technical Document; Availability

Federal Register 2010, 2011, 2012, 2013, 2014

2011-10-26

.../DevelopmentApprovalProcess/FormsSubmissionRequirements/ElectronicSubmissions/ucm253101.htm , http://www.fda.gov/BiologicsBloodVaccines/GuidanceComplianceRegulatoryInformation/Guidances/default.htm , or http...

"Chemical transformers" from nanoparticle ensembles operated with logic.

PubMed

Motornov, Mikhail; Zhou, Jian; Pita, Marcos; Gopishetty, Venkateshwarlu; Tokarev, Ihor; Katz, Evgeny; Minko, Sergiy

2008-09-01

The pH-responsive nanoparticles were coupled with information-processing enzyme-based systems to yield "smart" signal-responsive hybrid systems with built-in Boolean logic. The enzyme systems performed AND/OR logic operations, transducing biochemical input signals into reversible structural changes (signal-directed self-assembly) of the nanoparticle assemblies, thus resulting in the processing and amplification of the biochemical signals. The hybrid system mimics biological systems in effective processing of complex biochemical information, resulting in reversible changes of the self-assembled structures of the nanoparticles. The bioinspired approach to the nanostructured morphing materials could be used in future self-assembled molecular robotic systems.

An Information Storage and Retrieval System for Biological and Geological Data. Interim Report.

ERIC Educational Resources Information Center

Squires, Donald F.

A project is being conducted to test the feasibility of an information storage and retrieval system for museum specimen data, particularly for natural history museums. A pilot data processing system has been developed, with the specimen records from the national collections of birds, marine crustaceans, and rocks used as sample data. The research…

Trends in fluorescence imaging and related techniques to unravel biological information.

PubMed

Haustein, Elke; Schwille, Petra

2007-09-01

Optical microscopy is among the most powerful tools that the physical sciences have ever provided biology. It is indispensable for basic lab work, as well as for cutting edge research, as the visual monitoring of life processes still belongs to the most compelling evidences for a multitude of biomedical applications. Along with the rapid development of new probes and methods for the analysis of laser induced fluorescence, optical microscopy over past years experienced a vast increase of both new techniques and novel combinations of established methods to study biological processes with unprecedented spatial and temporal precision. On the one hand, major technical advances have significantly improved spatial resolution. On the other hand, life scientists are moving toward three- and even four-dimensional cell biology and biophysics involving time as a crucial coordinate to quantitatively understand living specimen. Monitoring the whole cell or tissue in real time, rather than producing snap-shot-like two-dimensional projections, will enable more physiological and, thus, more clinically relevant experiments, whereas an increase in temporal resolution facilitates monitoring fast nonperiodic processes as well as the quantitative analysis of characteristic dynamics.

Trends in fluorescence imaging and related techniques to unravel biological information

PubMed Central

Haustein, Elke; Schwille, Petra

2007-01-01

Optical microscopy is among the most powerful tools that the physical sciences have ever provided biology. It is indispensable for basic lab work, as well as for cutting edge research, as the visual monitoring of life processes still belongs to the most compelling evidences for a multitude of biomedical applications. Along with the rapid development of new probes and methods for the analysis of laser induced fluorescence, optical microscopy over past years experienced a vast increase of both new techniques and novel combinations of established methods to study biological processes with unprecedented spatial and temporal precision. On the one hand, major technical advances have significantly improved spatial resolution. On the other hand, life scientists are moving toward three- and even four-dimensional cell biology and biophysics involving time as a crucial coordinate to quantitatively understand living specimen. Monitoring the whole cell or tissue in real time, rather than producing snap-shot-like two-dimensional projections, will enable more physiological and, thus, more clinically relevant experiments, whereas an increase in temporal resolution facilitates monitoring fast nonperiodic processes as well as the quantitative analysis of characteristic dynamics. PMID:19404444

Neural systems for preparatory control of imitation.

PubMed

Cross, Katy A; Iacoboni, Marco

2014-01-01

Humans have an automatic tendency to imitate others. Previous studies on how we control these tendencies have focused on reactive mechanisms, where inhibition of imitation is implemented after seeing an action. This work suggests that reactive control of imitation draws on at least partially specialized mechanisms. Here, we examine preparatory imitation control, where advance information allows control processes to be employed before an action is observed. Drawing on dual route models from the spatial compatibility literature, we compare control processes using biological and non-biological stimuli to determine whether preparatory imitation control recruits specialized neural systems that are similar to those observed in reactive imitation control. Results indicate that preparatory control involves anterior prefrontal, dorsolateral prefrontal, posterior parietal and early visual cortices regardless of whether automatic responses are evoked by biological (imitative) or non-biological stimuli. These results indicate both that preparatory control of imitation uses general mechanisms, and that preparatory control of imitation draws on different neural systems from reactive imitation control. Based on the regions involved, we hypothesize that preparatory control is implemented through top-down attentional biasing of visual processing.

Markov Chain-Like Quantum Biological Modeling of Mutations, Aging, and Evolution.

PubMed

Djordjevic, Ivan B

2015-08-24

Recent evidence suggests that quantum mechanics is relevant in photosynthesis, magnetoreception, enzymatic catalytic reactions, olfactory reception, photoreception, genetics, electron-transfer in proteins, and evolution; to mention few. In our recent paper published in Life, we have derived the operator-sum representation of a biological channel based on codon basekets, and determined the quantum channel model suitable for study of the quantum biological channel capacity. However, this model is essentially memoryless and it is not able to properly model the propagation of mutation errors in time, the process of aging, and evolution of genetic information through generations. To solve for these problems, we propose novel quantum mechanical models to accurately describe the process of creation spontaneous, induced, and adaptive mutations and their propagation in time. Different biological channel models with memory, proposed in this paper, include: (i) Markovian classical model, (ii) Markovian-like quantum model, and (iii) hybrid quantum-classical model. We then apply these models in a study of aging and evolution of quantum biological channel capacity through generations. We also discuss key differences of these models with respect to a multilevel symmetric channel-based Markovian model and a Kimura model-based Markovian process. These models are quite general and applicable to many open problems in biology, not only biological channel capacity, which is the main focus of the paper. We will show that the famous quantum Master equation approach, commonly used to describe different biological processes, is just the first-order approximation of the proposed quantum Markov chain-like model, when the observation interval tends to zero. One of the important implications of this model is that the aging phenotype becomes determined by different underlying transition probabilities in both programmed and random (damage) Markov chain-like models of aging, which are mutually coupled.

Markov Chain-Like Quantum Biological Modeling of Mutations, Aging, and Evolution

PubMed Central

Djordjevic, Ivan B.

2015-01-01

Recent evidence suggests that quantum mechanics is relevant in photosynthesis, magnetoreception, enzymatic catalytic reactions, olfactory reception, photoreception, genetics, electron-transfer in proteins, and evolution; to mention few. In our recent paper published in Life, we have derived the operator-sum representation of a biological channel based on codon basekets, and determined the quantum channel model suitable for study of the quantum biological channel capacity. However, this model is essentially memoryless and it is not able to properly model the propagation of mutation errors in time, the process of aging, and evolution of genetic information through generations. To solve for these problems, we propose novel quantum mechanical models to accurately describe the process of creation spontaneous, induced, and adaptive mutations and their propagation in time. Different biological channel models with memory, proposed in this paper, include: (i) Markovian classical model, (ii) Markovian-like quantum model, and (iii) hybrid quantum-classical model. We then apply these models in a study of aging and evolution of quantum biological channel capacity through generations. We also discuss key differences of these models with respect to a multilevel symmetric channel-based Markovian model and a Kimura model-based Markovian process. These models are quite general and applicable to many open problems in biology, not only biological channel capacity, which is the main focus of the paper. We will show that the famous quantum Master equation approach, commonly used to describe different biological processes, is just the first-order approximation of the proposed quantum Markov chain-like model, when the observation interval tends to zero. One of the important implications of this model is that the aging phenotype becomes determined by different underlying transition probabilities in both programmed and random (damage) Markov chain-like models of aging, which are mutually coupled. PMID:26305258

The Physics of Open Ended Evolution

NASA Astrophysics Data System (ADS)

Adams, Alyssa M.

What makes living systems different than non-living ones? Unfortunately this question is impossible to answer, at least currently. Instead, we must face computationally tangible questions based on our current understanding of physics, computation, information, and biology. Yet we have few insights into how living systems might quantifiably differ from their non-living counterparts, as in a mathematical foundation to explain away our observations of biological evolution, emergence, innovation, and organization. The development of a theory of living systems, if at all possible, demands a mathematical understanding of how data generated by complex biological systems changes over time. In addition, this theory ought to be broad enough as to not be constrained to an Earth-based biochemistry. In this dissertation, the philosophy of studying living systems from the perspective of traditional physics is first explored as a motivating discussion for subsequent research. Traditionally, we have often thought of the physical world from a bottom-up approach: things happening on a smaller scale aggregate into things happening on a larger scale. In addition, the laws of physics are generally considered static over time. Research suggests that biological evolution may follow dynamic laws that (at least in part) change as a function of the state of the system. Of the three featured research projects, cellular automata (CA) are used as a model to study certain aspects of living systems in two of them. These aspects include self-reference, open-ended evolution, local physical universality, subjectivity, and information processing. Open-ended evolution and local physical universality are attributed to the vast amount of innovation observed throughout biological evolution. Biological systems may distinguish themselves in terms of information processing and storage, not outside the theory of computation. The final research project concretely explores real-world phenomenon by means of mapping dominance hierarchies in the evolution of video game strategies. Though the main question of how life differs from non-life remains unanswered, the mechanisms behind open-ended evolution and physical universality are revealed.

1H NMR-based metabolic profiling for evaluating poppy seed rancidity and brewing.

PubMed

Jawień, Ewa; Ząbek, Adam; Deja, Stanisław; Łukaszewicz, Marcin; Młynarz, Piotr

2015-12-01

Poppy seeds are widely used in household and commercial confectionery. The aim of this study was to demonstrate the application of metabolic profiling for industrial monitoring of the molecular changes which occur during minced poppy seed rancidity and brewing processes performed on raw seeds. Both forms of poppy seeds were obtained from a confectionery company. Proton nuclear magnetic resonance (1H NMR) was applied as the analytical method of choice together with multivariate statistical data analysis. Metabolic fingerprinting was applied as a bioprocess control tool to monitor rancidity with the trajectory of change and brewing progressions. Low molecular weight compounds were found to be statistically significant biomarkers of these bioprocesses. Changes in concentrations of chemical compounds were explained relative to the biochemical processes and external conditions. The obtained results provide valuable and comprehensive information to gain a better understanding of the biology of rancidity and brewing processes, while demonstrating the potential for applying NMR spectroscopy combined with multivariate data analysis tools for quality control in food industries involved in the processing of oilseeds. This precious and versatile information gives a better understanding of the biology of these processes.

MIMO: an efficient tool for molecular interaction maps overlap

PubMed Central

2013-01-01

Background Molecular pathways represent an ensemble of interactions occurring among molecules within the cell and between cells. The identification of similarities between molecular pathways across organisms and functions has a critical role in understanding complex biological processes. For the inference of such novel information, the comparison of molecular pathways requires to account for imperfect matches (flexibility) and to efficiently handle complex network topologies. To date, these characteristics are only partially available in tools designed to compare molecular interaction maps. Results Our approach MIMO (Molecular Interaction Maps Overlap) addresses the first problem by allowing the introduction of gaps and mismatches between query and template pathways and permits -when necessary- supervised queries incorporating a priori biological information. It then addresses the second issue by relying directly on the rich graph topology described in the Systems Biology Markup Language (SBML) standard, and uses multidigraphs to efficiently handle multiple queries on biological graph databases. The algorithm has been here successfully used to highlight the contact point between various human pathways in the Reactome database. Conclusions MIMO offers a flexible and efficient graph-matching tool for comparing complex biological pathways. PMID:23672344

Effects of Exposure to Microwaves: Problems and Perspectives*

PubMed Central

Michaelson, Sol M.

1974-01-01

During the last 25 years, there has been a remarkable development and increase in the number of processes and devices that utilize or emit microwaves. Such devices are used in all sectors of our society for military, industrial, telecommunications, and consumer applications. Although there is information on biologic effects and potential hazard to man from exposure to microwaves, considerable confusion and misinformation has permeated not only the public press but also some scientific and technical publications. The purpose of this review is to place the available information on biologic effects of microwaves in proper perspective and to suggest approaches to future studies. PMID:4620329

Action verbs are processed differently in metaphorical and literal sentences depending on the semantic match of visual primes

PubMed Central

Troyer, Melissa; Curley, Lauren B.; Miller, Luke E.; Saygin, Ayse P.; Bergen, Benjamin K.

2014-01-01

Language comprehension requires rapid and flexible access to information stored in long-term memory, likely influenced by activation of rich world knowledge and by brain systems that support the processing of sensorimotor content. We hypothesized that while literal language about biological motion might rely on neurocognitive representations of biological motion specific to the details of the actions described, metaphors rely on more generic representations of motion. In a priming and self-paced reading paradigm, participants saw video clips or images of (a) an intact point-light walker or (b) a scrambled control and read sentences containing literal or metaphoric uses of biological motion verbs either closely or distantly related to the depicted action (walking). We predicted that reading times for literal and metaphorical sentences would show differential sensitivity to the match between the verb and the visual prime. In Experiment 1, we observed interactions between the prime type (walker or scrambled video) and the verb type (close or distant match) for both literal and metaphorical sentences, but with strikingly different patterns. We found no difference in the verb region of literal sentences for Close-Match verbs after walker or scrambled motion primes, but Distant-Match verbs were read more quickly following walker primes. For metaphorical sentences, the results were roughly reversed, with Distant-Match verbs being read more slowly following a walker compared to scrambled motion. In Experiment 2, we observed a similar pattern following still image primes, though critical interactions emerged later in the sentence. We interpret these findings as evidence for shared recruitment of cognitive and neural mechanisms for processing visual and verbal biological motion information. Metaphoric language using biological motion verbs may recruit neurocognitive mechanisms similar to those used in processing literal language but be represented in a less-specific way. PMID:25538604

Some ozone advanced oxidation processes to improve the biological removal of selected pharmaceutical contaminants from urban wastewater.

PubMed

Espejo, Azahara; Aguinaco, Almudena; Amat, Ana M; Beltrán, Fernando J

2014-01-01

Removal of nine pharmaceutical compounds--acetaminophen (AAF), antipyrine (ANT), caffeine (CAF), carbamazepine (CRB), diclofenac (DCF), hydrochlorothiazide (HCT), ketorolac (KET), metoprolol (MET) and sulfamethoxazole (SMX)-spiked in a primary sedimentation effluent of a municipal wastewater has been studied with sequential aerobic biological and ozone advanced oxidation systems. Combinations of ozone, UVA black light and Fe(III) or Fe3O4 constituted the chemical systems. During the biological treatment (hydraulic residence time, HRT = 24 h), only AAF and CAF were completely eliminated, MET, SMX and HCT reached partial removal rates and the rest of compounds were completely refractory. With any ozone advanced oxidation process applied, the remaining pharmaceuticals disappear in less than 10 min. Fe3O4 or Fe(III) photocatalytic ozonation leads to 35% mineralization compared to 13% reached during ozonation alone after about 30-min reaction. Also, biodegradability of the treated wastewater increased 50% in the biological process plus another 150% after the ozonation processes. Both untreated and treated wastewater was non-toxic for Daphnia magna (D. magna) except when Fe(III) was used in photocatalytic ozonation. In this case, toxicity was likely due to the ferryoxalate formed in the process. Kinetic information on ozone processes reveals that pharmaceuticals at concentrations they have in urban wastewater are mainly removed through free radical oxidation.

Protein-protein interaction predictions using text mining methods.

PubMed

Papanikolaou, Nikolas; Pavlopoulos, Georgios A; Theodosiou, Theodosios; Iliopoulos, Ioannis

2015-03-01

It is beyond any doubt that proteins and their interactions play an essential role in most complex biological processes. The understanding of their function individually, but also in the form of protein complexes is of a great importance. Nowadays, despite the plethora of various high-throughput experimental approaches for detecting protein-protein interactions, many computational methods aiming to predict new interactions have appeared and gained interest. In this review, we focus on text-mining based computational methodologies, aiming to extract information for proteins and their interactions from public repositories such as literature and various biological databases. We discuss their strengths, their weaknesses and how they complement existing experimental techniques by simultaneously commenting on the biological databases which hold such information and the benchmark datasets that can be used for evaluating new tools. Copyright © 2014 Elsevier Inc. All rights reserved.

Alteration processes of alkenones and related lipids in water columns and sediments

NASA Astrophysics Data System (ADS)

Harvey, H. Rodger

2000-08-01

Alkenones produced by the haptophyte algae are currently being used as indices of sea surface temperature in recent and past ocean environments, but limited information is available concerning the impact of biotic and abiotic processes on the integrity of these long chain lipids. This synthesis provides selected background information on major alteration processes that must be considered before such indices can be used with confidence. A number of processes in the water column and surface sediments have the potential to impact the structural integrity of alkenones and compromise their ability as temperature markers. Processes discussed include the alteration of alkenone structure during early diagenesis, direct biotic and abiotic impacts, and the effect of digestive processes by grazers. Current literature suggests that despite substantial changes in concentration from biological processing, the temperature signal is preserved. For each of these processes, information on the integrity of the alkenone isotopic signature is also needed and limited information available is reviewed. In addition to the alkenones, related lipids including the long chain alkadienes and akyl alkenoates that might serve as ancillary markers are discussed.

QUANTITATIVE PROCEDURES FOR NEUROTOXICOLOGY RISK ASSESSMENT

EPA Science Inventory

In this project, previously published information on biologically based dose-response model for brain development was used to quantitatively evaluate critical neurodevelopmental processes, and to assess potential chemical impacts on early brain development. This model has been ex...

Exploring the Cause of English Pronoun Gender Errors by Chinese Learners of English: Evidence from the Self-paced Reading Paradigm.

PubMed

Dong, Yanping; Wen, Yun; Zeng, Xiaomeng; Ji, Yifei

2015-12-01

To locate the underlying cause of biological gender errors of oral English pronouns by proficient Chinese-English learners, two self-paced reading experiments were conducted to explore whether the reading time for each 'he' or 'she' that matched its antecedent was shorter than that in the corresponding mismatch situation, as with native speakers of English. The critical manipulation was to see whether highlighting the gender information of an antecedent with a human picture would make a difference. The results indicate that such manipulation did make a difference. Since oral Chinese does not distinguish 'he' and 'she', the findings suggest that Chinese speakers probably do not usually process biological gender for linguistic purposes and the mixed use of 'he' and 'she' is probably a result of deficient processing of gender information in the conceptualizer. Theoretical and pedagogical implications are discussed.

Global, quantitative and dynamic mapping of protein subcellular localization.

PubMed

Itzhak, Daniel N; Tyanova, Stefka; Cox, Jürgen; Borner, Georg Hh

2016-06-09

Subcellular localization critically influences protein function, and cells control protein localization to regulate biological processes. We have developed and applied Dynamic Organellar Maps, a proteomic method that allows global mapping of protein translocation events. We initially used maps statically to generate a database with localization and absolute copy number information for over 8700 proteins from HeLa cells, approaching comprehensive coverage. All major organelles were resolved, with exceptional prediction accuracy (estimated at >92%). Combining spatial and abundance information yielded an unprecedented quantitative view of HeLa cell anatomy and organellar composition, at the protein level. We subsequently demonstrated the dynamic capabilities of the approach by capturing translocation events following EGF stimulation, which we integrated into a quantitative model. Dynamic Organellar Maps enable the proteome-wide analysis of physiological protein movements, without requiring any reagents specific to the investigated process, and will thus be widely applicable in cell biology.

Promoting a structural view of biology for varied audiences: an overview of RCSB PDB resources and experiences

PubMed Central

Dutta, Shuchismita; Zardecki, Christine; Goodsell, David S.; Berman, Helen M.

2010-01-01

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) supports scientific research and education worldwide by providing an essential resource of information on biomolecular structures. In addition to serving as a deposition, data-processing and distribution center for PDB data, the RCSB PDB offers resources and online materials that different audiences can use to customize their structural biology instruction. These include resources for general audiences that present macromolecular structure in the context of a biological theme, method-based materials for researchers who take a more traditional approach to the presentation of structural science, and materials that mix theme-based and method-based approaches for educators and students. Through these efforts the RCSB PDB aims to enable optimal use of structural data by researchers, educators and students designing and understanding experiments in biology, chemistry and medicine, and by general users making informed decisions about their life and health. PMID:20877496

Scaling up: human genetics as a Cold War network.

PubMed

Lindee, Susan

2014-09-01

In this commentary I explore how the papers here illuminate the processes of collection that have been so central to the history of human genetics since 1945. The development of human population genetics in the Cold War period produced databases and biobanks that have endured into the present, and that continue to be used and debated. In the decades after the bomb, scientists collected and transferred human biological materials and information from populations of interest, and as they moved these biological resources or biosocial resources acquired new meanings and uses. The papers here collate these practices and map their desires and ironies. They explore how a large international network of geneticists, biological anthropologists, virologists and other physicians and scientists interacted with local informants, research subjects and public officials. They also track the networks and standards that mobilized the transfer of information, genealogies, tissue and blood samples. As Joanna Radin suggests here, the massive collections of human biological materials and data were often understood to be resources for an "as-yet-unknown" future. The stories told here contain elements of surveillance, extraction, salvage and eschatology. Copyright © 2014 Elsevier Ltd. All rights reserved.

Quantifying control effort of biological and technical movements: an information-entropy-based approach.

PubMed

Haeufle, D F B; Günther, M; Wunner, G; Schmitt, S

2014-01-01

In biomechanics and biorobotics, muscles are often associated with reduced movement control effort and simplified control compared to technical actuators. This is based on evidence that the nonlinear muscle properties positively influence movement control. It is, however, open how to quantify the simplicity aspect of control effort and compare it between systems. Physical measures, such as energy consumption, stability, or jerk, have already been applied to compare biological and technical systems. Here a physical measure of control effort based on information entropy is presented. The idea is that control is simpler if a specific movement is generated with less processed sensor information, depending on the control scheme and the physical properties of the systems being compared. By calculating the Shannon information entropy of all sensor signals required for control, an information cost function can be formulated allowing the comparison of models of biological and technical control systems. Exemplarily applied to (bio-)mechanical models of hopping, the method reveals that the required information for generating hopping with a muscle driven by a simple reflex control scheme is only I=32 bits versus I=660 bits with a DC motor and a proportional differential controller. This approach to quantifying control effort captures the simplicity of a control scheme and can be used to compare completely different actuators and control approaches.

Publications of the planetary biology program for 1976: A special bibliography

NASA Technical Reports Server (NTRS)

Bradley, F. D. (Compiler); Young, R. S. (Compiler)

1977-01-01

An annual listing of current publications resulting from research pursued under the auspices of NASA's Planetary Biology Program is presented. To stimulate the exchange of information and ideas among scientists working in the different areas of the program. To facilitate the exchange process. The author of each publication who is presently participating in the program is identified by asterisk. Current addresses for all principal investigators are given in the appendix.

On Roles of Models in Information Systems

NASA Astrophysics Data System (ADS)

Sølvberg, Arne

The increasing penetration of computers into all aspects of human activity makes it desirable that the interplay among software, data and the domains where computers are applied is made more transparent. An approach to this end is to explicitly relate the modeling concepts of the domains, e.g., natural science, technology and business, to the modeling concepts of software and data. This may make it simpler to build comprehensible integrated models of the interactions between computers and non-computers, e.g., interaction among computers, people, physical processes, biological processes, and administrative processes. This chapter contains an analysis of various facets of the modeling environment for information systems engineering. The lack of satisfactory conceptual modeling tools seems to be central to the unsatisfactory state-of-the-art in establishing information systems. The chapter contains a proposal for defining a concept of information that is relevant to information systems engineering.

Emergence of Coding and its Specificity as a Physico-Informatic Problem

NASA Astrophysics Data System (ADS)

Wills, Peter R.; Nieselt, Kay; McCaskill, John S.

2015-06-01

We explore the origin-of-life consequences of the view that biological systems are demarcated from inanimate matter by their possession of referential information, which is processed computationally to control choices of specific physico-chemical events. Cells are cybernetic: they use genetic information in processes of communication and control, subjecting physical events to a system of integrated governance. The genetic code is the most obvious example of how cells use information computationally, but the historical origin of the usefulness of molecular information is not well understood. Genetic coding made information useful because it imposed a modular metric on the evolutionary search and thereby offered a general solution to the problem of finding catalysts of any specificity. We use the term "quasispecies symmetry breaking" to describe the iterated process of self-organisation whereby the alphabets of distinguishable codons and amino acids increased, step by step.

Simulations of Living Cell Origins Using a Cellular Automata Model

NASA Astrophysics Data System (ADS)

Ishida, Takeshi

2014-04-01

Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

Simulations of living cell origins using a cellular automata model.

PubMed

Ishida, Takeshi

2014-04-01

Understanding the generalized mechanisms of cell self-assembly is fundamental for applications in various fields, such as mass producing molecular machines in nanotechnology. Thus, the details of real cellular reaction networks and the necessary conditions for self-organized cells must be elucidated. We constructed a 2-dimensional cellular automata model to investigate the emergence of biological cell formation, which incorporated a looped membrane and a membrane-bound information system (akin to a genetic code and gene expression system). In particular, with an artificial reaction system coupled with a thermal system, the simultaneous formation of a looped membrane and an inner reaction process resulted in a more stable structure. These double structures inspired the primitive biological cell formation process from chemical evolution stage. With a model to simulate cellular self-organization in a 2-dimensional cellular automata model, 3 phenomena could be realized: (1) an inner reaction system developed as an information carrier precursor (akin to DNA); (2) a cell border emerged (akin to a cell membrane); and (3) these cell structures could divide into 2. This double-structured cell was considered to be a primary biological cell. The outer loop evolved toward a lipid bilayer membrane, and inner polymeric particles evolved toward precursor information carriers (evolved toward DNA). This model did not completely clarify all the necessary and sufficient conditions for biological cell self-organization. Further, our virtual cells remained unstable and fragile. However, the "garbage bag model" of Dyson proposed that the first living cells were deficient; thus, it would be reasonable that the earliest cells were more unstable and fragile than the simplest current unicellular organisms.

Neuromorphic sensory systems.

PubMed

Liu, Shih-Chii; Delbruck, Tobi

2010-06-01

Biology provides examples of efficient machines which greatly outperform conventional technology. Designers in neuromorphic engineering aim to construct electronic systems with the same efficient style of computation. This task requires a melding of novel engineering principles with knowledge gleaned from neuroscience. We discuss recent progress in realizing neuromorphic sensory systems which mimic the biological retina and cochlea, and subsequent sensor processing. The main trends are the increasing number of sensors and sensory systems that communicate through asynchronous digital signals analogous to neural spikes; the improved performance and usability of these sensors; and novel sensory processing methods which capitalize on the timing of spikes from these sensors. Experiments using these sensors can impact how we think the brain processes sensory information. 2010 Elsevier Ltd. All rights reserved.

Integrated Information Increases with Fitness in the Evolution of Animats

PubMed Central

Edlund, Jeffrey A.; Chaumont, Nicolas; Hintze, Arend; Koch, Christof; Tononi, Giulio; Adami, Christoph

2011-01-01

One of the hallmarks of biological organisms is their ability to integrate disparate information sources to optimize their behavior in complex environments. How this capability can be quantified and related to the functional complexity of an organism remains a challenging problem, in particular since organismal functional complexity is not well-defined. We present here several candidate measures that quantify information and integration, and study their dependence on fitness as an artificial agent (“animat”) evolves over thousands of generations to solve a navigation task in a simple, simulated environment. We compare the ability of these measures to predict high fitness with more conventional information-theoretic processing measures. As the animat adapts by increasing its “fit” to the world, information integration and processing increase commensurately along the evolutionary line of descent. We suggest that the correlation of fitness with information integration and with processing measures implies that high fitness requires both information processing as well as integration, but that information integration may be a better measure when the task requires memory. A correlation of measures of information integration (but also information processing) and fitness strongly suggests that these measures reflect the functional complexity of the animat, and that such measures can be used to quantify functional complexity even in the absence of fitness data. PMID:22028639

The Latin American Biological Dosimetry Network (LBDNet).

PubMed

García, O; Di Giorgio, M; Radl, A; Taja, M R; Sapienza, C E; Deminge, M M; Fernández Rearte, J; Stuck Oliveira, M; Valdivia, P; Lamadrid, A I; González, J E; Romero, I; Mandina, T; Guerrero-Carbajal, C; ArceoMaldonado, C; Cortina Ramírez, G E; Espinoza, M; Martínez-López, W; Di Tomasso, M

2016-09-01

Biological Dosimetry is a necessary support for national radiation protection programmes and emergency response schemes. The Latin American Biological Dosimetry Network (LBDNet) was formally founded in 2007 to provide early biological dosimetry assistance in case of radiation emergencies in the Latin American Region. Here are presented the main topics considered in the foundational document of the network, which comprise: mission, partners, concept of operation, including the mechanism to request support for biological dosimetry assistance in the region, and the network capabilities. The process for network activation and the role of the coordinating laboratory during biological dosimetry emergency response is also presented. This information is preceded by historical remarks on biological dosimetry cooperation in Latin America. A summary of the main experimental and practical results already obtained by the LBDNet is also included. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The Biological Big Bang model for the major transitions in evolution.

PubMed

Koonin, Eugene V

2007-08-20

Major transitions in biological evolution show the same pattern of sudden emergence of diverse forms at a new level of complexity. The relationships between major groups within an emergent new class of biological entities are hard to decipher and do not seem to fit the tree pattern that, following Darwin's original proposal, remains the dominant description of biological evolution. The cases in point include the origin of complex RNA molecules and protein folds; major groups of viruses; archaea and bacteria, and the principal lineages within each of these prokaryotic domains; eukaryotic supergroups; and animal phyla. In each of these pivotal nexuses in life's history, the principal "types" seem to appear rapidly and fully equipped with the signature features of the respective new level of biological organization. No intermediate "grades" or intermediate forms between different types are detectable. Usually, this pattern is attributed to cladogenesis compressed in time, combined with the inevitable erosion of the phylogenetic signal. I propose that most or all major evolutionary transitions that show the "explosive" pattern of emergence of new types of biological entities correspond to a boundary between two qualitatively distinct evolutionary phases. The first, inflationary phase is characterized by extremely rapid evolution driven by various processes of genetic information exchange, such as horizontal gene transfer, recombination, fusion, fission, and spread of mobile elements. These processes give rise to a vast diversity of forms from which the main classes of entities at the new level of complexity emerge independently, through a sampling process. In the second phase, evolution dramatically slows down, the respective process of genetic information exchange tapers off, and multiple lineages of the new type of entities emerge, each of them evolving in a tree-like fashion from that point on. This biphasic model of evolution incorporates the previously developed concepts of the emergence of protein folds by recombination of small structural units and origin of viruses and cells from a pre-cellular compartmentalized pool of recombining genetic elements. The model is extended to encompass other major transitions. It is proposed that bacterial and archaeal phyla emerged independently from two distinct populations of primordial cells that, originally, possessed leaky membranes, which made the cells prone to rampant gene exchange; and that the eukaryotic supergroups emerged through distinct, secondary endosymbiotic events (as opposed to the primary, mitochondrial endosymbiosis). This biphasic model of evolution is substantially analogous to the scenario of the origin of universes in the eternal inflation version of modern cosmology. Under this model, universes like ours emerge in the infinite multiverse when the eternal process of exponential expansion, known as inflation, ceases in a particular region as a result of false vacuum decay, a first order phase transition process. The result is the nucleation of a new universe, which is traditionally denoted Big Bang, although this scenario is radically different from the Big Bang of the traditional model of an expanding universe. Hence I denote the phase transitions at the end of each inflationary epoch in the history of life Biological Big Bangs (BBB). A Biological Big Bang (BBB) model is proposed for the major transitions in life's evolution. According to this model, each transition is a BBB such that new classes of biological entities emerge at the end of a rapid phase of evolution (inflation) that is characterized by extensive exchange of genetic information which takes distinct forms for different BBBs. The major types of new forms emerge independently, via a sampling process, from the pool of recombining entities of the preceding generation. This process is envisaged as being qualitatively different from tree-pattern cladogenesis.

The Biological Big Bang model for the major transitions in evolution

PubMed Central

Koonin, Eugene V

2007-01-01

Background Major transitions in biological evolution show the same pattern of sudden emergence of diverse forms at a new level of complexity. The relationships between major groups within an emergent new class of biological entities are hard to decipher and do not seem to fit the tree pattern that, following Darwin's original proposal, remains the dominant description of biological evolution. The cases in point include the origin of complex RNA molecules and protein folds; major groups of viruses; archaea and bacteria, and the principal lineages within each of these prokaryotic domains; eukaryotic supergroups; and animal phyla. In each of these pivotal nexuses in life's history, the principal "types" seem to appear rapidly and fully equipped with the signature features of the respective new level of biological organization. No intermediate "grades" or intermediate forms between different types are detectable. Usually, this pattern is attributed to cladogenesis compressed in time, combined with the inevitable erosion of the phylogenetic signal. Hypothesis I propose that most or all major evolutionary transitions that show the "explosive" pattern of emergence of new types of biological entities correspond to a boundary between two qualitatively distinct evolutionary phases. The first, inflationary phase is characterized by extremely rapid evolution driven by various processes of genetic information exchange, such as horizontal gene transfer, recombination, fusion, fission, and spread of mobile elements. These processes give rise to a vast diversity of forms from which the main classes of entities at the new level of complexity emerge independently, through a sampling process. In the second phase, evolution dramatically slows down, the respective process of genetic information exchange tapers off, and multiple lineages of the new type of entities emerge, each of them evolving in a tree-like fashion from that point on. This biphasic model of evolution incorporates the previously developed concepts of the emergence of protein folds by recombination of small structural units and origin of viruses and cells from a pre-cellular compartmentalized pool of recombining genetic elements. The model is extended to encompass other major transitions. It is proposed that bacterial and archaeal phyla emerged independently from two distinct populations of primordial cells that, originally, possessed leaky membranes, which made the cells prone to rampant gene exchange; and that the eukaryotic supergroups emerged through distinct, secondary endosymbiotic events (as opposed to the primary, mitochondrial endosymbiosis). This biphasic model of evolution is substantially analogous to the scenario of the origin of universes in the eternal inflation version of modern cosmology. Under this model, universes like ours emerge in the infinite multiverse when the eternal process of exponential expansion, known as inflation, ceases in a particular region as a result of false vacuum decay, a first order phase transition process. The result is the nucleation of a new universe, which is traditionally denoted Big Bang, although this scenario is radically different from the Big Bang of the traditional model of an expanding universe. Hence I denote the phase transitions at the end of each inflationary epoch in the history of life Biological Big Bangs (BBB). Conclusion A Biological Big Bang (BBB) model is proposed for the major transitions in life's evolution. According to this model, each transition is a BBB such that new classes of biological entities emerge at the end of a rapid phase of evolution (inflation) that is characterized by extensive exchange of genetic information which takes distinct forms for different BBBs. The major types of new forms emerge independently, via a sampling process, from the pool of recombining entities of the preceding generation. This process is envisaged as being qualitatively different from tree-pattern cladogenesis. Reviewers This article was reviewed by William Martin, Sergei Maslov, and Leonid Mirny. PMID:17708768

Biomimetics: its practice and theory.

PubMed

Vincent, Julian F V; Bogatyreva, Olga A; Bogatyrev, Nikolaj R; Bowyer, Adrian; Pahl, Anja-Karina

2006-08-22

Biomimetics, a name coined by Otto Schmitt in the 1950s for the transfer of ideas and analogues from biology to technology, has produced some significant and successful devices and concepts in the past 50 years, but is still empirical. We show that TRIZ, the Russian system of problem solving, can be adapted to illuminate and manipulate this process of transfer. Analysis using TRIZ shows that there is only 12% similarity between biology and technology in the principles which solutions to problems illustrate, and while technology solves problems largely by manipulating usage of energy, biology uses information and structure, two factors largely ignored by technology.

Spaces of the possible: universal Darwinism and the wall between technological and biological innovation

PubMed Central

Wagner, Andreas; Rosen, William

2014-01-01

Innovations in biological evolution and in technology have many common features. Some of them involve similar processes, such as trial and error and horizontal information transfer. Others describe analogous outcomes such as multiple independent origins of similar innovations. Yet others display similar temporal patterns such as episodic bursts of change separated by periods of stasis. We review nine such commonalities, and propose that the mathematical concept of a space of innovations, discoveries or designs can help explain them. This concept can also help demolish a persistent conceptual wall between technological and biological innovation. PMID:24850903

Goodbye, Waste! What We Make. Science and Technology Education in Philippine Society.

ERIC Educational Resources Information Center

Philippines Univ., Quezon City. Science Education Center.

This module: (1) discusses the need for disposing of waste safely; (2) provides information and activities on wet and dry wastes; and (3) shows how to prepare, maintain, and study a fertilizer basket (in which fertilizer is made from wet waste). Information on the biology of the basket (including role of bacteria and fungi in the decay process) is…

Applying the dark diversity concept to nature conservation.

PubMed

Lewis, Rob J; de Bello, Francesco; Bennett, Jonathan A; Fibich, Pavel; Finerty, Genevieve E; Götzenberger, Lars; Hiiesalu, Inga; Kasari, Liis; Lepš, Jan; Májeková, Maria; Mudrák, Ondřej; Riibak, Kersti; Ronk, Argo; Rychtecká, Terezie; Vitová, Alena; Pärtel, Meelis

2017-02-01

Linking diversity to biological processes is central for developing informed and effective conservation decisions. Unfortunately, observable patterns provide only a proportion of the information necessary for fully understanding the mechanisms and processes acting on a particular population or community. We suggest conservation managers use the often overlooked information relative to species absences and pay particular attention to dark diversity (i.e., a set of species that are absent from a site but that could disperse to and establish there, in other words, the absent portion of a habitat-specific species pool). Together with existing ecological metrics, concepts, and conservation tools, dark diversity can be used to complement and further develop conservation prioritization and management decisions through an understanding of biodiversity relativized by its potential (i.e., its species pool). Furthermore, through a detailed understanding of the population, community, and functional dark diversity, the restoration potential of degraded habitats can be more rigorously assessed and so to the likelihood of successful species invasions. We suggest the application of the dark diversity concept is currently an underappreciated source of information that is valuable for conservation applications ranging from macroscale conservation prioritization to more locally scaled restoration ecology and the management of invasive species. © 2016 Society for Conservation Biology.

Evolutionary Computing Methods for Spectral Retrieval

NASA Technical Reports Server (NTRS)

Terrile, Richard; Fink, Wolfgang; Huntsberger, Terrance; Lee, Seugwon; Tisdale, Edwin; VonAllmen, Paul; Tinetti, Geivanna

2009-01-01

A methodology for processing spectral images to retrieve information on underlying physical, chemical, and/or biological phenomena is based on evolutionary and related computational methods implemented in software. In a typical case, the solution (the information that one seeks to retrieve) consists of parameters of a mathematical model that represents one or more of the phenomena of interest. The methodology was developed for the initial purpose of retrieving the desired information from spectral image data acquired by remote-sensing instruments aimed at planets (including the Earth). Examples of information desired in such applications include trace gas concentrations, temperature profiles, surface types, day/night fractions, cloud/aerosol fractions, seasons, and viewing angles. The methodology is also potentially useful for retrieving information on chemical and/or biological hazards in terrestrial settings. In this methodology, one utilizes an iterative process that minimizes a fitness function indicative of the degree of dissimilarity between observed and synthetic spectral and angular data. The evolutionary computing methods that lie at the heart of this process yield a population of solutions (sets of the desired parameters) within an accuracy represented by a fitness-function value specified by the user. The evolutionary computing methods (ECM) used in this methodology are Genetic Algorithms and Simulated Annealing, both of which are well-established optimization techniques and have also been described in previous NASA Tech Briefs articles. These are embedded in a conceptual framework, represented in the architecture of the implementing software, that enables automatic retrieval of spectral and angular data and analysis of the retrieved solutions for uniqueness.

Systems modelling methodology for the analysis of apoptosis signal transduction and cell death decisions.

PubMed

Rehm, Markus; Prehn, Jochen H M

2013-06-01

Systems biology and systems medicine, i.e. the application of systems biology in a clinical context, is becoming of increasing importance in biology, drug discovery and health care. Systems biology incorporates knowledge and methods that are applied in mathematics, physics and engineering, but may not be part of classical training in biology. We here provide an introduction to basic concepts and methods relevant to the construction and application of systems models for apoptosis research. We present the key methods relevant to the representation of biochemical processes in signal transduction models, with a particular reference to apoptotic processes. We demonstrate how such models enable a quantitative and temporal analysis of changes in molecular entities in response to an apoptosis-inducing stimulus, and provide information on cell survival and cell death decisions. We introduce methods for analyzing the spatial propagation of cell death signals, and discuss the concepts of sensitivity analyses that enable a prediction of network responses to disturbances of single or multiple parameters. Copyright © 2013 Elsevier Inc. All rights reserved.

STOCHSIMGPU: parallel stochastic simulation for the Systems Biology Toolbox 2 for MATLAB.

PubMed

Klingbeil, Guido; Erban, Radek; Giles, Mike; Maini, Philip K

2011-04-15

The importance of stochasticity in biological systems is becoming increasingly recognized and the computational cost of biologically realistic stochastic simulations urgently requires development of efficient software. We present a new software tool STOCHSIMGPU that exploits graphics processing units (GPUs) for parallel stochastic simulations of biological/chemical reaction systems and show that significant gains in efficiency can be made. It is integrated into MATLAB and works with the Systems Biology Toolbox 2 (SBTOOLBOX2) for MATLAB. The GPU-based parallel implementation of the Gillespie stochastic simulation algorithm (SSA), the logarithmic direct method (LDM) and the next reaction method (NRM) is approximately 85 times faster than the sequential implementation of the NRM on a central processing unit (CPU). Using our software does not require any changes to the user's models, since it acts as a direct replacement of the stochastic simulation software of the SBTOOLBOX2. The software is open source under the GPL v3 and available at http://www.maths.ox.ac.uk/cmb/STOCHSIMGPU. The web site also contains supplementary information. klingbeil@maths.ox.ac.uk Supplementary data are available at Bioinformatics online.

Local and global aspects of biological motion perception in children born at very low birth weight

PubMed Central

Williamson, K. E.; Jakobson, L. S.; Saunders, D. R.; Troje, N. F.

2015-01-01

Biological motion perception can be assessed using a variety of tasks. In the present study, 8- to 11-year-old children born prematurely at very low birth weight (<1500 g) and matched, full-term controls completed tasks that required the extraction of local motion cues, the ability to perceptually group these cues to extract information about body structure, and the ability to carry out higher order processes required for action recognition and person identification. Preterm children exhibited difficulties in all 4 aspects of biological motion perception. However, intercorrelations between test scores were weak in both full-term and preterm children—a finding that supports the view that these processes are relatively independent. Preterm children also displayed more autistic-like traits than full-term peers. In preterm (but not full-term) children, these traits were negatively correlated with performance in the task requiring structure-from-motion processing, r(30) = −.36, p < .05), but positively correlated with the ability to extract identity, r(30) = .45, p < .05). These findings extend previous reports of vulnerability in systems involved in processing dynamic cues in preterm children and suggest that a core deficit in social perception/cognition may contribute to the development of the social and behavioral difficulties even in members of this population who are functioning within the normal range intellectually. The results could inform the development of screening, diagnostic, and intervention tools. PMID:25103588

cPath: open source software for collecting, storing, and querying biological pathways.

PubMed

Cerami, Ethan G; Bader, Gary D; Gross, Benjamin E; Sander, Chris

2006-11-13

Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling.

Intergenerational transmission of biased information processing in posttraumatic stress disorder (PTSD) following displacement after World War II.

PubMed

Wittekind, Charlotte E; Jelinek, Lena; Kellner, Michael; Moritz, Steffen; Muhtz, Christoph

2010-12-01

An attentional bias for trauma-related stimuli has been demonstrated in individuals with posttraumatic stress disorder (PTSD). However, few studies have investigated how biological relatives of individuals with PTSD process trauma-relevant information. To investigate whether parental PTSD is associated with an attentional bias for trauma-related stimuli in adult offspring, we compared performance of individuals displaced after World War II with (n=22) and without PTSD (n=24) to a non-displaced healthy control group (n=11) and their respective offspring as to their processing of trauma-related stimuli in an emotional Stroop task. Evidence for biased information processing was neither found in individuals with PTSD nor their offspring. Possible explanations for the findings and implications for future studies are discussed. Copyright © 2010 Elsevier Ltd. All rights reserved.

Limits on reliable information flows through stochastic populations.

PubMed

Boczkowski, Lucas; Natale, Emanuele; Feinerman, Ofer; Korman, Amos

2018-06-06

Biological systems can share and collectively process information to yield emergent effects, despite inherent noise in communication. While man-made systems often employ intricate structural solutions to overcome noise, the structure of many biological systems is more amorphous. It is not well understood how communication noise may affect the computational repertoire of such groups. To approach this question we consider the basic collective task of rumor spreading, in which information from few knowledgeable sources must reliably flow into the rest of the population. We study the effect of communication noise on the ability of groups that lack stable structures to efficiently solve this task. We present an impossibility result which strongly restricts reliable rumor spreading in such groups. Namely, we prove that, in the presence of even moderate levels of noise that affect all facets of the communication, no scheme can significantly outperform the trivial one in which agents have to wait until directly interacting with the sources-a process which requires linear time in the population size. Our results imply that in order to achieve efficient rumor spread a system must exhibit either some degree of structural stability or, alternatively, some facet of the communication which is immune to noise. We then corroborate this claim by providing new analyses of experimental data regarding recruitment in Cataglyphis niger desert ants. Finally, in light of our theoretical results, we discuss strategies to overcome noise in other biological systems.

Molecular Force Spectroscopy on Cells

NASA Astrophysics Data System (ADS)

Liu, Baoyu; Chen, Wei; Zhu, Cheng

2015-04-01

Molecular force spectroscopy has become a powerful tool to study how mechanics regulates biology, especially the mechanical regulation of molecular interactions and its impact on cellular functions. This force-driven methodology has uncovered a wealth of new information of the physical chemistry of molecular bonds for various biological systems. The new concepts, qualitative and quantitative measures describing bond behavior under force, and structural bases underlying these phenomena have substantially advanced our fundamental understanding of the inner workings of biological systems from the nanoscale (molecule) to the microscale (cell), elucidated basic molecular mechanisms of a wide range of important biological processes, and provided opportunities for engineering applications. Here, we review major force spectroscopic assays, conceptual developments of mechanically regulated kinetics of molecular interactions, and their biological relevance. We also present current challenges and highlight future directions.

Synthetic biology: insights into biological computation.

PubMed

Manzoni, Romilde; Urrios, Arturo; Velazquez-Garcia, Silvia; de Nadal, Eulàlia; Posas, Francesc

2016-04-18

Organisms have evolved a broad array of complex signaling mechanisms that allow them to survive in a wide range of environmental conditions. They are able to sense external inputs and produce an output response by computing the information. Synthetic biology attempts to rationally engineer biological systems in order to perform desired functions. Our increasing understanding of biological systems guides this rational design, while the huge background in electronics for building circuits defines the methodology. In this context, biocomputation is the branch of synthetic biology aimed at implementing artificial computational devices using engineered biological motifs as building blocks. Biocomputational devices are defined as biological systems that are able to integrate inputs and return outputs following pre-determined rules. Over the last decade the number of available synthetic engineered devices has increased exponentially; simple and complex circuits have been built in bacteria, yeast and mammalian cells. These devices can manage and store information, take decisions based on past and present inputs, and even convert a transient signal into a sustained response. The field is experiencing a fast growth and every day it is easier to implement more complex biological functions. This is mainly due to advances in in vitro DNA synthesis, new genome editing tools, novel molecular cloning techniques, continuously growing part libraries as well as other technological advances. This allows that digital computation can now be engineered and implemented in biological systems. Simple logic gates can be implemented and connected to perform novel desired functions or to better understand and redesign biological processes. Synthetic biological digital circuits could lead to new therapeutic approaches, as well as new and efficient ways to produce complex molecules such as antibiotics, bioplastics or biofuels. Biological computation not only provides possible biomedical and biotechnological applications, but also affords a greater understanding of biological systems.

Modeling and Assimilating Ocean Color Radiances

NASA Technical Reports Server (NTRS)

Gregg, Watson

2012-01-01

Radiances are the source of information from ocean color sensors to produce estimates of biological and geochemical constituents. They potentially provide information on various other aspects of global biological and chemical systems, and there is considerable work involved in deriving new information from these signals. Each derived product, however, contains errors that are derived from the application of the radiances, above and beyond the radiance errors. A global biogeochemical model with an explicit spectral radiative transfer model is used to investigate the potential of assimilating radiances. The results indicate gaps in our understanding of radiative processes in the oceans and their relationships with biogeochemical variables. Most important, detritus optical properties are not well characterized and produce important effects of the simulated radiances. Specifically, there does not appear to be a relationship between detrital biomass and its optical properties, as there is for chlorophyll. Approximations are necessary to get beyond this problem. In this reprt we will discuss the challenges in modeling and assimilation water-leaving radiances and the prospects for improving our understanding of biogeochemical process by utilizing these signals.

An Overview of Biomolecular Event Extraction from Scientific Documents

PubMed Central

Vanegas, Jorge A.; Matos, Sérgio; González, Fabio; Oliveira, José L.

2015-01-01

This paper presents a review of state-of-the-art approaches to automatic extraction of biomolecular events from scientific texts. Events involving biomolecules such as genes, transcription factors, or enzymes, for example, have a central role in biological processes and functions and provide valuable information for describing physiological and pathogenesis mechanisms. Event extraction from biomedical literature has a broad range of applications, including support for information retrieval, knowledge summarization, and information extraction and discovery. However, automatic event extraction is a challenging task due to the ambiguity and diversity of natural language and higher-level linguistic phenomena, such as speculations and negations, which occur in biological texts and can lead to misunderstanding or incorrect interpretation. Many strategies have been proposed in the last decade, originating from different research areas such as natural language processing, machine learning, and statistics. This review summarizes the most representative approaches in biomolecular event extraction and presents an analysis of the current state of the art and of commonly used methods, features, and tools. Finally, current research trends and future perspectives are also discussed. PMID:26587051

Cost model for biobanks.

PubMed

Gonzalez-Sanchez, M Beatriz; Lopez-Valeiras, Ernesto; Morente, Manuel M; Fernández Lago, Orlando

2013-10-01

Current economic conditions and budget constraints in publicly funded biomedical research have brought about a renewed interest in analyzing the cost and economic viability of research infrastructures. However, there are no proposals for specific cost accounting models for these types of organizations in the international scientific literature. The aim of this paper is to present the basis of a cost analysis model useful for any biobank regardless of the human biological samples that it stores for biomedical research. The development of a unique cost model for biobanks can be a complicated task due to the diversity of the biological samples they store. Different types of samples (DNA, tumor tissues, blood, serum, etc.) require different production processes. Nonetheless, the common basic steps of the production process can be identified. Thus, the costs incurred in each step can be analyzed in detail to provide cost information. Six stages and four cost objects were obtained by taking the production processes of biobanks belonging to the Spanish National Biobank Network as a starting point. Templates and examples are provided to help managers to identify and classify the costs involved in their own biobanks to implement the model. The application of this methodology will provide accurate information on cost objects, along with useful information to give an economic value to the stored samples, to analyze the efficiency of the production process and to evaluate the viability of some sample collections.

Auditory-visual object recognition time suggests specific processing for animal sounds.

PubMed

Suied, Clara; Viaud-Delmon, Isabelle

2009-01-01

Recognizing an object requires binding together several cues, which may be distributed across different sensory modalities, and ignoring competing information originating from other objects. In addition, knowledge of the semantic category of an object is fundamental to determine how we should react to it. Here we investigate the role of semantic categories in the processing of auditory-visual objects. We used an auditory-visual object-recognition task (go/no-go paradigm). We compared recognition times for two categories: a biologically relevant one (animals) and a non-biologically relevant one (means of transport). Participants were asked to react as fast as possible to target objects, presented in the visual and/or the auditory modality, and to withhold their response for distractor objects. A first main finding was that, when participants were presented with unimodal or bimodal congruent stimuli (an image and a sound from the same object), similar reaction times were observed for all object categories. Thus, there was no advantage in the speed of recognition for biologically relevant compared to non-biologically relevant objects. A second finding was that, in the presence of a biologically relevant auditory distractor, the processing of a target object was slowed down, whether or not it was itself biologically relevant. It seems impossible to effectively ignore an animal sound, even when it is irrelevant to the task. These results suggest a specific and mandatory processing of animal sounds, possibly due to phylogenetic memory and consistent with the idea that hearing is particularly efficient as an alerting sense. They also highlight the importance of taking into account the auditory modality when investigating the way object concepts of biologically relevant categories are stored and retrieved.

BioPAX – A community standard for pathway data sharing

PubMed Central

Demir, Emek; Cary, Michael P.; Paley, Suzanne; Fukuda, Ken; Lemer, Christian; Vastrik, Imre; Wu, Guanming; D’Eustachio, Peter; Schaefer, Carl; Luciano, Joanne; Schacherer, Frank; Martinez-Flores, Irma; Hu, Zhenjun; Jimenez-Jacinto, Veronica; Joshi-Tope, Geeta; Kandasamy, Kumaran; Lopez-Fuentes, Alejandra C.; Mi, Huaiyu; Pichler, Elgar; Rodchenkov, Igor; Splendiani, Andrea; Tkachev, Sasha; Zucker, Jeremy; Gopinath, Gopal; Rajasimha, Harsha; Ramakrishnan, Ranjani; Shah, Imran; Syed, Mustafa; Anwar, Nadia; Babur, Ozgun; Blinov, Michael; Brauner, Erik; Corwin, Dan; Donaldson, Sylva; Gibbons, Frank; Goldberg, Robert; Hornbeck, Peter; Luna, Augustin; Murray-Rust, Peter; Neumann, Eric; Reubenacker, Oliver; Samwald, Matthias; van Iersel, Martijn; Wimalaratne, Sarala; Allen, Keith; Braun, Burk; Whirl-Carrillo, Michelle; Dahlquist, Kam; Finney, Andrew; Gillespie, Marc; Glass, Elizabeth; Gong, Li; Haw, Robin; Honig, Michael; Hubaut, Olivier; Kane, David; Krupa, Shiva; Kutmon, Martina; Leonard, Julie; Marks, Debbie; Merberg, David; Petri, Victoria; Pico, Alex; Ravenscroft, Dean; Ren, Liya; Shah, Nigam; Sunshine, Margot; Tang, Rebecca; Whaley, Ryan; Letovksy, Stan; Buetow, Kenneth H.; Rzhetsky, Andrey; Schachter, Vincent; Sobral, Bruno S.; Dogrusoz, Ugur; McWeeney, Shannon; Aladjem, Mirit; Birney, Ewan; Collado-Vides, Julio; Goto, Susumu; Hucka, Michael; Le Novère, Nicolas; Maltsev, Natalia; Pandey, Akhilesh; Thomas, Paul; Wingender, Edgar; Karp, Peter D.; Sander, Chris; Bader, Gary D.

2010-01-01

BioPAX (Biological Pathway Exchange) is a standard language to represent biological pathways at the molecular and cellular level. Its major use is to facilitate the exchange of pathway data (http://www.biopax.org). Pathway data captures our understanding of biological processes, but its rapid growth necessitates development of databases and computational tools to aid interpretation. However, the current fragmentation of pathway information across many databases with incompatible formats presents barriers to its effective use. BioPAX solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. BioPAX was created through a community process. Through BioPAX, millions of interactions organized into thousands of pathways across many organisms, from a growing number of sources, are available. Thus, large amounts of pathway data are available in a computable form to support visualization, analysis and biological discovery. PMID:20829833

Network news: prime time for systems biology of the plant circadian clock.

PubMed

McClung, C Robertson; Gutiérrez, Rodrigo A

2010-12-01

Whole-transcriptome analyses have established that the plant circadian clock regulates virtually every plant biological process and most prominently hormonal and stress response pathways. Systems biology efforts have successfully modeled the plant central clock machinery and an iterative process of model refinement and experimental validation has contributed significantly to the current view of the central clock machinery. The challenge now is to connect this central clock to the output pathways for understanding how the plant circadian clock contributes to plant growth and fitness in a changing environment. Undoubtedly, systems approaches will be needed to integrate and model the vastly increased volume of experimental data in order to extract meaningful biological information. Thus, we have entered an era of systems modeling, experimental testing, and refinement. This approach, coupled with advances from the genetic and biochemical analyses of clock function, is accelerating our progress towards a comprehensive understanding of the plant circadian clock network. Copyright © 2010 Elsevier Ltd. All rights reserved.

Analytic considerations and axiomatic approaches to the concept cell death and cell survival functions in biology and cancer treatment.

PubMed

Gkigkitzis, Ioannis; Haranas, Ioannis; Austerlitz, Carlos

2015-01-01

This study contains a discussion on the connection between current mathematical and biological modeling systems in response to the main research need for the development of a new mathematical theory for study of cell survival after medical treatment and cell biological behavior in general. This is a discussion of suggested future research directions and relations with interdisciplinary science. In an effort to establish the foundations for a possible framework that may be adopted to study and analyze the process of cell survival during treatment, we investigate the organic connection among an axiomatic system foundation, a predator-prey rate equation, and information theoretic signal processing. A new set theoretic approach is also introduced through the definition of cell survival units or cell survival units indicating the use of "proper classes" according to the Zermelo-Fraenkel set theory and the axiom of choice, as the mathematics appropriate for the development of biological theory of cell survival.

Ultrashort Phenomena in Biochemistry and Biological Signaling

NASA Astrophysics Data System (ADS)

Splinter, Robert

2014-11-01

In biological phenomena there are indications that within the long pulse-length of the action potential on millisecond scale, there is additional ultrashort perturbation encoding that provides the brain with detailed information about the origin (location) and physiological characteristics. The objective is to identify the mechanism-of-action providing the potential for encoding in biological signal propagation. The actual molecular processes involved in the initiation of the action potential have been identified to be in the femtosecond and pico-second scale. The depolarization process of the cellular membrane itself, leading to the onset of the actionpotential that is transmitted to the brain, however is in the millisecond timeframe. One example of the femtosecond chemical interaction is the photoresponse of bacteriorhodopsin. No clear indication for the spatial encoding has so far been verified. Further research will be required on a cellular signal analysis level to confirm or deny the spatial and physiological encoding in the signal wave-trains of intercellular communications and sensory stimuli. The pathological encoding process for cardiac depolarization is however very pronounced and validated, however this electro-chemical process is in the millisecond amplitude and frequency modulation spectrum.

Soft-Bodied Fossils Are Not Simply Rotten Carcasses - Toward a Holistic Understanding of Exceptional Fossil Preservation: Exceptional Fossil Preservation Is Complex and Involves the Interplay of Numerous Biological and Geological Processes.

PubMed

Parry, Luke A; Smithwick, Fiann; Nordén, Klara K; Saitta, Evan T; Lozano-Fernandez, Jesus; Tanner, Alastair R; Caron, Jean-Bernard; Edgecombe, Gregory D; Briggs, Derek E G; Vinther, Jakob

2018-01-01

Exceptionally preserved fossils are the product of complex interplays of biological and geological processes including burial, autolysis and microbial decay, authigenic mineralization, diagenesis, metamorphism, and finally weathering and exhumation. Determining which tissues are preserved and how biases affect their preservation pathways is important for interpreting fossils in phylogenetic, ecological, and evolutionary frameworks. Although laboratory decay experiments reveal important aspects of fossilization, applying the results directly to the interpretation of exceptionally preserved fossils may overlook the impact of other key processes that remove or preserve morphological information. Investigations of fossils preserving non-biomineralized tissues suggest that certain structures that are decay resistant (e.g., the notochord) are rarely preserved (even where carbonaceous components survive), and decay-prone structures (e.g., nervous systems) can fossilize, albeit rarely. As we review here, decay resistance is an imperfect indicator of fossilization potential, and a suite of biological and geological processes account for the features preserved in exceptional fossils. © 2017 The Authors. BioEssays Published by WILEY Periodicals, Inc.

Predicting green: really radical (plant) predictive processing

PubMed Central

Friston, Karl

2017-01-01

In this article we account for the way plants respond to salient features of their environment under the free-energy principle for biological systems. Biological self-organization amounts to the minimization of surprise over time. We posit that any self-organizing system must embody a generative model whose predictions ensure that (expected) free energy is minimized through action. Plants respond in a fast, and yet coordinated manner, to environmental contingencies. They pro-actively sample their local environment to elicit information with an adaptive value. Our main thesis is that plant behaviour takes place by way of a process (active inference) that predicts the environmental sources of sensory stimulation. This principle, we argue, endows plants with a form of perception that underwrites purposeful, anticipatory behaviour. The aim of the article is to assess the prospects of a radical predictive processing story that would follow naturally from the free-energy principle for biological systems; an approach that may ultimately bear upon our understanding of life and cognition more broadly. PMID:28637913

Microbial ecology of denitrification in biological wastewater treatment.

PubMed

Lu, Huijie; Chandran, Kartik; Stensel, David

2014-11-01

Globally, denitrification is commonly employed in biological nitrogen removal processes to enhance water quality. However, substantial knowledge gaps remain concerning the overall community structure, population dynamics and metabolism of different organic carbon sources. This systematic review provides a summary of current findings pertaining to the microbial ecology of denitrification in biological wastewater treatment processes. DNA fingerprinting-based analysis has revealed a high level of microbial diversity in denitrification reactors and highlighted the impacts of carbon sources in determining overall denitrifying community composition. Stable isotope probing, fluorescence in situ hybridization, microarrays and meta-omics further link community structure with function by identifying the functional populations and their gene regulatory patterns at the transcriptional and translational levels. This review stresses the need to integrate microbial ecology information into conventional denitrification design and operation at full-scale. Some emerging questions, from physiological mechanisms to practical solutions, for example, eliminating nitrous oxide emissions and supplementing more sustainable carbon sources than methanol, are also discussed. A combination of high-throughput approaches is next in line for thorough assessment of wastewater denitrifying community structure and function. Though denitrification is used as an example here, this synergy between microbial ecology and process engineering is applicable to other biological wastewater treatment processes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Meta-analysis of magnitudes, differences and variation in evolutionary parameters.

PubMed

Morrissey, M B

2016-10-01

Meta-analysis is increasingly used to synthesize major patterns in the large literatures within ecology and evolution. Meta-analytic methods that do not account for the process of observing data, which we may refer to as 'informal meta-analyses', may have undesirable properties. In some cases, informal meta-analyses may produce results that are unbiased, but do not necessarily make the best possible use of available data. In other cases, unbiased statistical noise in individual reports in the literature can potentially be converted into severe systematic biases in informal meta-analyses. I first present a general description of how failure to account for noise in individual inferences should be expected to lead to biases in some kinds of meta-analysis. In particular, informal meta-analyses of quantities that reflect the dispersion of parameters in nature, for example, the mean absolute value of a quantity, are likely to be generally highly misleading. I then re-analyse three previously published informal meta-analyses, where key inferences were of aspects of the dispersion of values in nature, for example, the mean absolute value of selection gradients. Major biological conclusions in each original informal meta-analysis closely match those that could arise as artefacts due to statistical noise. I present alternative mixed-model-based analyses that are specifically tailored to each situation, but where all analyses may be implemented with widely available open-source software. In each example meta-re-analysis, major conclusions change substantially. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

National Biological Information Infrastructure (NBII) | Information Center

Science.gov Websites

National Biological Information Infrastructure (NBII) Contact Information Website: http://www.nbii.gov/ The National Biological Information Infrastructure (NBII) is a broad, collaborative program to provide increased access to data and information on the nation's biological resources. The NBII links diverse, high

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

Olsen, C.R.; Larsen, I.L.; Lowry, P.D.

Radionuclides released into the Susquehanna--Chesapeake System from the Three Mile Island, Peach Bottom, and Calvert Cliffs nuclear power plants are partitioned among dissolved, particulate, and biological phases and may thus exist in a number of physical and chemical forms. In this project, we have measured the dissolved and particulate distributions of fallout /sup 137/Cs; reactor-released /sup 137/Cs, /sup 134/Cs, /sup 65/Zn, /sup 60/Co, and /sup 58/Co; and naturally occurring /sup 7/Be and /sup 210/Pb in the lower Susquehanna River and Upper Chesapeake Bay. In addition, we chemically leached suspended particles and bottom sediments in the laboratory to determine radionuclide partitioningmore » among different particulate-sorbing phases to complement the site-specific field data. This information has been used to document the important geochemical processes that affect the transport, sorption, distribution, and fate of reactor-released radionuclides (and by analogy, other trace contaminants) in this river-estuarine system. Knowledge of the mechanisms, kinetic factors, and processes that affect radionuclide distributions is crucial for predicting their biological availability, toxicity, chemical behavior, physical transport, and accumulation in aquatic systems. The results from this project provide the information necessary for developing accurate radionuclide-transport and biological-uptake models. 76 refs., 12 figs.« less

THE CAUSAL ANALYSIS / DIAGNOSIS DECISION ...

EPA Pesticide Factsheets

CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based on the US EPA's Stressor Identification process which is a formal method for identifying causes of impairments in aquatic systems. CADDIS 2007 increases access to relevant information useful for causal analysis and provides methods and tools that practitioners can use to analyze their own data. The new Candidate Cause section provides overviews of commonly encountered causes of impairments to aquatic systems: metals, sediments, nutrients, flow alteration, temperature, ionic strength, and low dissolved oxygen. CADDIS includes new Conceptual Models that illustrate the relationships from sources to stressors to biological effects. An Interactive Conceptual Model for phosphorus links the diagram with supporting literature citations. The new Analyzing Data section helps practitioners analyze their data sets and interpret and use those results as evidence within the USEPA causal assessment process. Downloadable tools include a graphical user interface statistical package (CADStat), and programs for use with the freeware R statistical package, and a Microsoft Excel template. These tools can be used to quantify associations between causes and biological impairments using innovative methods such as species-sensitivity distributions, biological inferenc

At a glance: cellular biology for engineers.

PubMed

Khoshmanesh, K; Kouzani, A Z; Nahavandi, S; Baratchi, S; Kanwar, J R

2008-10-01

Engineering contributions have played an important role in the rise and evolution of cellular biology. Engineering technologies have helped biologists to explore the living organisms at cellular and molecular levels, and have created new opportunities to tackle the unsolved biological problems. There is now a growing demand to further expand the role of engineering in cellular biology research. For an engineer to play an effective role in cellular biology, the first essential step is to understand the cells and their components. However, the stumbling block of this step is to comprehend the information given in the cellular biology literature because it best suits the readers with a biological background. This paper aims to overcome this bottleneck by describing the human cell components as micro-plants that form cells as micro-bio-factories. This concept can accelerate the engineers' comprehension of the subject. In this paper, first the structure and function of different cell components are described. In addition, the engineering attempts to mimic various cell components through numerical modelling or physical implementation are highlighted. Next, the interaction of different cell components that facilitate complicated chemical processes, such as energy generation and protein synthesis, are described. These complex interactions are translated into simple flow diagrams, generally used by engineers to represent multi-component processes.

Metabolic Free Energy and Biological Codes: A 'Data Rate Theorem' Aging Model.

PubMed

Wallace, Rodrick

2015-06-01

A famous argument by Maturana and Varela (Autopoiesis and cognition. Reidel, Dordrecht, 1980) holds that the living state is cognitive at every scale and level of organization. Since it is possible to associate many cognitive processes with 'dual' information sources, pathologies can sometimes be addressed using statistical models based on the Shannon Coding, the Shannon-McMillan Source Coding, the Rate Distortion, and the Data Rate Theorems, which impose necessary conditions on information transmission and system control. Deterministic-but-for-error biological codes do not directly invoke cognition, but may be essential subcomponents within larger cognitive processes. A formal argument, however, places such codes within a similar framework, with metabolic free energy serving as a 'control signal' stabilizing biochemical code-and-translator dynamics in the presence of noise. Demand beyond available energy supply triggers punctuated destabilization of the coding channel, affecting essential biological functions. Aging, normal or prematurely driven by psychosocial or environmental stressors, must interfere with the routine operation of such mechanisms, initiating the chronic diseases associated with senescence. Amyloid fibril formation, intrinsically disordered protein logic gates, and cell surface glycan/lectin 'kelp bed' logic gates are reviewed from this perspective. The results generalize beyond coding machineries having easily recognizable symmetry modes, and strip a layer of mathematical complication from the study of phase transitions in nonequilibrium biological systems.

Integrating data from biological experiments into metabolic networks with the DBE information system.

PubMed

Borisjuk, Ljudmilla; Hajirezaei, Mohammad-Reza; Klukas, Christian; Rolletschek, Hardy; Schreiber, Falk

2005-01-01

Modern 'omics'-technologies result in huge amounts of data about life processes. For analysis and data mining purposes this data has to be considered in the context of the underlying biological networks. This work presents an approach for integrating data from biological experiments into metabolic networks by mapping the data onto network elements and visualising the data enriched networks automatically. This methodology is implemented in DBE, an information system that supports the analysis and visualisation of experimental data in the context of metabolic networks. It consists of five parts: (1) the DBE-Database for consistent data storage, (2) the Excel-Importer application for the data import, (3) the DBE-Website as the interface for the system, (4) the DBE-Pictures application for the up- and download of binary (e. g. image) files, and (5) DBE-Gravisto, a network analysis and graph visualisation system. The usability of this approach is demonstrated in two examples.

Synthetic Biology: Mapping the Scientific Landscape

PubMed Central

Oldham, Paul; Hall, Stephen; Burton, Geoff

2012-01-01

This article uses data from Thomson Reuters Web of Science to map and analyse the scientific landscape for synthetic biology. The article draws on recent advances in data visualisation and analytics with the aim of informing upcoming international policy debates on the governance of synthetic biology by the Subsidiary Body on Scientific, Technical and Technological Advice (SBSTTA) of the United Nations Convention on Biological Diversity. We use mapping techniques to identify how synthetic biology can best be understood and the range of institutions, researchers and funding agencies involved. Debates under the Convention are likely to focus on a possible moratorium on the field release of synthetic organisms, cells or genomes. Based on the empirical evidence we propose that guidance could be provided to funding agencies to respect the letter and spirit of the Convention on Biological Diversity in making research investments. Building on the recommendations of the United States Presidential Commission for the Study of Bioethical Issues we demonstrate that it is possible to promote independent and transparent monitoring of developments in synthetic biology using modern information tools. In particular, public and policy understanding and engagement with synthetic biology can be enhanced through the use of online interactive tools. As a step forward in this process we make existing data on the scientific literature on synthetic biology available in an online interactive workbook so that researchers, policy makers and civil society can explore the data and draw conclusions for themselves. PMID:22539946

Lost at sea: ocean acidification undermines larval fish orientation via altered hearing and marine soundscape modification.

PubMed

Rossi, Tullio; Nagelkerken, Ivan; Pistevos, Jennifer C A; Connell, Sean D

2016-01-01

The dispersal of larvae and their settlement to suitable habitat is fundamental to the replenishment of marine populations and the communities in which they live. Sound plays an important role in this process because for larvae of various species, it acts as an orientational cue towards suitable settlement habitat. Because marine sounds are largely of biological origin, they not only carry information about the location of potential habitat, but also information about the quality of habitat. While ocean acidification is known to affect a wide range of marine organisms and processes, its effect on marine soundscapes and its reception by navigating oceanic larvae remains unknown. Here, we show that ocean acidification causes a switch in role of present-day soundscapes from attractor to repellent in the auditory preferences in a temperate larval fish. Using natural CO2 vents as analogues of future ocean conditions, we further reveal that ocean acidification can impact marine soundscapes by profoundly diminishing their biological sound production. An altered soundscape poorer in biological cues indirectly penalizes oceanic larvae at settlement stage because both control and CO2-treated fish larvae showed lack of any response to such future soundscapes. These indirect and direct effects of ocean acidification put at risk the complex processes of larval dispersal and settlement. © 2016 The Author(s).

Semantics-driven modelling of user preferences for information retrieval in the biomedical domain.

PubMed

Gladun, Anatoly; Rogushina, Julia; Valencia-García, Rafael; Béjar, Rodrigo Martínez

2013-03-01

A large amount of biomedical and genomic data are currently available on the Internet. However, data are distributed into heterogeneous biological information sources, with little or even no organization. Semantic technologies provide a consistent and reliable basis with which to confront the challenges involved in the organization, manipulation and visualization of data and knowledge. One of the knowledge representation techniques used in semantic processing is the ontology, which is commonly defined as a formal and explicit specification of a shared conceptualization of a domain of interest. The work presented here introduces a set of interoperable algorithms that can use domain and ontological information to improve information-retrieval processes. This work presents an ontology-based information-retrieval system for the biomedical domain. This system, with which some experiments have been carried out that are described in this paper, is based on the use of domain ontologies for the creation and normalization of lightweight ontologies that represent user preferences in a determined domain in order to improve information-retrieval processes.

Ecophysiological variation of transpiration of pine forests: synthesis of new and published results

Treesearch

Pantana Tor-ngern; Ram Oren; Andrew C. Oishi; Joshua M. Uebelherr; Sari Palmroth; Lasse Tarvainen; Mikaell Ottosson-Löfvenius; Sune Linder; Jean-Christophe Domec; Torgny Näsholm

2017-01-01

Canopy transpiration (EC) is a large fraction of evapotranspiration, integrating physical and biological processes within the energy, water, and carbon cycles of forests. Quantifying EC is of both scientific and practical importance, providing information relevant to...

The bioelectric code: An ancient computational medium for dynamic control of growth and form.

PubMed

Levin, Michael; Martyniuk, Christopher J

2018-02-01

What determines large-scale anatomy? DNA does not directly specify geometrical arrangements of tissues and organs, and a process of encoding and decoding for morphogenesis is required. Moreover, many species can regenerate and remodel their structure despite drastic injury. The ability to obtain the correct target morphology from a diversity of initial conditions reveals that the morphogenetic code implements a rich system of pattern-homeostatic processes. Here, we describe an important mechanism by which cellular networks implement pattern regulation and plasticity: bioelectricity. All cells, not only nerves and muscles, produce and sense electrical signals; in vivo, these processes form bioelectric circuits that harness individual cell behaviors toward specific anatomical endpoints. We review emerging progress in reading and re-writing anatomical information encoded in bioelectrical states, and discuss the approaches to this problem from the perspectives of information theory, dynamical systems, and computational neuroscience. Cracking the bioelectric code will enable much-improved control over biological patterning, advancing basic evolutionary developmental biology as well as enabling numerous applications in regenerative medicine and synthetic bioengineering. Copyright © 2017 Elsevier B.V. All rights reserved.

WE-DE-202-00: Connecting Radiation Physics with Computational Biology

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

NONE

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

Optimal Information Processing in Biochemical Networks

NASA Astrophysics Data System (ADS)

Wiggins, Chris

2012-02-01

A variety of experimental results over the past decades provide examples of near-optimal information processing in biological networks, including in biochemical and transcriptional regulatory networks. Computing information-theoretic quantities requires first choosing or computing the joint probability distribution describing multiple nodes in such a network --- for example, representing the probability distribution of finding an integer copy number of each of two interacting reactants or gene products while respecting the `intrinsic' small copy number noise constraining information transmission at the scale of the cell. I'll given an overview of some recent analytic and numerical work facilitating calculation of such joint distributions and the associated information, which in turn makes possible numerical optimization of information flow in models of noisy regulatory and biochemical networks. Illustrating cases include quantification of form-function relations, ideal design of regulatory cascades, and response to oscillatory driving.

Developmental Gene Regulation and Mechanisms of Evolution

NASA Technical Reports Server (NTRS)

1998-01-01

The Marine Biological Laboratory and the National Aeronautics and Space Administration have established a cooperative agreement with the formation of a Center for Advanced Studies 'in the Space Life Sciences (CASSLS) at the MBL. This Center serves as an interface between NASA and the basic science community, addressing issues of mutual interest. The Center for Advanced Studies 'in the Space Life Sciences provides a forum for scientists to think and discuss, often for the first time, the role that gravity and aspects of spaceflight may play 'in fundamental cellular and physiologic processes. In addition the Center will sponsor discussions on evolutionary biology. These interactions will inform the community of research opportunities that are of interest to NASA. This workshop is one of a series of symposia, workshops and seminars that will be held at the MBL to advise NASA on a wide variety of topics in the life sciences, including cell biology, developmental biology, mg evolutionary biology, molecular biology, neurobiology, plant biology and systems biology.

Bipartite graphs in systems biology and medicine: a survey of methods and applications.

PubMed

Pavlopoulos, Georgios A; Kontou, Panagiota I; Pavlopoulou, Athanasia; Bouyioukos, Costas; Markou, Evripides; Bagos, Pantelis G

2018-04-01

The latest advances in high-throughput techniques during the past decade allowed the systems biology field to expand significantly. Today, the focus of biologists has shifted from the study of individual biological components to the study of complex biological systems and their dynamics at a larger scale. Through the discovery of novel bioentity relationships, researchers reveal new information about biological functions and processes. Graphs are widely used to represent bioentities such as proteins, genes, small molecules, ligands, and others such as nodes and their connections as edges within a network. In this review, special focus is given to the usability of bipartite graphs and their impact on the field of network biology and medicine. Furthermore, their topological properties and how these can be applied to certain biological case studies are discussed. Finally, available methodologies and software are presented, and useful insights on how bipartite graphs can shape the path toward the solution of challenging biological problems are provided.

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

PubMed Central

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

2016-01-01

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

The peripheral blood proteome signature of idiopathic pulmonary fibrosis is distinct from normal and is associated with novel immunological processes.

PubMed

O'Dwyer, David N; Norman, Katy C; Xia, Meng; Huang, Yong; Gurczynski, Stephen J; Ashley, Shanna L; White, Eric S; Flaherty, Kevin R; Martinez, Fernando J; Murray, Susan; Noth, Imre; Arnold, Kelly B; Moore, Bethany B

2017-04-25

Idiopathic pulmonary fibrosis (IPF) is a progressive and fatal interstitial pneumonia. The disease pathophysiology is poorly understood and the etiology remains unclear. Recent advances have generated new therapies and improved knowledge of the natural history of IPF. These gains have been brokered by advances in technology and improved insight into the role of various genes in mediating disease, but gene expression and protein levels do not always correlate. Thus, in this paper we apply a novel large scale high throughput aptamer approach to identify more than 1100 proteins in the peripheral blood of well-characterized IPF patients and normal volunteers. We use systems biology approaches to identify a unique IPF proteome signature and give insight into biological processes driving IPF. We found IPF plasma to be altered and enriched for proteins involved in defense response, wound healing and protein phosphorylation when compared to normal human plasma. Analysis also revealed a minimal protein signature that differentiated IPF patients from normal controls, which may allow for accurate diagnosis of IPF based on easily-accessible peripheral blood. This report introduces large scale unbiased protein discovery analysis to IPF and describes distinct biological processes that further inform disease biology.

First-principles modeling of biological systems and structure-based drug-design.

PubMed

Sgrignani, Jacopo; Magistrato, Alessandra

2013-03-01

Molecular modeling techniques play a relevant role in drug design providing detailed information at atomistic level on the structural, dynamical, mechanistic and electronic properties of biological systems involved in diseases' onset, integrating and supporting commonly used experimental approaches. These information are often not accessible to the experimental techniques taken singularly, but are of crucial importance for drug design. Due to the enormous increase of the computer power in the last decades, quantum mechanical (QM) or first-principles-based methods have become often used to address biological issues of pharmaceutical relevance, providing relevant information for drug design. Due to their complexity and their size, biological systems are often investigated by means of a mixed quantum-classical (QM/MM) approach, which treats at an accurate QM level a limited chemically relevant portion of the system and at the molecular mechanics (MM) level the remaining of the biomolecule and its environment. This method provides a good compromise between computational cost and accuracy, allowing to characterize the properties of the biological system and the (free) energy landscape of the process in study with the accuracy of a QM description. In this review, after a brief introduction of QM and QM/MM methods, we will discuss few representative examples, taken from our work, of the application of these methods in the study of metallo-enzymes of pharmaceutical interest, of metal-containing anticancer drugs targeting the DNA as well as of neurodegenerative diseases. The information obtained from these studies may provide the basis for a rationale structure-based drug design of new and more efficient inhibitors or drugs.

KA-SB: from data integration to large scale reasoning

PubMed Central

Roldán-García, María del Mar; Navas-Delgado, Ismael; Kerzazi, Amine; Chniber, Othmane; Molina-Castro, Joaquín; Aldana-Montes, José F

2009-01-01

Background The analysis of information in the biological domain is usually focused on the analysis of data from single on-line data sources. Unfortunately, studying a biological process requires having access to disperse, heterogeneous, autonomous data sources. In this context, an analysis of the information is not possible without the integration of such data. Methods KA-SB is a querying and analysis system for final users based on combining a data integration solution with a reasoner. Thus, the tool has been created with a process divided into two steps: 1) KOMF, the Khaos Ontology-based Mediator Framework, is used to retrieve information from heterogeneous and distributed databases; 2) the integrated information is crystallized in a (persistent and high performance) reasoner (DBOWL). This information could be further analyzed later (by means of querying and reasoning). Results In this paper we present a novel system that combines the use of a mediation system with the reasoning capabilities of a large scale reasoner to provide a way of finding new knowledge and of analyzing the integrated information from different databases, which is retrieved as a set of ontology instances. This tool uses a graphical query interface to build user queries easily, which shows a graphical representation of the ontology and allows users o build queries by clicking on the ontology concepts. Conclusion These kinds of systems (based on KOMF) will provide users with very large amounts of information (interpreted as ontology instances once retrieved), which cannot be managed using traditional main memory-based reasoners. We propose a process for creating persistent and scalable knowledgebases from sets of OWL instances obtained by integrating heterogeneous data sources with KOMF. This process has been applied to develop a demo tool , which uses the BioPax Level 3 ontology as the integration schema, and integrates UNIPROT, KEGG, CHEBI, BRENDA and SABIORK databases. PMID:19796402

XML-based approaches for the integration of heterogeneous bio-molecular data.

PubMed

Mesiti, Marco; Jiménez-Ruiz, Ernesto; Sanz, Ismael; Berlanga-Llavori, Rafael; Perlasca, Paolo; Valentini, Giorgio; Manset, David

2009-10-15

The today's public database infrastructure spans a very large collection of heterogeneous biological data, opening new opportunities for molecular biology, bio-medical and bioinformatics research, but raising also new problems for their integration and computational processing. In this paper we survey the most interesting and novel approaches for the representation, integration and management of different kinds of biological data by exploiting XML and the related recommendations and approaches. Moreover, we present new and interesting cutting edge approaches for the appropriate management of heterogeneous biological data represented through XML. XML has succeeded in the integration of heterogeneous biomolecular information, and has established itself as the syntactic glue for biological data sources. Nevertheless, a large variety of XML-based data formats have been proposed, thus resulting in a difficult effective integration of bioinformatics data schemes. The adoption of a few semantic-rich standard formats is urgent to achieve a seamless integration of the current biological resources.

On the search for design principles in biological systems.

PubMed

Poyatos, Juan F

2012-01-01

The search for basic concepts and underlying principles was at the core of the systems approach to science and technology. This approach was somehow abandoned in mainstream biology after its initial proposal, due to the rise and success of molecular biology. This situation has changed. The accumulated knowledge of decades of molecular studies in combination with new technological advances, while further highlighting the intricacies of natural systems, is also bringing back the quest-for-principles research program. Here, I present two lessons that I derived from my own quest: the importance of studying biological information processing to identify common principles in seemingly unrelated contexts and the adequacy of using known design principles at one level of biological organization as a valuable tool to help recognizing principles at an alternative one. These and additional lessons should contribute to the ultimate goal of establishing principles able to integrate the many scales of biological complexity.

Development of a software tool to support chemical and biological terrorism intelligence analysis

NASA Astrophysics Data System (ADS)

Hunt, Allen R.; Foreman, William

1997-01-01

AKELA has developed a software tool which uses a systems analytic approach to model the critical processes which support the acquisition of biological and chemical weapons by terrorist organizations. This tool has four major components. The first is a procedural expert system which describes the weapon acquisition process. It shows the relationship between the stages a group goes through to acquire and use a weapon, and the activities in each stage required to be successful. It applies to both state sponsored and small group acquisition. An important part of this expert system is an analysis of the acquisition process which is embodied in a list of observables of weapon acquisition activity. These observables are cues for intelligence collection The second component is a detailed glossary of technical terms which helps analysts with a non- technical background understand the potential relevance of collected information. The third component is a linking capability which shows where technical terms apply to the parts of the acquisition process. The final component is a simple, intuitive user interface which shows a picture of the entire process at a glance and lets the user move quickly to get more detailed information. This paper explains e each of these five model components.

EEG theta and Mu oscillations during perception of human and robot actions

PubMed Central

Urgen, Burcu A.; Plank, Markus; Ishiguro, Hiroshi; Poizner, Howard; Saygin, Ayse P.

2013-01-01

The perception of others’ actions supports important skills such as communication, intention understanding, and empathy. Are mechanisms of action processing in the human brain specifically tuned to process biological agents? Humanoid robots can perform recognizable actions, but can look and move differently from humans, and as such, can be used in experiments to address such questions. Here, we recorded EEG as participants viewed actions performed by three agents. In the Human condition, the agent had biological appearance and motion. The other two conditions featured a state-of-the-art robot in two different appearances: Android, which had biological appearance but mechanical motion, and Robot, which had mechanical appearance and motion. We explored whether sensorimotor mu (8–13 Hz) and frontal theta (4–8 Hz) activity exhibited selectivity for biological entities, in particular for whether the visual appearance and/or the motion of the observed agent was biological. Sensorimotor mu suppression has been linked to the motor simulation aspect of action processing (and the human mirror neuron system, MNS), and frontal theta to semantic and memory-related aspects. For all three agents, action observation induced significant attenuation in the power of mu oscillations, with no difference between agents. Thus, mu suppression, considered an index of MNS activity, does not appear to be selective for biological agents. Observation of the Robot resulted in greater frontal theta activity compared to the Android and the Human, whereas the latter two did not differ from each other. Frontal theta thus appears to be sensitive to visual appearance, suggesting agents that are not sufficiently biological in appearance may result in greater memory processing demands for the observer. Studies combining robotics and neuroscience such as this one can allow us to explore neural basis of action processing on the one hand, and inform the design of social robots on the other. PMID:24348375

EEG theta and Mu oscillations during perception of human and robot actions.

PubMed

Urgen, Burcu A; Plank, Markus; Ishiguro, Hiroshi; Poizner, Howard; Saygin, Ayse P

2013-01-01

The perception of others' actions supports important skills such as communication, intention understanding, and empathy. Are mechanisms of action processing in the human brain specifically tuned to process biological agents? Humanoid robots can perform recognizable actions, but can look and move differently from humans, and as such, can be used in experiments to address such questions. Here, we recorded EEG as participants viewed actions performed by three agents. In the Human condition, the agent had biological appearance and motion. The other two conditions featured a state-of-the-art robot in two different appearances: Android, which had biological appearance but mechanical motion, and Robot, which had mechanical appearance and motion. We explored whether sensorimotor mu (8-13 Hz) and frontal theta (4-8 Hz) activity exhibited selectivity for biological entities, in particular for whether the visual appearance and/or the motion of the observed agent was biological. Sensorimotor mu suppression has been linked to the motor simulation aspect of action processing (and the human mirror neuron system, MNS), and frontal theta to semantic and memory-related aspects. For all three agents, action observation induced significant attenuation in the power of mu oscillations, with no difference between agents. Thus, mu suppression, considered an index of MNS activity, does not appear to be selective for biological agents. Observation of the Robot resulted in greater frontal theta activity compared to the Android and the Human, whereas the latter two did not differ from each other. Frontal theta thus appears to be sensitive to visual appearance, suggesting agents that are not sufficiently biological in appearance may result in greater memory processing demands for the observer. Studies combining robotics and neuroscience such as this one can allow us to explore neural basis of action processing on the one hand, and inform the design of social robots on the other.

Toward the First Data Acquisition Standard in Synthetic Biology.

PubMed

Sainz de Murieta, Iñaki; Bultelle, Matthieu; Kitney, Richard I

2016-08-19

This paper describes the development of a new data acquisition standard for synthetic biology. This comprises the creation of a methodology that is designed to capture all the data, metadata, and protocol information associated with biopart characterization experiments. The new standard, called DICOM-SB, is based on the highly successful Digital Imaging and Communications in Medicine (DICOM) standard in medicine. A data model is described which has been specifically developed for synthetic biology. The model is a modular, extensible data model for the experimental process, which can optimize data storage for large amounts of data. DICOM-SB also includes services orientated toward the automatic exchange of data and information between modalities and repositories. DICOM-SB has been developed in the context of systematic design in synthetic biology, which is based on the engineering principles of modularity, standardization, and characterization. The systematic design approach utilizes the design, build, test, and learn design cycle paradigm. DICOM-SB has been designed to be compatible with and complementary to other standards in synthetic biology, including SBOL. In this regard, the software provides effective interoperability. The new standard has been tested by experiments and data exchange between Nanyang Technological University in Singapore and Imperial College London.

[Prospects for Application of Gases and Gas Hydrates to Cryopreservation].

PubMed

Shishova, N V; Fesenko, E E

2015-01-01

In the present review, we tried to evaluate the known properties of gas hydrates and gases participating in the formation of gas hydrates from the point of view of the mechanisms of cryoinjury and cryoprotection, to consider the papers on freezing biological materials in the presence of inert gases, and to analyze the perspectives for the development of this direction. For the purpose, we searched for the information on the physical properties of gases and gas hydrates, compared processes occured during the formation of gas hydrates and water ice, analyzed the influence of the formation and growth of gas hydrates on the structure of biological objects. We prepared a short review on the biological effects of xenon, krypton, argon, carbon dioxide, hydrogen sulfide, and carbon monoxide especially on hypothermal conditions and probable application of these properties in cryopreservation technologies. The description of the existing experiments on cryopreservation of biological objects with the use of gases was analyzed. On the basis of the information we found, the most perspective directions of work in the field of cryopreservation of biological objects with the use of gases were outlined. An attempt was made to forecast the potential problems in this field.

Mechanism on brain information processing: Energy coding

NASA Astrophysics Data System (ADS)

Wang, Rubin; Zhang, Zhikang; Jiao, Xianfa

2006-09-01

According to the experimental result of signal transmission and neuronal energetic demands being tightly coupled to information coding in the cerebral cortex, the authors present a brand new scientific theory that offers a unique mechanism for brain information processing. They demonstrate that the neural coding produced by the activity of the brain is well described by the theory of energy coding. Due to the energy coding model's ability to reveal mechanisms of brain information processing based upon known biophysical properties, they cannot only reproduce various experimental results of neuroelectrophysiology but also quantitatively explain the recent experimental results from neuroscientists at Yale University by means of the principle of energy coding. Due to the theory of energy coding to bridge the gap between functional connections within a biological neural network and energetic consumption, they estimate that the theory has very important consequences for quantitative research of cognitive function.

The heparanome--the enigma of encoding and decoding heparan sulfate sulfation.

PubMed

Lamanna, William C; Kalus, Ina; Padva, Michael; Baldwin, Rebecca J; Merry, Catherine L R; Dierks, Thomas

2007-04-30

Heparan sulfate (HS) is a cell surface carbohydrate polymer modified with sulfate moieties whose highly ordered composition is central to directing specific cell signaling events. The ability of the cell to generate these information rich glycans with such specificity has opened up a new field of "heparanomics" which seeks to understand the systems involved in generating these cell type and developmental stage specific HS sulfation patterns. Unlike other instances where biological information is encrypted as linear sequences in molecules such as DNA, HS sulfation patterns are generated through a non-template driven process. Thus, deciphering the sulfation code and the dynamic nature of its generation has posed a new challenge to system biologists. The recent discovery of two sulfatases, Sulf1 and Sulf2, with the unique ability to edit sulfation patterns at the cell surface, has opened up a new dimension as to how we understand the regulation of HS sulfation patterning and pattern-dependent cell signaling events. This review will focus on the functional relationship between HS sulfation patterning and biological processes. Special attention will be given to Sulf1 and Sulf2 and how these key editing enzymes might act in concert with the HS biosynthetic enzymes to generate and regulate specific HS sulfation patterns in vivo. We will further explore the use of knock out mice as biological models for understanding the dynamic systems involved in generating HS sulfation patterns and their biological relevance. A brief overview of new technologies and innovations summarizes advances in the systems biology field for understanding non-template molecular networks and their influence on the "heparanome".

Complexity and Entropy Analysis of DNMT1 Gene

USDA-ARS?s Scientific Manuscript database

Background: The application of complexity information on DNA sequence and protein in biological processes are well established in this study. Available sequences for DNMT1 gene, which is a maintenance methyltransferase is responsible for copying DNA methylation patterns to the daughter strands durin...

Biomimetics: its practice and theory

PubMed Central

Vincent, Julian F.V; Bogatyreva, Olga A; Bogatyrev, Nikolaj R; Bowyer, Adrian; Pahl, Anja-Karina

2006-01-01

Biomimetics, a name coined by Otto Schmitt in the 1950s for the transfer of ideas and analogues from biology to technology, has produced some significant and successful devices and concepts in the past 50 years, but is still empirical. We show that TRIZ, the Russian system of problem solving, can be adapted to illuminate and manipulate this process of transfer. Analysis using TRIZ shows that there is only 12% similarity between biology and technology in the principles which solutions to problems illustrate, and while technology solves problems largely by manipulating usage of energy, biology uses information and structure, two factors largely ignored by technology. PMID:16849244

PathJam: a new service for integrating biological pathway information.

PubMed

Glez-Peña, Daniel; Reboiro-Jato, Miguel; Domínguez, Rubén; Gómez-López, Gonzalo; Pisano, David G; Fdez-Riverola, Florentino

2010-10-28

Biological pathways are crucial to much of the scientific research today including the study of specific biological processes related with human diseases. PathJam is a new comprehensive and freely accessible web-server application integrating scattered human pathway annotation from several public sources. The tool has been designed for both (i) being intuitive for wet-lab users providing statistical enrichment analysis of pathway annotations and (ii) giving support to the development of new integrative pathway applications. PathJam’s unique features and advantages include interactive graphs linking pathways and genes of interest, downloadable results in fully compatible formats, GSEA compatible output files and a standardized RESTful API.

Cortical neurons sensitive to combinations of information-bearing elements of biosonar signals in the mustache bat.

PubMed

Suga, N; O'Neill, W E; Manabe, T

1978-05-19

The auditory cortex of the mustache bat, Pteronotus parnellii rubiginosus, is composed of functional divisions which are differently organized to be suited for processing the elements of its biosonar signal according to their biological significance. Unlike the Doppler-shifted-CF (constant frequency) processing area, the area processing the frequency-modulated components does not show clear tonotopic and amplitopic representations, but consists of several clusters of neurons, each of which is sensitive to a particular combination (or combinations) of information-bearing elements of the biosonar signal and echoes. The response properties of neurons in the major clusters indicate that processing of information carried by the frequency-modulated components of echoes is facilitated by the first harmonic of the emitted biosonar signal. The properties of some of these neurons suggest that they are tuned to a target which has a particular cross-sectional area and which is located at a particular distance.

Polymer application for separation/filtration of biological active compounds

NASA Astrophysics Data System (ADS)

Tylkowski, B.; Tsibranska, I.

2017-06-01

Membrane technology is an important part of the engineer's toolbox. This is especially true for industries that process food and other products with their primary source from nature. This review is focused on ongoing development work using membrane technologies for concentration and separation of biologically active compounds, such as polyphenols and flavonoids. We provide the readers not only with the last results achieve in this field but also, we deliver detailed information about the membrane types and polymers used for their preparation.

Multiscale Physical and Biological Dynamics in the Philippines Archipelago: Predictions and Processes

DTIC Science & Technology

2011-01-01

for failing to comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE 2010 2. REPORT...TYPE 3. DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE MultiscalePhysical and Biological Dynamics in the Philippines Archipelago...chemistry,  and   radioisotopes  in  the  Southeast  Asian  Basins.  J.  Geophys.  Res.,  91:14,345-­‐14,354.   Cabrera

Two-Dimensional Spectroscopy Is Being Used to Address Core Scientific Questions in Biology and Materials Science.

PubMed

Petti, Megan K; Lomont, Justin P; Maj, Michał; Zanni, Martin T

2018-02-15

Two-dimensional spectroscopy is a powerful tool for extracting structural and dynamic information from a wide range of chemical systems. We provide a brief overview of the ways in which two-dimensional visible and infrared spectroscopies are being applied to elucidate fundamental details of important processes in biological and materials science. The topics covered include amyloid proteins, photosynthetic complexes, ion channels, photovoltaics, batteries, as well as a variety of promising new methods in two-dimensional spectroscopy.

3-D components of a biological neural network visualized in computer generated imagery. I - Macular receptive field organization

NASA Technical Reports Server (NTRS)

Ross, Muriel D.; Cutler, Lynn; Meyer, Glenn; Lam, Tony; Vaziri, Parshaw

1990-01-01

Computer-assisted, 3-dimensional reconstructions of macular receptive fields and of their linkages into a neural network have revealed new information about macular functional organization. Both type I and type II hair cells are included in the receptive fields. The fields are rounded, oblong, or elongated, but gradations between categories are common. Cell polarizations are divergent. Morphologically, each calyx of oblong and elongated fields appears to be an information processing site. Intrinsic modulation of information processing is extensive and varies with the kind of field. Each reconstructed field differs in detail from every other, suggesting that an element of randomness is introduced developmentally and contributes to endorgan adaptability.

Recent advances in mass spectrometry-based approaches for proteomics and biologics: Great contribution for developing therapeutic antibodies.

PubMed

Iwamoto, Noriko; Shimada, Takashi

2018-05-01

Since the turn of the century, mass spectrometry (MS) technologies have continued to improve dramatically, and advanced strategies that were impossible a decade ago are increasingly becoming available. The basic characteristics behind these advancements are MS resolution, quantitative accuracy, and information science for appropriate data processing. The spectral data from MS contain various types of information. The benefits of improving the resolution of MS data include accurate molecular structural-derived information, and as a result, we can obtain a refined biomolecular structure determination in a sequential and large-scale manner. Moreover, in MS data, not only accurate structural information but also the generated ion amount plays an important rule. This progress has greatly contributed a research field that captures biological events as a system by comprehensively tracing the various changes in biomolecular dynamics. The sequential changes of proteome expression in biological pathways are very essential, and the amounts of the changes often directly become the targets of drug discovery or indicators of clinical efficacy. To take this proteomic approach, it is necessary to separate the individual MS spectra derived from each biomolecule in the complexed biological samples. MS itself is not so infinite to perform the all peak separation, and we should consider improving the methods for sample processing and purification to make them suitable for injection into MS. The above-described characteristics can only be achieved using MS with any analytical instrument. Moreover, MS is expected to be applied and expand into many fields, not only basic life sciences but also forensic medicine, plant sciences, materials, and natural products. In this review, we focus on the technical fundamentals and future aspects of the strategies for accurate structural identification, structure-indicated quantitation, and on the challenges for pharmacokinetics of high-molecular-weight protein biopharmaceuticals. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Flexible automated approach for quantitative liquid handling of complex biological samples.

PubMed

Palandra, Joe; Weller, David; Hudson, Gary; Li, Jeff; Osgood, Sarah; Hudson, Emily; Zhong, Min; Buchholz, Lisa; Cohen, Lucinda H

2007-11-01

A fully automated protein precipitation technique for biological sample preparation has been developed for the quantitation of drugs in various biological matrixes. All liquid handling during sample preparation was automated using a Hamilton MicroLab Star Robotic workstation, which included the preparation of standards and controls from a Watson laboratory information management system generated work list, shaking of 96-well plates, and vacuum application. Processing time is less than 30 s per sample or approximately 45 min per 96-well plate, which is then immediately ready for injection onto an LC-MS/MS system. An overview of the process workflow is discussed, including the software development. Validation data are also provided, including specific liquid class data as well as comparative data of automated vs manual preparation using both quality controls and actual sample data. The efficiencies gained from this automated approach are described.

Time rescaling and pattern formation in biological evolution.

PubMed

Igamberdiev, Abir U

2014-09-01

Biological evolution is analyzed as a process of continuous measurement in which biosystems interpret themselves in the environment resulting in changes of both. This leads to rescaling of internal time (heterochrony) followed by spatial reconstructions of morphology (heterotopy). The logical precondition of evolution is the incompleteness of biosystem's internal description, while the physical precondition is the uncertainty of quantum measurement. The process of evolution is based on perpetual changes in interpretation of information in the changing world. In this interpretation the external biospheric gradients are used for establishment of new features of organization. It is concluded that biological evolution involves the anticipatory epigenetic changes in the interpretation of genetic symbolism which cannot generally be forecasted but can provide canalization of structural transformations defined by the existing organization and leading to predictable patterns of form generation. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Fluorescence correlation spectroscopy: novel variations of an established technique.

PubMed

Haustein, Elke; Schwille, Petra

2007-01-01

Fluorescence correlation spectroscopy (FCS) is one of the major biophysical techniques used for unraveling molecular interactions in vitro and in vivo. It allows minimally invasive study of dynamic processes in biological specimens with extremely high temporal and spatial resolution. By recording and correlating the fluorescence fluctuations of single labeled molecules through the exciting laser beam, FCS gives information on molecular mobility and photophysical and photochemical reactions. By using dual-color fluorescence cross-correlation, highly specific binding studies can be performed. These have been extended to four reaction partners accessible by multicolor applications. Alternative detection schemes shift accessible time frames to slower processes (e.g., scanning FCS) or higher concentrations (e.g., TIR-FCS). Despite its long tradition, FCS is by no means dated. Rather, it has proven to be a highly versatile technique that can easily be adapted to solve specific biological questions, and it continues to find exciting applications in biology and medicine.

Quasielastic neutron scattering in biology: Theory and applications

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

Vural, Derya; Univ. of Tennessee, Knoxville, TN; Hu, Xiaohu

Neutrons scatter quasielastically from stochastic, diffusive processes, such as overdamped vibrations, localized diffusion and transitions between energy minima. In biological systems, such as proteins and membranes, these relaxation processes are of considerable physical interest. We review here recent methodological advances and applications of quasielastic neutron scattering (QENS) in biology, concentrating on the role of molecular dynamics simulation in generating data with which neutron profiles can be unambiguously interpreted. We examine the use of massively-parallel computers in calculating scattering functions, and the application of Markov state modeling. The decomposition of MD-derived neutron dynamic susceptibilities is described, and the use of thismore » in combination with NMR spectroscopy. We discuss dynamics at very long times, including approximations to the infinite time mean-square displacement and nonequilibrium aspects of single-protein dynamics. Lastly, we examine how neutron scattering and MD can be combined to provide information on lipid nanodomains.« less

Quasielastic neutron scattering in biology: Theory and applications

DOE PAGES

Vural, Derya; Univ. of Tennessee, Knoxville, TN; Hu, Xiaohu; ...

2016-06-15

Neutrons scatter quasielastically from stochastic, diffusive processes, such as overdamped vibrations, localized diffusion and transitions between energy minima. In biological systems, such as proteins and membranes, these relaxation processes are of considerable physical interest. We review here recent methodological advances and applications of quasielastic neutron scattering (QENS) in biology, concentrating on the role of molecular dynamics simulation in generating data with which neutron profiles can be unambiguously interpreted. We examine the use of massively-parallel computers in calculating scattering functions, and the application of Markov state modeling. The decomposition of MD-derived neutron dynamic susceptibilities is described, and the use of thismore » in combination with NMR spectroscopy. We discuss dynamics at very long times, including approximations to the infinite time mean-square displacement and nonequilibrium aspects of single-protein dynamics. Lastly, we examine how neutron scattering and MD can be combined to provide information on lipid nanodomains.« less

Water quality and habitat conditions in upper Midwest streams relative to riparian vegetation and soil characteristics, August 1997 : study design, methods, and data

USGS Publications Warehouse

Sorenson, S.K.; Porter, S.D.; Akers, K.B.; Harris, M.A.; Kalkhoff, S.J.; Lee, K.E.; Roberts, L.; Terrio, P.J.

1999-01-01

Water-chemistry, biological, and habitat data were collected from 70 sites on Midwestern streams during August 1997 as part of an integrated, regional water-quality assessment by the U.S. Geological Survey National Water-Quality Assessment (NAWQA) Program. The study area includes the Corn Belt region of southern Minnesota, eastern Iowa, and west-central Illinois, one of the most intensive and productive agricultural regions of the world. The focus of the study was to evaluate the condition of woodedriparian zones and the influence of basin soildrainage characteristics on water quality and biological-community responses. This report includes a description of the study design and site-characterization process, sample-collection and processing methods, laboratory methods, quality-assurance procedures, and summaries of data on nutrients, herbicides and metabolites, stream productivity and respiration, biological communities, habitat conditions, and agriculturalchemical and land-use information.

Carbon and nitrogen biogeochemistry in the ocean: A study using stable isotope natural abundance

NASA Technical Reports Server (NTRS)

Rau, G. H.; Desmarais, David J.

1985-01-01

Determining the biogeochemical pathways traveled by carbon and nitrogen in the ocean is fundamental to the understanding of how the ocean participates in the cycling of these elements within the biosphere. Because biological production, metabolism, and respiration can significantly alter the natural abundance of C-13 and N-15, these abundances can provide important information about the nature of these biological processes and their variability in the marine environment. The research initially seeks to characterize the spatial and temporal patterns of stable isotope abundances in organic matter, and to relate these abundances to C and N biogeochemical processes within selected areas of the northeastern Pacific Ocean.

WE-DE-202-02: Are Track Structure Simulations Truly Needed for Radiobiology at the Cellular and Tissue Levels?

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

Stewart, R.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

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

McMahon, S.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

WE-DE-202-01: Connecting Nanoscale Physics to Initial DNA Damage Through Track Structure Simulations

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

Schuemann, J.

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are themore » most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological processes are too complex for a mechanistic approach. Can computer simulations be used to guide future biological research? We will debate the feasibility of explaining biology from a physicists’ perspective. Learning Objectives: Understand the potential applications and limitations of computational methods for dose-response modeling at the molecular, cellular and tissue levels Learn about mechanism of action underlying the induction, repair and biological processing of damage to DNA and other constituents Understand how effects and processes at one biological scale impact on biological processes and outcomes on other scales J. Schuemann, NCI/NIH grantsS. McMahon, Funding: European Commission FP7 (grant EC FP7 MC-IOF-623630)« less

Unfolding single RNA molecules: bridging the gap between equilibrium and non-equilibrium statistical thermodynamics.

PubMed

Bustamante, Carlos

2005-11-01

During the last 15 years, scientists have developed methods that permit the direct mechanical manipulation of individual molecules. Using this approach, they have begun to investigate the effect of force and torque in chemical and biochemical reactions. These studies span from the study of the mechanical properties of macromolecules, to the characterization of molecular motors, to the mechanical unfolding of individual proteins and RNA. Here I present a review of some of our most recent results using mechanical force to unfold individual molecules of RNA. These studies make it possible to follow in real time the trajectory of each molecule as it unfolds and characterize the various intermediates of the reaction. Moreover, if the process takes place reversibly it is possible to extract both kinetic and thermodynamic information from these experiments at the same time that we characterize the forces that maintain the three-dimensional structure of the molecule in solution. These studies bring us closer to the biological unfolding processes in the cell as they simulate in vitro, the mechanical unfolding of RNAs carried out in the cell by helicases. If the unfolding process occurs irreversibly, I show here that single-molecule experiments can still provide equilibrium, thermodynamic information from non-equilibrium data by using recently discovered fluctuation theorems. Such theorems represent a bridge between equilibrium and non-equilibrium statistical mechanics. In fact, first derived in 1997, the first experimental demonstration of the validity of fluctuation theorems was obtained by unfolding mechanically a single molecule of RNA. It is perhaps a sign of the times that important physical results are these days used to extract information about biological systems and that biological systems are being used to test and confirm fundamental new laws in physics.

Annotating novel genes by integrating synthetic lethals and genomic information

PubMed Central

Schöner, Daniel; Kalisch, Markus; Leisner, Christian; Meier, Lukas; Sohrmann, Marc; Faty, Mahamadou; Barral, Yves; Peter, Matthias; Gruissem, Wilhelm; Bühlmann, Peter

2008-01-01

Background Large scale screening for synthetic lethality serves as a common tool in yeast genetics to systematically search for genes that play a role in specific biological processes. Often the amounts of data resulting from a single large scale screen far exceed the capacities of experimental characterization of every identified target. Thus, there is need for computational tools that select promising candidate genes in order to reduce the number of follow-up experiments to a manageable size. Results We analyze synthetic lethality data for arp1 and jnm1, two spindle migration genes, in order to identify novel members in this process. To this end, we use an unsupervised statistical method that integrates additional information from biological data sources, such as gene expression, phenotypic profiling, RNA degradation and sequence similarity. Different from existing methods that require large amounts of synthetic lethal data, our method merely relies on synthetic lethality information from two single screens. Using a Multivariate Gaussian Mixture Model, we determine the best subset of features that assign the target genes to two groups. The approach identifies a small group of genes as candidates involved in spindle migration. Experimental testing confirms the majority of our candidates and we present she1 (YBL031W) as a novel gene involved in spindle migration. We applied the statistical methodology also to TOR2 signaling as another example. Conclusion We demonstrate the general use of Multivariate Gaussian Mixture Modeling for selecting candidate genes for experimental characterization from synthetic lethality data sets. For the given example, integration of different data sources contributes to the identification of genetic interaction partners of arp1 and jnm1 that play a role in the same biological process. PMID:18194531

A Prototype System for Retrieval of Gene Functional Information

PubMed Central

Folk, Lillian C.; Patrick, Timothy B.; Pattison, James S.; Wolfinger, Russell D.; Mitchell, Joyce A.

2003-01-01

Microarrays allow researchers to gather data about the expression patterns of thousands of genes simultaneously. Statistical analysis can reveal which genes show statistically significant results. Making biological sense of those results requires the retrieval of functional information about the genes thus identified, typically a manual gene-by-gene retrieval of information from various on-line databases. For experiments generating thousands of genes of interest, retrieval of functional information can become a significant bottleneck. To address this issue, we are currently developing a prototype system to automate the process of retrieval of functional information from multiple on-line sources. PMID:14728346

Data Mining in Cyber Operations

DTIC Science & Technology

2014-07-01

information processing units intended to mimic the network of neurons in the human brain for performing pattern recognition  Self- organizing maps (SOM...patterns are mined from in order to influence the learning model . An exploratory attack does not alter the training process , but rather uses other...New Jersey: Prentice Hall. 21) Kohonen, T. (1982). Self- organized formation of topologically correct feature maps. Biological Cybernetics , 43, 59–69

Model-based design of experiments for cellular processes.

PubMed

Chakrabarty, Ankush; Buzzard, Gregery T; Rundell, Ann E

2013-01-01

Model-based design of experiments (MBDOE) assists in the planning of highly effective and efficient experiments. Although the foundations of this field are well-established, the application of these techniques to understand cellular processes is a fertile and rapidly advancing area as the community seeks to understand ever more complex cellular processes and systems. This review discusses the MBDOE paradigm along with applications and challenges within the context of cellular processes and systems. It also provides a brief tutorial on Fisher information matrix (FIM)-based and Bayesian experiment design methods along with an overview of existing software packages and computational advances that support MBDOE application and adoption within the Systems Biology community. As cell-based products and biologics progress into the commercial sector, it is anticipated that MBDOE will become an essential practice for design, quality control, and production. Copyright © 2013 Wiley Periodicals, Inc.

cPath: open source software for collecting, storing, and querying biological pathways

PubMed Central

Cerami, Ethan G; Bader, Gary D; Gross, Benjamin E; Sander, Chris

2006-01-01

Background Biological pathways, including metabolic pathways, protein interaction networks, signal transduction pathways, and gene regulatory networks, are currently represented in over 220 diverse databases. These data are crucial for the study of specific biological processes, including human diseases. Standard exchange formats for pathway information, such as BioPAX, CellML, SBML and PSI-MI, enable convenient collection of this data for biological research, but mechanisms for common storage and communication are required. Results We have developed cPath, an open source database and web application for collecting, storing, and querying biological pathway data. cPath makes it easy to aggregate custom pathway data sets available in standard exchange formats from multiple databases, present pathway data to biologists via a customizable web interface, and export pathway data via a web service to third-party software, such as Cytoscape, for visualization and analysis. cPath is software only, and does not include new pathway information. Key features include: a built-in identifier mapping service for linking identical interactors and linking to external resources; built-in support for PSI-MI and BioPAX standard pathway exchange formats; a web service interface for searching and retrieving pathway data sets; and thorough documentation. The cPath software is freely available under the LGPL open source license for academic and commercial use. Conclusion cPath is a robust, scalable, modular, professional-grade software platform for collecting, storing, and querying biological pathways. It can serve as the core data handling component in information systems for pathway visualization, analysis and modeling. PMID:17101041

Numeric promoter description - A comparative view on concepts and general application.

PubMed

Beier, Rico; Labudde, Dirk

2016-01-01

Nucleic acid molecules play a key role in a variety of biological processes. Starting from storage and transfer tasks, this also comprises the triggering of biological processes, regulatory effects and the active influence gained by target binding. Based on the experimental output (in this case promoter sequences), further in silico analyses aid in gaining new insights into these processes and interactions. The numerical description of nucleic acids thereby constitutes a bridge between the concrete biological issues and the analytical methods. Hence, this study compares 26 descriptor sets obtained by applying well-known numerical description concepts to an established dataset of 38 DNA promoter sequences. The suitability of the description sets was evaluated by computing partial least squares regression models and assessing the model accuracy. We conclude that the major importance regarding the descriptive power is attached to positional information rather than to explicitly incorporated physico-chemical information, since a sufficient amount of implicit physico-chemical information is already encoded in the nucleobase classification. The regression models especially benefited from employing the information that is encoded in the sequential and structural neighborhood of the nucleobases. Thus, the analyses of n-grams (short fragments of length n) suggested that they are valuable descriptors for DNA target interactions. A mixed n-gram descriptor set thereby yielded the best description of the promoter sequences. The corresponding regression model was checked and found to be plausible as it was able to reproduce the characteristic binding motifs of promoter sequences in a reasonable degree. As most functional nucleic acids are based on the principle of molecular recognition, the findings are not restricted to promoter sequences, but can rather be transferred to other kinds of functional nucleic acids. Thus, the concepts presented in this study could provide advantages for future nucleic acid-based technologies, like biosensoring, therapeutics and molecular imaging. Copyright © 2015 Elsevier Inc. All rights reserved.

ART-ML: a new markup language for modelling and representation of biological processes in cardiovascular diseases.

PubMed

Karvounis, E C; Exarchos, T P; Fotiou, E; Sakellarios, A I; Iliopoulou, D; Koutsouris, D; Fotiadis, D I

2013-01-01

With an ever increasing number of biological models available on the internet, a standardized modelling framework is required to allow information to be accessed and visualized. In this paper we propose a novel Extensible Markup Language (XML) based format called ART-ML that aims at supporting the interoperability and the reuse of models of geometry, blood flow, plaque progression and stent modelling, exported by any cardiovascular disease modelling software. ART-ML has been developed and tested using ARTool. ARTool is a platform for the automatic processing of various image modalities of coronary and carotid arteries. The images and their content are fused to develop morphological models of the arteries in 3D representations. All the above described procedures integrate disparate data formats, protocols and tools. ART-ML proposes a representation way, expanding ARTool, for interpretability of the individual resources, creating a standard unified model for the description of data and, consequently, a format for their exchange and representation that is machine independent. More specifically, ARTool platform incorporates efficient algorithms which are able to perform blood flow simulations and atherosclerotic plaque evolution modelling. Integration of data layers between different modules within ARTool are based upon the interchange of information included in the ART-ML model repository. ART-ML provides a markup representation that enables the representation and management of embedded models within the cardiovascular disease modelling platform, the storage and interchange of well-defined information. The corresponding ART-ML model incorporates all relevant information regarding geometry, blood flow, plaque progression and stent modelling procedures. All created models are stored in a model repository database which is accessible to the research community using efficient web interfaces, enabling the interoperability of any cardiovascular disease modelling software models. ART-ML can be used as a reference ML model in multiscale simulations of plaque formation and progression, incorporating all scales of the biological processes.

A Ratiometric Two-Photon Fluorescent Probe for Tracking the Lysosomal ATP Level: Direct in cellulo Observation of Lysosomal Membrane Fusion Processes.

PubMed

Jun, Yong Woong; Wang, Taejun; Hwang, Sekyu; Kim, Dokyoung; Ma, Donghee; Kim, Ki Hean; Kim, Sungjee; Jung, Junyang; Ahn, Kyo Han

2018-06-05

Vesicles exchange its contents through membrane fusion processes-kiss-and-run and full-collapse fusion. Indirect observation of these fusion processes using artificial vesicles enhanced our understanding on the molecular mechanisms involved. Direct observation of the fusion processes in a real biological system, however, remains a challenge owing to many technical obstacles. We disclose a ratiometric two-photon probe offering real-time tracking of lysosomal ATP with quantitative information for the first time. By applying the probe to two-photon live-cell imaging technique, lysosomal membrane fusion process in cells has been directly observed along with the concentration of its content-lysosomal ATP. Results show that the kiss-and-run process between lysosomes proceeds through repeating transient interactions with gradual content mixing, whereas the full-fusion process occurs at once. Furthermore, it is confirmed that both the fusion processes proceed with conservation of the content. Such a small-molecule probe exerts minimal disturbance and hence has potential for studying various biological processes associated with lysosomal ATP. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Analysis of cellular signal transduction from an information theoretic approach.

PubMed

Uda, Shinsuke; Kuroda, Shinya

2016-03-01

Signal transduction processes the information of various cellular functions, including cell proliferation, differentiation, and death. The information for controlling cell fate is transmitted by concentrations of cellular signaling molecules. However, how much information is transmitted in signaling pathways has thus far not been investigated. Shannon's information theory paves the way to quantitatively analyze information transmission in signaling pathways. The theory has recently been applied to signal transduction, and mutual information of signal transduction has been determined to be a measure of information transmission. We review this work and provide an overview of how signal transduction transmits informational input and exerts biological output. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Modeling the academic performance of medical students in basic sciences and pre-clinical courses: a longitudinal study].

PubMed

Zúñiga, Denisse; Mena, Beltrán; Oliva, Rose; Pedrals, Nuria; Padilla, Oslando; Bitran, Marcela

2009-10-01

The study of predictors of academic performance is relevant for medical education. Most studies of academic performance use global ratings as outcome measure, and do not evaluate the influence of the assessment methods. To model by multivariate analysis, the academic performance of medical considering, besides academic and demographic variables, the methods used to assess students' learning and their preferred modes of information processing. Two hundred seventy two students admitted to the medical school of the Pontificia Universidad Católica de Chile from 2000 to 2003. Six groups of variables were studied to model the students' performance in five basic science courses (Anatomy, Biology, Calculus, Chemistry and Physics) and two pre-clinical courses (Integrated Medical Clinic I and IT). The assessment methods examined were multiple choice question tests, Objective Structured Clinical Examination and tutor appraisal. The results of the university admission tests (high school grades, mathematics and biology tests), the assessment methods used, the curricular year and previous application to medical school, were predictors of academic performance. The information processing modes influenced academic performance, but only in interaction with other variables. Perception (abstract or concrete) interacted with the assessment methods, and information use (active or reflexive), with sex. The correlation between the real and predicted grades was 0.7. In addition to the academic results obtained prior to university entrance, the methods of assessment used in the university and the information processing modes influence the academic performance of medical students in basic and preclinical courses.

In situ monitoring of biomolecular processes in living systems using surface-enhanced Raman scattering

NASA Astrophysics Data System (ADS)

Altunbek, Mine; Kelestemur, Seda; Culha, Mustafa

2015-12-01

Surface-enhanced Raman scattering (SERS) continues to strive to gather molecular level information from dynamic biological systems. It is our ongoing effort to utilize the technique for understanding of the biomolecular processes in living systems such as eukaryotic and prokaryotic cells. In this study, the technique is investigated to identify cell death mechanisms in 2D and 3D in vitro cell culture models, which is a very important process in tissue engineering and pharmaceutical applications. Second, in situ biofilm formation monitoring is investigated to understand how microorganisms respond to the environmental stimuli, which inferred information can be used to interfere with biofilm formation and fight against their pathogenic activity.

Biological information systems: Evolution as cognition-based information management.

PubMed

Miller, William B

2018-05-01

An alternative biological synthesis is presented that conceptualizes evolutionary biology as an epiphenomenon of integrated self-referential information management. Since all biological information has inherent ambiguity, the systematic assessment of information is required by living organisms to maintain self-identity and homeostatic equipoise in confrontation with environmental challenges. Through their self-referential attachment to information space, cells are the cornerstone of biological action. That individualized assessment of information space permits self-referential, self-organizing niche construction. That deployment of information and its subsequent selection enacted the dominant stable unicellular informational architectures whose biological expressions are the prokaryotic, archaeal, and eukaryotic unicellular forms. Multicellularity represents the collective appraisal of equivocal environmental information through a shared information space. This concerted action can be viewed as systematized information management to improve information quality for the maintenance of preferred homeostatic boundaries among the varied participants. When reiterated in successive scales, this same collaborative exchange of information yields macroscopic organisms as obligatory multicellular holobionts. Cognition-Based Evolution (CBE) upholds that assessment of information precedes biological action, and the deployment of information through integrative self-referential niche construction and natural cellular engineering antecedes selection. Therefore, evolutionary biology can be framed as a complex reciprocating interactome that consists of the assessment, communication, deployment and management of information by self-referential organisms at multiple scales in continuous confrontation with environmental stresses. Copyright © 2017 Elsevier Ltd. All rights reserved.

The significance and scope of evolutionary developmental biology: a vision for the 21st century.

PubMed

Moczek, Armin P; Sears, Karen E; Stollewerk, Angelika; Wittkopp, Patricia J; Diggle, Pamela; Dworkin, Ian; Ledon-Rettig, Cristina; Matus, David Q; Roth, Siegfried; Abouheif, Ehab; Brown, Federico D; Chiu, Chi-Hua; Cohen, C Sarah; Tomaso, Anthony W De; Gilbert, Scott F; Hall, Brian; Love, Alan C; Lyons, Deirdre C; Sanger, Thomas J; Smith, Joel; Specht, Chelsea; Vallejo-Marin, Mario; Extavour, Cassandra G

2015-01-01

Evolutionary developmental biology (evo-devo) has undergone dramatic transformations since its emergence as a distinct discipline. This paper aims to highlight the scope, power, and future promise of evo-devo to transform and unify diverse aspects of biology. We articulate key questions at the core of eleven biological disciplines-from Evolution, Development, Paleontology, and Neurobiology to Cellular and Molecular Biology, Quantitative Genetics, Human Diseases, Ecology, Agriculture and Science Education, and lastly, Evolutionary Developmental Biology itself-and discuss why evo-devo is uniquely situated to substantially improve our ability to find meaningful answers to these fundamental questions. We posit that the tools, concepts, and ways of thinking developed by evo-devo have profound potential to advance, integrate, and unify biological sciences as well as inform policy decisions and illuminate science education. We look to the next generation of evolutionary developmental biologists to help shape this process as we confront the scientific challenges of the 21st century. © 2015 Wiley Periodicals, Inc.

PSI:Biology-Materials Repository: A Biologist’s Resource for Protein Expression Plasmids

PubMed Central

Cormier, Catherine Y.; Park, Jin G.; Fiacco, Michael; Steel, Jason; Hunter, Preston; Kramer, Jason; Singla, Rajeev; LaBaer, Joshua

2011-01-01

The Protein Structure Initiative:Biology-Materials Repository (PSI:Biology-MR; MR; http://psimr.asu.edu) sequence-verifies, annotates, stores, and distributes the protein expression plasmids and vectors created by the Protein Structure Initiative (PSI). The MR has developed an informatics and sample processing pipeline that manages this process for thousands of samples per month from nearly a dozen PSI centers. DNASU (http://dnasu.asu.edu), a freely searchable database, stores the plasmid annotations, which include the full-length sequence, vector information, and associated publications for over 130,000 plasmids created by our laboratory, by the PSI and other consortia, and by individual laboratories for distribution to researchers worldwide. Each plasmid links to external resources, including the PSI Structural Biology Knowledgebase (http://sbkb.org), which facilitates cross-referencing of a particular plasmid to additional protein annotations and experimental data. To expedite and simplify plasmid requests, the MR uses an expedited material transfer agreement (EP-MTA) network, where researchers from network institutions can order and receive PSI plasmids without institutional delays. Currently over 39,000 protein expression plasmids and 78 empty vectors from the PSI are available upon request from DNASU. Overall, the MR’s repository of expression-ready plasmids, its automated pipeline, and the rapid process for receiving and distributing these plasmids more effectively allows the research community to dissect the biological function of proteins whose structures have been studied by the PSI. PMID:21360289

Key Planning Factors for Recovery from a Biological Terrorism Incident

DTIC Science & Technology

2012-08-30

Goals, this document identifies key technical planning areas that may be used to inform subsequent FEMA response and recovery guidance documents. The...expressed herein do not necessarily state or reflect those of their respective organizations or the US Government. The modeling and analysis provided by...responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would

Exosomes and microvesicles: extracellular vesicles for genetic information transfer and gene therapy.

PubMed

Lee, Yi; El Andaloussi, Samir; Wood, Matthew J A

2012-10-15

Exosomes and microvesicles are extracellular nanovesicles released by most but not all cells. They are specifically equipped to mediate intercellular communication via the transfer of genetic information, including the transfer of both coding and non-coding RNAs, to recipient cells. As a result, both exosomes and microvesicles play a fundamental biological role in the regulation of normal physiological as well as aberrant pathological processes, via altered gene regulatory networks and/or via epigenetic programming. For example, microvesicle-mediated genetic transfer can regulate the maintenance of stem cell plasticity and induce beneficial cell phenotype modulation. Alternatively, such vesicles play a role in tumor pathogenesis and the spread of neurodegenerative diseases via the transfer of specific microRNAs and pathogenic proteins. Given this natural property for genetic information transfer, the possibility of exploiting these vesicles for therapeutic purposes is now being investigated. Stem cell-derived microvesicles appear to be naturally equipped to mediate tissue regeneration under certain conditions, while recent evidence suggests that exosomes might be harnessed for the targeted delivery of human genetic therapies via the introduction of exogenous genetic cargoes such as siRNA. Thus, extracellular vesicles are emerging as potent genetic information transfer agents underpinning a range of biological processes and with therapeutic potential.

Information processing in echo state networks at the edge of chaos.

PubMed

Boedecker, Joschka; Obst, Oliver; Lizier, Joseph T; Mayer, N Michael; Asada, Minoru

2012-09-01

We investigate information processing in randomly connected recurrent neural networks. It has been shown previously that the computational capabilities of these networks are maximized when the recurrent layer is close to the border between a stable and an unstable dynamics regime, the so called edge of chaos. The reasons, however, for this maximized performance are not completely understood. We adopt an information-theoretical framework and are for the first time able to quantify the computational capabilities between elements of these networks directly as they undergo the phase transition to chaos. Specifically, we present evidence that both information transfer and storage in the recurrent layer are maximized close to this phase transition, providing an explanation for why guiding the recurrent layer toward the edge of chaos is computationally useful. As a consequence, our study suggests self-organized ways of improving performance in recurrent neural networks, driven by input data. Moreover, the networks we study share important features with biological systems such as feedback connections and online computation on input streams. A key example is the cerebral cortex, which was shown to also operate close to the edge of chaos. Consequently, the behavior of model systems as studied here is likely to shed light on reasons why biological systems are tuned into this specific regime.

The Three Planes of Language.

ERIC Educational Resources Information Center

Sampson, Gloria

1999-01-01

Currently, the language sciences place together four different forms of mental activity on one plane of language, which results in confusion. This paper presents arguments from metaphysics, hermeneutics, and semiotics to demonstrate that there are actually three planes of language (a biologically-based information processing plane, a literal…

Producing Seed Crops to Naturally Regenerate Southern Pines

Treesearch

James P. Barnett; Ronald O. Haugen

1995-01-01

The biological processes that affect seed production in natural southern pine are documented, and information that will allow foresters to manipulate stands in a manner to improve and predict seed production is provided. As a result, natural regeneration should become a more reliable technique.

BIOLOGICAL PROCESS OF CANCER EXPLORED TO IMPROVE RISK ASSESSEMENT

EPA Science Inventory

Cancer research at EPA is advancing understanding of how a group of air pollutants, polycyclic aromatic hydrocarbons (PAHs) cause cancer in experimental animals. The research also will provide scientific information on responses of dose and effect that will respond to gaps in our...

Investigating Aquatic Dead Zones

ERIC Educational Resources Information Center

Testa, Jeremy; Gurbisz, Cassie; Murray, Laura; Gray, William; Bosch, Jennifer; Burrell, Chris; Kemp, Michael

2010-01-01

This article features two engaging high school activities that include current scientific information, data, and authentic case studies. The activities address the physical, biological, and chemical processes that are associated with oxygen-depleted areas, or "dead zones," in aquatic systems. Students can explore these dead zones through both…

Rock Magnetic and Ferromagnetic Resonance Tests of Biogenic Magnetite in ALH84001

NASA Technical Reports Server (NTRS)

Kirschvink, J. L.; Kim, S.; Weiss, B. P.; Shannon, D. M.; Kobayashi, A. K.

2002-01-01

Three separate rock magnetic and ferromagnetic resonance tests support the hypothesis that between 25 and 50% of the fine-grained magnetite in the Martian meteorite ALH84001 was formed via biological processes. Additional information is contained in the original extended abstract.

How Can We Use Bioinformatics to Predict Which Agents Will Cause Birth Defects?

EPA Science Inventory

The availability of genomic sequences from a growing number of human and model organisms has provided an explosion of data, information, and knowledge regarding biological systems and disease processes. High-throughput technologies such as DNA and protein microarray biochips are ...

77 FR 31387 - Remanded Biological Opinions on the Coordinated Long-Term Operation of the Central Valley Project...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-25

... process will be accepted on or before June 28, 2012. ADDRESSES: Send written comments to Janice Pi[ntilde... FURTHER INFORMATION CONTACT: Janice Pi[ntilde]ero at (916) 414- 2428; or email at [email protected

A Biological-Plausable Architecture for Shape Recognition

DTIC Science & Technology

2006-06-30

between curves. Information Processing Letters, 64, 1997. [4] Irving Biederman . Recognition-by-components: A theory of human image understanding...Psychological Review, 94(2):115–147, 1987 . 43 [5] C. Cadieu, M. Kouh, M. Riesenhuber, and T. Poggio. Shape representation in v4: Investi- gating position

Global, quantitative and dynamic mapping of protein subcellular localization

PubMed Central

Itzhak, Daniel N; Tyanova, Stefka; Cox, Jürgen; Borner, Georg HH

2016-01-01

Subcellular localization critically influences protein function, and cells control protein localization to regulate biological processes. We have developed and applied Dynamic Organellar Maps, a proteomic method that allows global mapping of protein translocation events. We initially used maps statically to generate a database with localization and absolute copy number information for over 8700 proteins from HeLa cells, approaching comprehensive coverage. All major organelles were resolved, with exceptional prediction accuracy (estimated at >92%). Combining spatial and abundance information yielded an unprecedented quantitative view of HeLa cell anatomy and organellar composition, at the protein level. We subsequently demonstrated the dynamic capabilities of the approach by capturing translocation events following EGF stimulation, which we integrated into a quantitative model. Dynamic Organellar Maps enable the proteome-wide analysis of physiological protein movements, without requiring any reagents specific to the investigated process, and will thus be widely applicable in cell biology. DOI: http://dx.doi.org/10.7554/eLife.16950.001 PMID:27278775

Online Analytical Processing (OLAP): A Fast and Effective Data Mining Tool for Gene Expression Databases

PubMed Central

2005-01-01

Gene expression databases contain a wealth of information, but current data mining tools are limited in their speed and effectiveness in extracting meaningful biological knowledge from them. Online analytical processing (OLAP) can be used as a supplement to cluster analysis for fast and effective data mining of gene expression databases. We used Analysis Services 2000, a product that ships with SQLServer2000, to construct an OLAP cube that was used to mine a time series experiment designed to identify genes associated with resistance of soybean to the soybean cyst nematode, a devastating pest of soybean. The data for these experiments is stored in the soybean genomics and microarray database (SGMD). A number of candidate resistance genes and pathways were found. Compared to traditional cluster analysis of gene expression data, OLAP was more effective and faster in finding biologically meaningful information. OLAP is available from a number of vendors and can work with any relational database management system through OLE DB. PMID:16046824

GEsture: an online hand-drawing tool for gene expression pattern search.

PubMed

Wang, Chunyan; Xu, Yiqing; Wang, Xuelin; Zhang, Li; Wei, Suyun; Ye, Qiaolin; Zhu, Youxiang; Yin, Hengfu; Nainwal, Manoj; Tanon-Reyes, Luis; Cheng, Feng; Yin, Tongming; Ye, Ning

2018-01-01

Gene expression profiling data provide useful information for the investigation of biological function and process. However, identifying a specific expression pattern from extensive time series gene expression data is not an easy task. Clustering, a popular method, is often used to classify similar expression genes, however, genes with a 'desirable' or 'user-defined' pattern cannot be efficiently detected by clustering methods. To address these limitations, we developed an online tool called GEsture. Users can draw, or graph a curve using a mouse instead of inputting abstract parameters of clustering methods. GEsture explores genes showing similar, opposite and time-delay expression patterns with a gene expression curve as input from time series datasets. We presented three examples that illustrate the capacity of GEsture in gene hunting while following users' requirements. GEsture also provides visualization tools (such as expression pattern figure, heat map and correlation network) to display the searching results. The result outputs may provide useful information for researchers to understand the targets, function and biological processes of the involved genes.

An improved Pearson's correlation proximity-based hierarchical clustering for mining biological association between genes.

PubMed

Booma, P M; Prabhakaran, S; Dhanalakshmi, R

2014-01-01

Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality.

An Improved Pearson's Correlation Proximity-Based Hierarchical Clustering for Mining Biological Association between Genes

PubMed Central

Booma, P. M.; Prabhakaran, S.; Dhanalakshmi, R.

2014-01-01

Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality. PMID:25136661

Biologically-Oriented Processes in the Coastal Sea Ice Zone of the White Sea

NASA Astrophysics Data System (ADS)

Melnikov, I. A.

2002-12-01

The annual advance and retreat of sea ice is a major physical determinant of spatial and temporal changes in the structure and function of marine coastal biological communities. Sea ice biological data obtained in the tidal zone of Kandalaksha Gulf (White Sea) during 1996-2001 period will be presented. Previous observations in this area were mainly conducted during the ice-free summer season. However, there is little information on the ice-covered winter season (6-7 months duration), and, especially, on the sea-ice biology in the coastal zone within tidal regimes. During the January-May period time-series observations were conducted on transects along shorelines with coastal and fast ice. Trends in the annual extent of sea ice showed significant impacts on ice-associated biological communities. Three types of sea ice impact on kelps, balanoides, littorinas and amphipods are distinguished: (i) positive, when sea ice protects these populations from grinding (ii) negative, when ice grinds both fauna and flora, and (iii) a combined effect, when fast ice protects, but anchored ice grinds plant and animals. To understand the full spectrum of ecological problems caused by pollution on the coastal zone, as well as the problems of sea ice melting caused by global warming, an integrated, long-term study of the physical, chemical, and biological processes is needed.

Influencing Eating Choices: Biological Food Cues in Advertising and Packaging Alter Trajectories of Decision Making and Behavior.

PubMed

Bailey, Rachel L

2017-10-01

From an ecological perception perspective (Gibson, 1977), the availability of perceptual information alters what behaviors are more and less likely at different times. This study examines how perceptual information delivered in food advertisements and packaging alters the time course of information processing and decision making. Participants categorized images of food that varied in information delivered in terms of color, glossiness, and texture (e.g., food cues) before and after being exposed to a set of advertisements that also varied in this way. In general, items with more direct cues enhanced appetitive motivational processes, especially if they were also advertised with direct food cues. Individuals also chose to eat products that were packaged with more available direct food cues compared to opaque packaging.

Software Tool for Researching Annotations of Proteins (STRAP): Open-Source Protein Annotation Software with Data Visualization

PubMed Central

Bhatia, Vivek N.; Perlman, David H.; Costello, Catherine E.; McComb, Mark E.

2009-01-01

In order that biological meaning may be derived and testable hypotheses may be built from proteomics experiments, assignments of proteins identified by mass spectrometry or other techniques must be supplemented with additional notation, such as information on known protein functions, protein-protein interactions, or biological pathway associations. Collecting, organizing, and interpreting this data often requires the input of experts in the biological field of study, in addition to the time-consuming search for and compilation of information from online protein databases. Furthermore, visualizing this bulk of information can be challenging due to the limited availability of easy-to-use and freely available tools for this process. In response to these constraints, we have undertaken the design of software to automate annotation and visualization of proteomics data in order to accelerate the pace of research. Here we present the Software Tool for Researching Annotations of Proteins (STRAP) – a user-friendly, open-source C# application. STRAP automatically obtains gene ontology (GO) terms associated with proteins in a proteomics results ID list using the freely accessible UniProtKB and EBI GOA databases. Summarized in an easy-to-navigate tabular format, STRAP includes meta-information on the protein in addition to complimentary GO terminology. Additionally, this information can be edited by the user so that in-house expertise on particular proteins may be integrated into the larger dataset. STRAP provides a sortable tabular view for all terms, as well as graphical representations of GO-term association data in pie (biological process, cellular component and molecular function) and bar charts (cross comparison of sample sets) to aid in the interpretation of large datasets and differential analyses experiments. Furthermore, proteins of interest may be exported as a unique FASTA-formatted file to allow for customizable re-searching of mass spectrometry data, and gene names corresponding to the proteins in the lists may be encoded in the Gaggle microformat for further characterization, including pathway analysis. STRAP, a tutorial, and the C# source code are freely available from http://cpctools.sourceforge.net. PMID:19839595

Chemical computing with reaction-diffusion processes.

PubMed

Gorecki, J; Gizynski, K; Guzowski, J; Gorecka, J N; Garstecki, P; Gruenert, G; Dittrich, P

2015-07-28

Chemical reactions are responsible for information processing in living organisms. It is believed that the basic features of biological computing activity are reflected by a reaction-diffusion medium. We illustrate the ideas of chemical information processing considering the Belousov-Zhabotinsky (BZ) reaction and its photosensitive variant. The computational universality of information processing is demonstrated. For different methods of information coding constructions of the simplest signal processing devices are described. The function performed by a particular device is determined by the geometrical structure of oscillatory (or of excitable) and non-excitable regions of the medium. In a living organism, the brain is created as a self-grown structure of interacting nonlinear elements and reaches its functionality as the result of learning. We discuss whether such a strategy can be adopted for generation of chemical information processing devices. Recent studies have shown that lipid-covered droplets containing solution of reagents of BZ reaction can be transported by a flowing oil. Therefore, structures of droplets can be spontaneously formed at specific non-equilibrium conditions, for example forced by flows in a microfluidic reactor. We describe how to introduce information to a droplet structure, track the information flow inside it and optimize medium evolution to achieve the maximum reliability. Applications of droplet structures for classification tasks are discussed. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

A neuromorphic circuit mimicking biological short-term memory.

PubMed

Barzegarjalali, Saeid; Parker, Alice C

2016-08-01

Research shows that the way we remember things for a few seconds is a different mechanism from the way we remember things for a longer time. Short-term memory is based on persistently firing neurons, whereas storing information for a longer time is based on strengthening the synapses or even forming new neural connections. Information about location and appearance of an object is segregated and processed by separate neurons. Furthermore neurons can continue firing using different mechanisms. Here, we have designed a biomimetic neuromorphic circuit that mimics short-term memory by firing neurons, using biological mechanisms to remember location and shape of an object. Our neuromorphic circuit has a hybrid architecture. Neurons are designed with CMOS 45nm technology and synapses are designed with carbon nanotubes (CNT).

Data is the currency of R&D, and that currency is now generated and traded globally.

PubMed

Brown, Frank K; Maliski, Edward; Waller, Chris

2010-05-01

Changes in the understanding of biological science, translational research and corporate business models require a corresponding change in the approach to chemical and biological information management. The concept of operations being partitioned into discrete departments for drug discovery is beginning to be replaced by a translational approach to this process. Pharmaceutical business and organizational models are also constantly evolving. Traditional approaches to transactional systems, transferring data up to a departmental data warehouse, are no longer meeting the needs of pharmaceutical scientists and, thus, IT departments are not considered as relevant to the business. These changes and their impact on information systems, as well as some solutions to the challenges faced, are discussed in this editorial.

Modern morphometry: new perspectives in physical anthropology.

PubMed

Mantini, Simone; Ripani, Maurizio

2009-06-01

In the past one hundred years physical anthropology has recourse to more and more efficient methods, which provide several new information regarding, human evolution and biology. Apart from the molecular approach, the introduction of new computed assisted techniques gave rise to a new concept of morphometry. Computed tomography and 3D-imaging, allowed providing anatomical description of the external and inner structures exceeding the problems encountered with the traditional morphometric methods. Furthermore, the support of geometric morphometrics, allowed creating geometric models to investigate morphological variation in terms of evolution, ontogeny and variability. The integration of these new tools gave rise to the virtual anthropology and to a new image of the anthropologist in which anatomical, biological, mathematical statistical and data processing information are fused in a multidisciplinary approach.

Mixed mechanisms of multi-site phosphorylation

PubMed Central

Suwanmajo, Thapanar; Krishnan, J.

2015-01-01

Multi-site phosphorylation is ubiquitous in cell biology and has been widely studied experimentally and theoretically. The underlying chemical modification mechanisms are typically assumed to be distributive or processive. In this paper, we study the behaviour of mixed mechanisms that can arise either because phosphorylation and dephosphorylation involve different mechanisms or because phosphorylation and/or dephosphorylation can occur through a combination of mechanisms. We examine a hierarchy of models to assess chemical information processing through different mixed mechanisms, using simulations, bifurcation analysis and analytical work. We demonstrate how mixed mechanisms can show important and unintuitive differences from pure distributive and processive mechanisms, in some cases resulting in monostable behaviour with simple dose–response behaviour, while in other cases generating new behaviour-like oscillations. Our results also suggest patterns of information processing that are relevant as the number of modification sites increases. Overall, our work creates a framework to examine information processing arising from complexities of multi-site modification mechanisms and their impact on signal transduction. PMID:25972433

Human development II: we need an integrated theory for matter, life and consciousness to understand life and healing.

PubMed

Ventegodt, Søren; Hermansen, Tyge Dahl; Nielsen, Maj Lyck; Clausen, Birgitte; Merrick, Joav

2006-07-06

For almost a decade, we have experimented with supporting the philosophical development of severely ill patients to induce recovery and spontaneous healing. Recently, we have observed a new pattern of extremely rapid, spontaneous healing that apparently can facilitate even the spontaneous remission of cancer and the spontaneous recovery of mental diseases like schizophrenia and borderline schizophrenia. Our working hypothesis is that the accelerated healing is a function of the patient's brain-mind and body-mind coming closer together due to the development of what we call "deep" cosmology. To understand and describe what happens at a biological level, we have suggested naming the process adult human metamorphosis, a possibility that is opened by the human genome showing full generic equipment for metamorphosis. To understand the mechanistic details in the complicated interaction between consciousness and biology, we need an adequate theory for biological information. In a series of papers, we propose what we call "holistic biology for holistic medicine". We suggest that a relatively simple model based on interacting wholenesses instead of isolated parts can shed a new light on a number of difficult issues that we need to explain and understand in biology and medicine in order to understand and use metamorphosis in the holistic medical clinic. We aim to give a holistic theoretical interpretation of biological phenomena at large, morphogenesis, evolution, immune system regulation (self-nonself discrimination), brain function, consciousness, and health in particular. We start at the most fundamental problem: what is biological information at the subcellular, cellular, and supracellular levels if we presume that it is the same phenomenon on all levels (using Occam's razor), and how can this be described scientifically? The problems we address are all connected to the information flow in the functioning, living organism: function of the brain and consciousness, the regulations of the immune system and cell growth, the dynamics of health and disease. We suggest that life utilizes an unseen fine structure of the physical energy of the universe at a subparticular or quantum level to give information-directed self-organization; we give a first sketch of a possible fractal structure of the energy able to both contain and communicate biological information and carry individual and collective consciousness. Finally, thorough our analysis, we put up a model for adult human metamorphosis.

Cellular processing and destinies of artificial DNA nanostructures.

PubMed

Lee, Di Sheng; Qian, Hang; Tay, Chor Yong; Leong, David Tai

2016-08-07

Since many bionanotechnologies are targeted at cells, understanding how and where their interactions occur and the subsequent results of these interactions is important. Changing the intrinsic properties of DNA nanostructures and linking them with interactions presents a holistic and powerful strategy for understanding dual nanostructure-biological systems. With the recent advances in DNA nanotechnology, DNA nanostructures present a great opportunity to understand the often convoluted mass of information pertaining to nanoparticle-biological interactions due to the more precise control over their chemistry, sizes, and shapes. Coupling just some of these designs with an understanding of biological processes is both a challenge and a source of opportunities. Despite continuous advances in the field of DNA nanotechnology, the intracellular fate of DNA nanostructures has remained unclear and controversial. Because understanding its cellular processing and destiny is a necessary prelude to any rational design of exciting and innovative bionanotechnology, in this review, we will discuss and provide a comprehensive picture relevant to the intracellular processing and the fate of various DNA nanostructures which have been remained elusive for some time. We will also link the unique capabilities of DNA to some novel ideas for developing next-generation bionanotechnologies.

Modeling for Visual Feature Extraction Using Spiking Neural Networks

NASA Astrophysics Data System (ADS)

Kimura, Ichiro; Kuroe, Yasuaki; Kotera, Hiromichi; Murata, Tomoya

This paper develops models for “visual feature extraction” in biological systems by using “spiking neural network (SNN)”. The SNN is promising for developing the models because the information is encoded and processed by spike trains similar to biological neural networks. Two architectures of SNN are proposed for modeling the directionally selective and the motion parallax cell in neuro-sensory systems and they are trained so as to possess actual biological responses of each cell. To validate the developed models, their representation ability is investigated and their visual feature extraction mechanisms are discussed from the neurophysiological viewpoint. It is expected that this study can be the first step to developing a sensor system similar to the biological systems and also a complementary approach to investigating the function of the brain.

Signal processing for molecular and cellular biological physics: an emerging field.

PubMed

Little, Max A; Jones, Nick S

2013-02-13

Recent advances in our ability to watch the molecular and cellular processes of life in action--such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer--raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied.

Signal processing for molecular and cellular biological physics: an emerging field

PubMed Central

Little, Max A.; Jones, Nick S.

2013-01-01

Recent advances in our ability to watch the molecular and cellular processes of life in action—such as atomic force microscopy, optical tweezers and Forster fluorescence resonance energy transfer—raise challenges for digital signal processing (DSP) of the resulting experimental data. This article explores the unique properties of such biophysical time series that set them apart from other signals, such as the prevalence of abrupt jumps and steps, multi-modal distributions and autocorrelated noise. It exposes the problems with classical linear DSP algorithms applied to this kind of data, and describes new nonlinear and non-Gaussian algorithms that are able to extract information that is of direct relevance to biological physicists. It is argued that these new methods applied in this context typify the nascent field of biophysical DSP. Practical experimental examples are supplied. PMID:23277603

Innovation: an emerging focus from cells to societies.

PubMed

Hochberg, Michael E; Marquet, Pablo A; Boyd, Robert; Wagner, Andreas

2017-12-05

Innovations are generally unexpected, often spectacular changes in phenotypes and ecological functions. The contributions to this theme issue are the latest conceptual, theoretical and experimental developments, addressing how ecology, environment, ontogeny and evolution are central to understanding the complexity of the processes underlying innovations. Here, we set the stage by introducing and defining key terms relating to innovation and discuss their relevance to biological, cultural and technological change. Discovering how the generation and transmission of novel biological information, environmental interactions and selective evolutionary processes contribute to innovation as an ecosystem will shed light on how the dominant features across life come to be, generalize to social, cultural and technological evolution, and have applications in the health sciences and sustainability.This article is part of the theme issue 'Process and pattern in innovations from cells to societies'. © 2017 The Author(s).

Innovation: an emerging focus from cells to societies

PubMed Central

Boyd, Robert

2017-01-01

Innovations are generally unexpected, often spectacular changes in phenotypes and ecological functions. The contributions to this theme issue are the latest conceptual, theoretical and experimental developments, addressing how ecology, environment, ontogeny and evolution are central to understanding the complexity of the processes underlying innovations. Here, we set the stage by introducing and defining key terms relating to innovation and discuss their relevance to biological, cultural and technological change. Discovering how the generation and transmission of novel biological information, environmental interactions and selective evolutionary processes contribute to innovation as an ecosystem will shed light on how the dominant features across life come to be, generalize to social, cultural and technological evolution, and have applications in the health sciences and sustainability. This article is part of the theme issue ‘Process and pattern in innovations from cells to societies’. PMID:29061887

Update on Genomic Databases and Resources at the National Center for Biotechnology Information.

PubMed

Tatusova, Tatiana

2016-01-01

The National Center for Biotechnology Information (NCBI), as a primary public repository of genomic sequence data, collects and maintains enormous amounts of heterogeneous data. Data for genomes, genes, gene expressions, gene variation, gene families, proteins, and protein domains are integrated with the analytical, search, and retrieval resources through the NCBI website, text-based search and retrieval system, provides a fast and easy way to navigate across diverse biological databases.Comparative genome analysis tools lead to further understanding of evolution processes quickening the pace of discovery. Recent technological innovations have ignited an explosion in genome sequencing that has fundamentally changed our understanding of the biology of living organisms. This huge increase in DNA sequence data presents new challenges for the information management system and the visualization tools. New strategies have been designed to bring an order to this genome sequence shockwave and improve the usability of associated data.

PLAN2L: a web tool for integrated text mining and literature-based bioentity relation extraction.

PubMed

Krallinger, Martin; Rodriguez-Penagos, Carlos; Tendulkar, Ashish; Valencia, Alfonso

2009-07-01

There is an increasing interest in using literature mining techniques to complement information extracted from annotation databases or generated by bioinformatics applications. Here we present PLAN2L, a web-based online search system that integrates text mining and information extraction techniques to access systematically information useful for analyzing genetic, cellular and molecular aspects of the plant model organism Arabidopsis thaliana. Our system facilitates a more efficient retrieval of information relevant to heterogeneous biological topics, from implications in biological relationships at the level of protein interactions and gene regulation, to sub-cellular locations of gene products and associations to cellular and developmental processes, i.e. cell cycle, flowering, root, leaf and seed development. Beyond single entities, also predefined pairs of entities can be provided as queries for which literature-derived relations together with textual evidences are returned. PLAN2L does not require registration and is freely accessible at http://zope.bioinfo.cnio.es/plan2l.

Unzippers, Resolvers and Sensors: A Structural and Functional Biochemistry Tale of RNA Helicases

PubMed Central

Leitão, Ana Lúcia; Costa, Marina C.; Enguita, Francisco J.

2015-01-01

The centrality of RNA within the biological world is an irrefutable fact that currently attracts increasing attention from the scientific community. The panoply of functional RNAs requires the existence of specific biological caretakers, RNA helicases, devoted to maintain the proper folding of those molecules, resolving unstable structures. However, evolution has taken advantage of the specific position and characteristics of RNA helicases to develop new functions for these proteins, which are at the interface of the basic processes for transference of information from DNA to proteins. RNA helicases are involved in many biologically relevant processes, not only as RNA chaperones, but also as signal transducers, scaffolds of molecular complexes, and regulatory elements. Structural biology studies during the last decade, founded in X-ray crystallography, have characterized in detail several RNA-helicases. This comprehensive review summarizes the structural knowledge accumulated in the last two decades within this family of proteins, with special emphasis on the structure-function relationships of the most widely-studied families of RNA helicases: the DEAD-box, RIG-I-like and viral NS3 classes. PMID:25622248

Understanding Classrooms through Social Network Analysis: A Primer for Social Network Analysis in Education Research.

PubMed

Grunspan, Daniel Z; Wiggins, Benjamin L; Goodreau, Steven M

2014-01-01

Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA) provides the necessary tool kit for investigating questions involving relational data. We introduce basic concepts in SNA, along with methods for data collection, data processing, and data analysis, using a previously collected example study on an undergraduate biology classroom as a tutorial. We conduct descriptive analyses of the structure of the network of costudying relationships. We explore generative processes that create observed study networks between students and also test for an association between network position and success on exams. We also cover practical issues, such as the unique aspects of human subjects review for network studies. Our aims are to convince readers that using SNA in classroom environments allows rich and informative analyses to take place and to provide some initial tools for doing so, in the process inspiring future educational studies incorporating relational data. © 2014 D. Z. Grunspan 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).

75 FR 29725 - Mid-Atlantic Fishery Management Council; Public Hearings

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-27

... management process; the biological and socio-economic outcomes of a catch share system and how such outcomes depend on specific program design features; the possible need for changes to existing information...) fisheries and that uncontrolled activation of latent capacity could cause negative economic effects for...

Online Bioinformatics Tutorials | Office of Cancer Genomics

Cancer.gov

Bioinformatics is a scientific discipline that applies computer science and information technology to help understand biological processes. The NIH provides a list of free online bioinformatics tutorials, either generated by the NIH Library or other institutes, which includes introductory lectures and "how to" videos on using various tools.

Proteogenomics | Office of Cancer Clinical Proteomics Research

Cancer.gov

Proteogenomics, or the integration of proteomics with genomics and transcriptomics, is an emerging approach that promises to advance basic, translational and clinical research.  By combining genomic and proteomic information, leading scientists are gaining new insights due to a more complete and unified understanding of complex biological processes.

Problem Solving in Biology: A Methodology

ERIC Educational Resources Information Center

Wisehart, Gary; Mandell, Mark

2008-01-01

A methodology is described that teaches science process by combining informal logic and a heuristic for rating factual reliability. This system facilitates student hypothesis formation, testing, and evaluation of results. After problem solving with this scheme, students are asked to examine and evaluate arguments for the underlying principles of…

EXPLOITING GENOME DATA TO UNDERSTAND THE FUNCTION, REGULATION AND EVOLUTIONARY ORIGINS OF TOXICOLOGICALLY RELEVANT GENES

EPA Science Inventory

The wealth of new information coming from the many genome sequencing projects is providing unprecedented opportunities for major advances in all areas of biology, including the environmental health sciences. To facilitate this discovery process, experts in the fields of function...

Work and Organizational Life in the Year 2000.

DTIC Science & Technology

1972-12-01

information, processing data, and making decisions partkcularly, as every high school student is introduced to programming as he now is to biology or...Hamilton, New York: American Foundation for Managemnt Researh , 1968. Roszak, T. The making of a counterculture. New York: Doubleday, 1968. Schoin, E.11

THE ART OF DATA MINING THE MINEFIELDS OF TOXICITY DATABASES TO LINK CHEMISTRY TO BIOLOGY

EPA Science Inventory

Toxicity databases have a special role in predictive toxicology, providing ready access to historical information throughout the workflow of discovery, development, and product safety processes in drug development as well as in review by regulatory agencies. To provide accurate i...

Translational systems biology: introduction of an engineering approach to the pathophysiology of the burn patient.

PubMed

An, Gary; Faeder, James; Vodovotz, Yoram

2008-01-01

The pathophysiology of the burn patient manifests the full spectrum of the complexity of the inflammatory response. In the acute phase, inflammation may have negative effects via capillary leak, the propagation of inhalation injury, and development of multiple organ failure. Attempts to mediate these processes remain a central subject of burn care research. Conversely, inflammation is a necessary prologue and component in the later stage processes of wound healing. Despite the volume of information concerning the cellular and molecular processes involved in inflammation, there exists a significant gap between the knowledge of mechanistic pathophysiology and the development of effective clinical therapeutic regimens. Translational systems biology (TSB) is the application of dynamic mathematical modeling and certain engineering principles to biological systems to integrate mechanism with phenomenon and, importantly, to revise clinical practice. This study will review the existing applications of TSB in the areas of inflammation and wound healing, relate them to specific areas of interest to the burn community, and present an integrated framework that links TSB with traditional burn research.

Wavelet data processing of micro-Raman spectra of biological samples

NASA Astrophysics Data System (ADS)

Camerlingo, C.; Zenone, F.; Gaeta, G. M.; Riccio, R.; Lepore, M.

2006-02-01

A wavelet multi-component decomposition algorithm is proposed for processing data from micro-Raman spectroscopy (μ-RS) of biological tissue. The μ-RS has been recently recognized as a promising tool for the biopsy test and in vivo diagnosis of degenerative human tissue pathologies, due to the high chemical and structural information contents of this spectroscopic technique. However, measurements of biological tissues are usually hampered by typically low-level signals and by the presence of noise and background components caused by light diffusion or fluorescence processes. In order to overcome these problems, a numerical method based on discrete wavelet transform is used for the analysis of data from μ-RS measurements performed in vitro on animal (pig and chicken) tissue samples and, in a preliminary form, on human skin and oral tissue biopsy from normal subjects. Visible light μ-RS was performed using a He-Ne laser and a monochromator with a liquid nitrogen cooled charge coupled device equipped with a grating of 1800 grooves mm-1. The validity of the proposed data procedure has been tested on the well-characterized Raman spectra of reference acetylsalicylic acid samples.

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.

Genome Scale Modeling in Systems Biology: Algorithms and Resources

PubMed Central

Najafi, Ali; Bidkhori, Gholamreza; Bozorgmehr, Joseph H.; Koch, Ina; Masoudi-Nejad, Ali

2014-01-01

In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics. PMID:24822031

Making species checklists understandable to machines - a shift from relational databases to ontologies.

PubMed

Laurenne, Nina; Tuominen, Jouni; Saarenmaa, Hannu; Hyvönen, Eero

2014-01-01

The scientific names of plants and animals play a major role in Life Sciences as information is indexed, integrated, and searched using scientific names. The main problem with names is their ambiguous nature, because more than one name may point to the same taxon and multiple taxa may share the same name. In addition, scientific names change over time, which makes them open to various interpretations. Applying machine-understandable semantics to these names enables efficient processing of biological content in information systems. The first step is to use unique persistent identifiers instead of name strings when referring to taxa. The most commonly used identifiers are Life Science Identifiers (LSID), which are traditionally used in relational databases, and more recently HTTP URIs, which are applied on the Semantic Web by Linked Data applications. We introduce two models for expressing taxonomic information in the form of species checklists. First, we show how species checklists are presented in a relational database system using LSIDs. Then, in order to gain a more detailed representation of taxonomic information, we introduce meta-ontology TaxMeOn to model the same content as Semantic Web ontologies where taxa are identified using HTTP URIs. We also explore how changes in scientific names can be managed over time. The use of HTTP URIs is preferable for presenting the taxonomic information of species checklists. An HTTP URI identifies a taxon and operates as a web address from which additional information about the taxon can be located, unlike LSID. This enables the integration of biological data from different sources on the web using Linked Data principles and prevents the formation of information silos. The Linked Data approach allows a user to assemble information and evaluate the complexity of taxonomical data based on conflicting views of taxonomic classifications. Using HTTP URIs and Semantic Web technologies also facilitate the representation of the semantics of biological data, and in this way, the creation of more "intelligent" biological applications and services.

Process Pharmacology: A Pharmacological Data Science Approach to Drug Development and Therapy.

PubMed

Lötsch, Jörn; Ultsch, Alfred

2016-04-01

A novel functional-genomics based concept of pharmacology that uses artificial intelligence techniques for mining and knowledge discovery in "big data" providing comprehensive information about the drugs' targets and their functional genomics is proposed. In "process pharmacology", drugs are associated with biological processes. This puts the disease, regarded as alterations in the activity in one or several cellular processes, in the focus of drug therapy. In this setting, the molecular drug targets are merely intermediates. The identification of drugs for therapeutic or repurposing is based on similarities in the high-dimensional space of the biological processes that a drug influences. Applying this principle to data associated with lymphoblastic leukemia identified a short list of candidate drugs, including one that was recently proposed as novel rescue medication for lymphocytic leukemia. The pharmacological data science approach provides successful selections of drug candidates within development and repurposing tasks. © 2016 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Dual-wavelength common-path digital holographic microscopy for quantitative phase imaging of biological cells

NASA Astrophysics Data System (ADS)

Di, Jianglei; Song, Yu; Xi, Teli; Zhang, Jiwei; Li, Ying; Ma, Chaojie; Wang, Kaiqiang; Zhao, Jianlin

2017-11-01

Biological cells are usually transparent with a small refractive index gradient. Digital holographic interferometry can be used in the measurement of biological cells. We propose a dual-wavelength common-path digital holographic microscopy for the quantitative phase imaging of biological cells. In the proposed configuration, a parallel glass plate is inserted in the light path to create the lateral shearing, and two lasers with different wavelengths are used as the light source to form the dual-wavelength composite digital hologram. The information of biological cells for different wavelengths is separated and extracted in the Fourier domain of the hologram, and then combined to a shorter wavelength in the measurement process. This method could improve the system's temporal stability and reduce speckle noises simultaneously. Mouse osteoblastic cells and peony pollens are measured to show the feasibility of this method.

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

"Do I need to know this for the exam?" Using popular media, inquiry-based laboratories, and a community of scientific practice to motivate students to learn developmental biology.

PubMed

Madhuri, Marga; Broussard, Christine

2008-01-01

One of the greatest challenges instructors face is getting students to connect with the subject in a manner that encourages them to learn. In this essay, we describe the redesign of our Developmental Biology course to foster a deeper connection between students and the field of developmental biology. In our approach, we created a community of scientific practice focused on the investigation of environmental impacts on embryonic development and informed by popular and scientific media, the students' own questions, and the instructor. Our goals were to engage students in meaningful ways with the material, to develop students' science process skills, and to enhance students' understanding of broad principles of developmental biology. Though significant challenges arose during implementation, assessments indicate using this approach to teach undergraduate developmental biology was successful.

Processing of Visual Imagery by an Adaptive Model of the Visual System: Its Performance and its Significance. Final Report, June 1969-March 1970.

ERIC Educational Resources Information Center

Tallman, Oliver H.

A digital simulation of a model for the processing of visual images is derived from known aspects of the human visual system. The fundamental principle of computation suggested by a biological model is a transformation that distributes information contained in an input stimulus everywhere in a transform domain. Each sensory input contributes under…

Stimulus Sensitivity of a Spiking Neural Network Model

NASA Astrophysics Data System (ADS)

Chevallier, Julien

2018-02-01

Some recent papers relate the criticality of complex systems to their maximal capacity of information processing. In the present paper, we consider high dimensional point processes, known as age-dependent Hawkes processes, which have been used to model spiking neural networks. Using mean-field approximation, the response of the network to a stimulus is computed and we provide a notion of stimulus sensitivity. It appears that the maximal sensitivity is achieved in the sub-critical regime, yet almost critical for a range of biologically relevant parameters.

Computing the origin and evolution of the ribosome from its structure — Uncovering processes of macromolecular accretion benefiting synthetic biology

PubMed Central

Caetano-Anollés, Gustavo; Caetano-Anollés, Derek

2015-01-01

Accretion occurs pervasively in nature at widely different timeframes. The process also manifests in the evolution of macromolecules. Here we review recent computational and structural biology studies of evolutionary accretion that make use of the ideographic (historical, retrodictive) and nomothetic (universal, predictive) scientific frameworks. Computational studies uncover explicit timelines of accretion of structural parts in molecular repertoires and molecules. Phylogenetic trees of protein structural domains and proteomes and their molecular functions were built from a genomic census of millions of encoded proteins and associated terminal Gene Ontology terms. Trees reveal a ‘metabolic-first’ origin of proteins, the late development of translation, and a patchwork distribution of proteins in biological networks mediated by molecular recruitment. Similarly, the natural history of ancient RNA molecules inferred from trees of molecular substructures built from a census of molecular features shows patchwork-like accretion patterns. Ideographic analyses of ribosomal history uncover the early appearance of structures supporting mRNA decoding and tRNA translocation, the coevolution of ribosomal proteins and RNA, and a first evolutionary transition that brings ribosomal subunits together into a processive protein biosynthetic complex. Nomothetic structural biology studies of tertiary interactions and ancient insertions in rRNA complement these findings, once concentric layering assumptions are removed. Patterns of coaxial helical stacking reveal a frustrated dynamics of outward and inward ribosomal growth possibly mediated by structural grafting. The early rise of the ribosomal ‘turnstile’ suggests an evolutionary transition in natural biological computation. Results make explicit the need to understand processes of molecular growth and information transfer of macromolecules. PMID:27096056

Achieving biopolymer synergy in systems chemistry.

PubMed

Bai, Yushi; Chotera, Agata; Taran, Olga; Liang, Chen; Ashkenasy, Gonen; Lynn, David G

2018-05-31

Synthetic and materials chemistry initiatives have enabled the translation of the macromolecular functions of biology into synthetic frameworks. These explorations into alternative chemistries of life attempt to capture the versatile functionality and adaptability of biopolymers in new orthogonal scaffolds. Information storage and transfer, however, so beautifully represented in the central dogma of biology, require multiple components functioning synergistically. Over a single decade, the emerging field of systems chemistry has begun to catalyze the construction of mutualistic biopolymer networks, and this review begins with the foundational small-molecule-based dynamic chemical networks and peptide amyloid-based dynamic physical networks on which this effort builds. The approach both contextualizes the versatile approaches that have been developed to enrich chemical information in synthetic networks and highlights the properties of amyloids as potential alternative genetic elements. The successful integration of both chemical and physical networks through β-sheet assisted replication processes further informs the synergistic potential of these networks. Inspired by the cooperative synergies of nucleic acids and proteins in biology, synthetic nucleic-acid-peptide chimeras are now being explored to extend their informational content. With our growing range of synthetic capabilities, structural analyses, and simulation technologies, this foundation is radically extending the structural space that might cross the Darwinian threshold for the origins of life as well as creating an array of alternative systems capable of achieving the progressive growth of novel informational materials.

Application of Non-Kolmogorovian Probability and Quantum Adaptive Dynamics to Unconscious Inference in Visual Perception Process

NASA Astrophysics Data System (ADS)

Accardi, Luigi; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

2016-07-01

Recently a novel quantum information formalism — quantum adaptive dynamics — was developed and applied to modelling of information processing by bio-systems including cognitive phenomena: from molecular biology (glucose-lactose metabolism for E.coli bacteria, epigenetic evolution) to cognition, psychology. From the foundational point of view quantum adaptive dynamics describes mutual adapting of the information states of two interacting systems (physical or biological) as well as adapting of co-observations performed by the systems. In this paper we apply this formalism to model unconscious inference: the process of transition from sensation to perception. The paper combines theory and experiment. Statistical data collected in an experimental study on recognition of a particular ambiguous figure, the Schröder stairs, support the viability of the quantum(-like) model of unconscious inference including modelling of biases generated by rotation-contexts. From the probabilistic point of view, we study (for concrete experimental data) the problem of contextuality of probability, its dependence on experimental contexts. Mathematically contextuality leads to non-Komogorovness: probability distributions generated by various rotation contexts cannot be treated in the Kolmogorovian framework. At the same time they can be embedded in a “big Kolmogorov space” as conditional probabilities. However, such a Kolmogorov space has too complex structure and the operational quantum formalism in the form of quantum adaptive dynamics simplifies the modelling essentially.

Bio-inspired nano-sensor-enhanced CNN visual computer.

PubMed

Porod, Wolfgang; Werblin, Frank; Chua, Leon O; Roska, Tamas; Rodriguez-Vazquez, Angel; Roska, Botond; Fay, Patrick; Bernstein, Gary H; Huang, Yih-Fang; Csurgay, Arpad I

2004-05-01

Nanotechnology opens new ways to utilize recent discoveries in biological image processing by translating the underlying functional concepts into the design of CNN (cellular neural/nonlinear network)-based systems incorporating nanoelectronic devices. There is a natural intersection joining studies of retinal processing, spatio-temporal nonlinear dynamics embodied in CNN, and the possibility of miniaturizing the technology through nanotechnology. This intersection serves as the springboard for our multidisciplinary project. Biological feature and motion detectors map directly into the spatio-temporal dynamics of CNN for target recognition, image stabilization, and tracking. The neural interactions underlying color processing will drive the development of nanoscale multispectral sensor arrays for image fusion. Implementing such nanoscale sensors on a CNN platform will allow the implementation of device feedback control, a hallmark of biological sensory systems. These biologically inspired CNN subroutines are incorporated into the new world of analog-and-logic algorithms and software, containing also many other active-wave computing mechanisms, including nature-inspired (physics and chemistry) as well as PDE-based sophisticated spatio-temporal algorithms. Our goal is to design and develop several miniature prototype devices for target detection, navigation, tracking, and robotics. This paper presents an example illustrating the synergies emerging from the convergence of nanotechnology, biotechnology, and information and cognitive science.

Professional paths of alumni from doctorate programs in health and biological sciences

PubMed Central

Hortale, Virginia Alonso; Moreira, Carlos Otávio Fiúza; Bochner, Rosany; Leal, Maria do Carmo

2014-01-01

OBJECTIVE To analyze the career path and professional satisfaction of alumni from the doctorate degree programs in health sector. METHODS Exploratory study with 827 alumni of doctoral programs in public health, biological and health sciences at the Fundação Oswaldo Cruz , RJ, Southeastern Brazil, from1984 to 2007. The subjects were grouped in three cross-temporal cohorts according to year. The profiles of the alumni were analyzed, their career paths mapped and information on the perceptions of the education they received and the reasons that led them to choose the institute for their doctoral courses gathered, as well as their evaluations of the courses. The data were collected by means of an online questionnaire. RESULTS There are differences between cohorts of alumni related to the periods they followed the courses, their distinct educational backgrounds and labor processes between those from the biological and health sciences areas, and to the specificities of the different areas where the institution offers doctoral courses: public health, biological and health sciences. CONCLUSIONS The results allow the academic management of the educational processes to expend its knowledge, thus establishing a baseline for tracking the trajectory of alumni, and may contribute to upgrading the follow up process of Brazilian graduate programs. PMID:24789631

Adverse Outcome Pathways – Organizing Toxicological ...

EPA Pesticide Factsheets

The number of chemicals for which environmental regulatory decisions are required far exceeds the current capacity for toxicity testing. High throughput screening (HTS) commonly used for drug discovery has the potential to increase this capacity. The adverse outcome pathway (AOP) concept has emerged as a natural framework for connecting high throughput toxicity testing (HTT) results to potential impacts on humans and wildlife populations. An AOP consists of two main components that describe the biological mechanisms driving toxicity. Key events represent biological processes essential for causing the adverse outcome that are also measurable experimentally. Key event relationships capture the biological processes connecting the key events. Evidence documented for each KER based on measurements of the KEs can provide the confidence needed for extrapolating HTT from early key events to overt toxicity represented by later key events based on the AOP. The IPCS mode of action (MOA) framework incorporates information required for making a chemical-specific toxicity determination. Given the close relationship between the AOP and MOA frameworks, it is possible to assemble an MOA by incorporating HTT results, chemical properties including absorption, distribution, metabolism, and excretion (ADME), and an AOP describing the biological basis of toxicity thereby streamlining the process. While current applications focus on the assessment of risk for environmental chemicals,

Spaces of the possible: universal Darwinism and the wall between technological and biological innovation.

PubMed

Wagner, Andreas; Rosen, William

2014-08-06

Innovations in biological evolution and in technology have many common features. Some of them involve similar processes, such as trial and error and horizontal information transfer. Others describe analogous outcomes such as multiple independent origins of similar innovations. Yet others display similar temporal patterns such as episodic bursts of change separated by periods of stasis. We review nine such commonalities, and propose that the mathematical concept of a space of innovations, discoveries or designs can help explain them. This concept can also help demolish a persistent conceptual wall between technological and biological innovation. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Modern methods and systems for precise control of the quality of agricultural and food production

NASA Astrophysics Data System (ADS)

Bednarjevsky, Sergey S.; Veryasov, Yuri V.; Akinina, Evgeniya V.; Smirnov, Gennady I.

1999-01-01

The results on the modeling of non-linear dynamics of strong continuous and impulse radiation in the laser nephelometry of polydisperse biological systems, important from the viewpoint of applications in biotechnologies, are presented. The processes of nonlinear self-action of the laser radiation by the multiple scattering in the disperse biological agro-media are considered. The simplified algorithms of the calculation of the parameters of the biological media under investigation are indicated and the estimates of the errors of the laser-nephelometric measurements are given. The universal high-informative optical analyzers and the standard etalon specimens of agro- objects make the technological foundation of the considered methods and systems.

Information Fusion for Hypothesis Generation under Uncertain and Partial Information Access Situation

DTIC Science & Technology

2006-07-21

This fundermental architecture can be illustrated as bow-tie architeture , that is claimed to be the fundermenal architecture of robust systems (Fig...sequenced genomes86,87. The Gene Ontology’s biological process hierarchy88 was used to annotate functional categories to each gene, and proportions of... proportions in the early Drosophila embryo. Nature 415, 798-802 (2002). 14. Kitano, H. Cancer robustness: tumour tactics. Nature 426, 125 (2003). 15

Information Fusion for Hypothesis Generation under Uncertain and Partial Information Access Situation

DTIC Science & Technology

2008-07-21

size. This fundermental architecture can be illustrated as bow-tie architeture , that is claimed to be the fundermenal architecture of robust systems...sequenced genomes86,87. The Gene Ontology’s biological process hierarchy88 was used to annotate functional categories to each gene, and proportions ...and proportions in the early Drosophila embryo. Nature 415, 798-802 (2002). 14. Kitano, H. Cancer robustness: tumour tactics. Nature 426, 125 (2003

An Investigation into Spike-Based Neuromorphic Approaches for Artificial Olfactory Systems

PubMed Central

Osseiran, Adam

2017-01-01

The implementation of neuromorphic methods has delivered promising results for vision and auditory sensors. These methods focus on mimicking the neuro-biological architecture to generate and process spike-based information with minimal power consumption. With increasing interest in developing low-power and robust chemical sensors, the application of neuromorphic engineering concepts for electronic noses has provided an impetus for research focusing on improving these instruments. While conventional e-noses apply computationally expensive and power-consuming data-processing strategies, neuromorphic olfactory sensors implement the biological olfaction principles found in humans and insects to simplify the handling of multivariate sensory data by generating and processing spike-based information. Over the last decade, research on neuromorphic olfaction has established the capability of these sensors to tackle problems that plague the current e-nose implementations such as drift, response time, portability, power consumption and size. This article brings together the key contributions in neuromorphic olfaction and identifies future research directions to develop near-real-time olfactory sensors that can be implemented for a range of applications such as biosecurity and environmental monitoring. Furthermore, we aim to expose the computational parallels between neuromorphic olfaction and gustation for future research focusing on the correlation of these senses. PMID:29125586

Incorporating ecogeomorphic feedbacks to better understand resiliency in streams: A review and directions forward

NASA Astrophysics Data System (ADS)

Atkinson, Carla L.; Allen, Daniel C.; Davis, Lisa; Nickerson, Zachary L.

2018-03-01

Decades of interdisciplinary research show river form and function depends on interactions between the living and nonliving world, but a dominant paradigm underlying ecogeomorphic work consists of a top-down, unidirectional approach with abiotic forces driving biotic systems. Stream form and location within the stream network does dictate the habitat and resources available for organisms and overall community structure. Yet this traditional hierarchal framework on its own is inadequate in communicating information regarding the influence of biological systems on fluvial geomorphology that lead to changes in channel morphology, sediment cycling, and system-scale functions (e.g., sediment yield, biogeochemical nutrient cycling). Substantial evidence that organisms influence fluvial geomorphology exists, specifically the ability of aquatic vegetation and lotic animals to modify flow velocities and sediment deposition and transport - thus challenging the traditional hierarchal framework. Researchers recognize the need for ecogeomorphic frameworks that conceptualize feedbacks between organisms, sediment transport, and geomorphic structure. Furthermore, vital ecosystem processes, such as biogeochemical nutrient cycling represent the conversations that are occurring between geomorphological and biological systems. Here we review and synthesize selected case studies highlighting the role organisms play in moderating geomorphic processes and likely interact with these processes to have an impact on an essential ecosystem process, biogeochemical nutrient recycling. We explore whether biophysical interactions can provide information essential to improving predictions of system-scale river functions, specifically sediment transport and biogeochemical cycling, and discuss tools used to study these interactions. We suggest that current conceptual frameworks should acknowledge that hydrologic, geomorphologic, and ecologic processes operate on different temporal scales, generating bidirectional feedback loops over space and time. Hydro- and geomorphologic processes, operating episodically during bankfull conditions, influence ecological processes (e.g., biogeochemical cycling) occurring over longer time periods during base-flow conditions. This ecological activity generates the antecedent conditions that influence the hydro- and geomorphologic processes occurring during the next high flow event, creating a bidirectional feedback. This feedback should enhance the resiliency of fluvial landforms and ecosystem processes, allowing physical and biological processes to pull and push against each other over time.

Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology

PubMed Central

Roncaglia, Paola; Howe, Douglas G.; Laulederkind, Stanley J.F.; Khodiyar, Varsha K.; Berardini, Tanya Z.; Tweedie, Susan; Foulger, Rebecca E.; Osumi-Sutherland, David; Campbell, Nancy H.; Huntley, Rachael P.; Talmud, Philippa J.; Blake, Judith A.; Breckenridge, Ross; Riley, Paul R.; Lambiase, Pier D.; Elliott, Perry M.; Clapp, Lucie; Tinker, Andrew; Hill, David P.

2018-01-01

Background: A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. Methods and Results: In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. Conclusions: We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. PMID:29440116

Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology.

PubMed

Lovering, Ruth C; Roncaglia, Paola; Howe, Douglas G; Laulederkind, Stanley J F; Khodiyar, Varsha K; Berardini, Tanya Z; Tweedie, Susan; Foulger, Rebecca E; Osumi-Sutherland, David; Campbell, Nancy H; Huntley, Rachael P; Talmud, Philippa J; Blake, Judith A; Breckenridge, Ross; Riley, Paul R; Lambiase, Pier D; Elliott, Perry M; Clapp, Lucie; Tinker, Andrew; Hill, David P

2018-02-01

A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. © 2018 The Authors.

Information technology developments within the national biological information infrastructure

USGS Publications Warehouse

Cotter, G.; Frame, M.T.

2000-01-01

Looking out an office window or exploring a community park, one can easily see the tremendous challenges that biological information presents the computer science community. Biological information varies in format and content depending whether or not it is information pertaining to a particular species (i.e. Brown Tree Snake), or a specific ecosystem, which often includes multiple species, land use characteristics, and geospatially referenced information. The complexity and uniqueness of each individual species or ecosystem do not easily lend themselves to today's computer science tools and applications. To address the challenges that the biological enterprise presents the National Biological Information Infrastructure (NBII) (http://www.nbii.gov) was established in 1993. The NBII is designed to address these issues on a National scale within the United States, and through international partnerships abroad. This paper discusses current computer science efforts within the National Biological Information Infrastructure Program and future computer science research endeavors that are needed to address the ever-growing issues related to our Nation's biological concerns.

Energy Efficient Communication Using Relationships between Biological Signals for Ubiquitous Health Monitoring

NASA Astrophysics Data System (ADS)

Lee, Songjun; Na, Doosu; Koo, Bonmin

Wireless sensor networks with a star network topology are commonly applied for health monitoring systems. To determine the condition of a patient, sensor nodes are attached to the body to transmit the data to a coordinator. However, this process is inefficient because the coordinator is always communicating with each sensor node resulting in a data processing workload for the coordinator that becomes much greater than that of the sensor nodes. In this paper, a method is proposed to reduce the number of data transmissions from the sensor nodes to the coordinator by establishing a threshold for data from the biological signals to ensure that only relevant information is transmitted. This results in a dramatic reduction in power consumption throughout the entire network.

The importance of benthic-pelagic coupling for marine ecosystem functioning in a changing world.

PubMed

Griffiths, Jennifer R; Kadin, Martina; Nascimento, Francisco J A; Tamelander, Tobias; Törnroos, Anna; Bonaglia, Stefano; Bonsdorff, Erik; Brüchert, Volker; Gårdmark, Anna; Järnström, Marie; Kotta, Jonne; Lindegren, Martin; Nordström, Marie C; Norkko, Alf; Olsson, Jens; Weigel, Benjamin; Žydelis, Ramunas; Blenckner, Thorsten; Niiranen, Susa; Winder, Monika

2017-06-01

Benthic-pelagic coupling is manifested as the exchange of energy, mass, or nutrients between benthic and pelagic habitats. It plays a prominent role in aquatic ecosystems, and it is crucial to functions from nutrient cycling to energy transfer in food webs. Coastal and estuarine ecosystem structure and function are strongly affected by anthropogenic pressures; however, there are large gaps in our understanding of the responses of inorganic nutrient and organic matter fluxes between benthic habitats and the water column. We illustrate the varied nature of physical and biological benthic-pelagic coupling processes and their potential sensitivity to three anthropogenic pressures - climate change, nutrient loading, and fishing - using the Baltic Sea as a case study and summarize current knowledge on the exchange of inorganic nutrients and organic material between habitats. Traditionally measured benthic-pelagic coupling processes (e.g., nutrient exchange and sedimentation of organic material) are to some extent quantifiable, but the magnitude and variability of biological processes are rarely assessed, preventing quantitative comparisons. Changing oxygen conditions will continue to have widespread effects on the processes that govern inorganic and organic matter exchange among habitats while climate change and nutrient load reductions may have large effects on organic matter sedimentation. Many biological processes (predation, bioturbation) are expected to be sensitive to anthropogenic drivers, but the outcomes for ecosystem function are largely unknown. We emphasize how improved empirical and experimental understanding of benthic-pelagic coupling processes and their variability are necessary to inform models that can quantify the feedbacks among processes and ecosystem responses to a changing world. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

High-contrast 3D microscopic imaging of deep layers in a biological medium

NASA Astrophysics Data System (ADS)

Faridian, Ahmad; Pedrini, Giancarlo; Osten, Wolfgang

2014-03-01

Multilayer imaging of biological specimens is a demanding field of research, but scattering is one of the major obstacles in imaging the internal layers of a specimen. Although in many studies the biological object is assumed to be a weak scatterer, this condition is hardly satisfied for sub-millimeter sized organisms. The scattering medium is inhomogeneously distributed inside the specimen. Therefore, the scattering which occurs in the upper layers of a given internal layer of interest is different from the lower layers. That results in a different amount of collectable information for a specific point in the layer from each view. An opposed view dark-field digital holographic microscope (DHM) has been implemented in this work to collect the information concurrently from both views and increase the image quality. Implementing a DHM system gives the possibility to perform digital refocusing process and obtain multilayer images from each side without depth scanning of the object. The results have been presented and discussed here for a Drosophila embryo.

DL-ReSuMe: A Delay Learning-Based Remote Supervised Method for Spiking Neurons.

PubMed

Taherkhani, Aboozar; Belatreche, Ammar; Li, Yuhua; Maguire, Liam P

2015-12-01

Recent research has shown the potential capability of spiking neural networks (SNNs) to model complex information processing in the brain. There is biological evidence to prove the use of the precise timing of spikes for information coding. However, the exact learning mechanism in which the neuron is trained to fire at precise times remains an open problem. The majority of the existing learning methods for SNNs are based on weight adjustment. However, there is also biological evidence that the synaptic delay is not constant. In this paper, a learning method for spiking neurons, called delay learning remote supervised method (DL-ReSuMe), is proposed to merge the delay shift approach and ReSuMe-based weight adjustment to enhance the learning performance. DL-ReSuMe uses more biologically plausible properties, such as delay learning, and needs less weight adjustment than ReSuMe. Simulation results have shown that the proposed DL-ReSuMe approach achieves learning accuracy and learning speed improvements compared with ReSuMe.

BioCore Guide: A Tool for Interpreting the Core Concepts of Vision and Change for Biology Majors.

PubMed

Brownell, Sara E; Freeman, Scott; Wenderoth, Mary Pat; Crowe, Alison J

2014-01-01

Vision and Change in Undergraduate Biology Education outlined five core concepts intended to guide undergraduate biology education: 1) evolution; 2) structure and function; 3) information flow, exchange, and storage; 4) pathways and transformations of energy and matter; and 5) systems. We have taken these general recommendations and created a Vision and Change BioCore Guide-a set of general principles and specific statements that expand upon the core concepts, creating a framework that biology departments can use to align with the goals of Vision and Change. We used a grassroots approach to generate the BioCore Guide, beginning with faculty ideas as the basis for an iterative process that incorporated feedback from more than 240 biologists and biology educators at a diverse range of academic institutions throughout the United States. The final validation step in this process demonstrated strong national consensus, with more than 90% of respondents agreeing with the importance and scientific accuracy of the statements. It is our hope that the BioCore Guide will serve as an agent of change for biology departments as we move toward transforming undergraduate biology education. © 2014 S. E. Brownell 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).

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

PubMed

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

2016-01-01

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

Googling trends in conservation biology.

PubMed

Proulx, Raphaël; Massicotte, Philippe; Pépino, Marc

2014-02-01

Web-crawling approaches, that is, automated programs data mining the internet to obtain information about a particular process, have recently been proposed for monitoring early signs of ecosystem degradation or for establishing crop calendars. However, lack of a clear conceptual and methodological framework has prevented the development of such approaches within the field of conservation biology. Our objective was to illustrate how Google Trends, a freely accessible web-crawling engine, can be used to track changes in timing of biological processes, spatial distribution of invasive species, and level of public awareness about key conservation issues. Google Trends returns the number of internet searches that were made for a keyword in a given region of the world over a defined period. Using data retrieved online for 13 countries, we exemplify how Google Trends can be used to study the timing of biological processes, such as the seasonal recurrence of pollen release or mosquito outbreaks across a latitudinal gradient. We mapped the spatial extent of results from Google Trends for 5 invasive species in the United States and found geographic patterns in invasions that are consistent with their coarse-grained distribution at state levels. From 2004 through 2012, Google Trends showed that the level of public interest and awareness about conservation issues related to ecosystem services, biodiversity, and climate change increased, decreased, and followed both trends, respectively. Finally, to further the development of research approaches at the interface of conservation biology, collective knowledge, and environmental management, we developed an algorithm that allows the rapid retrieval of Google Trends data. © 2013 Society for Conservation Biology.

Automated Morphological and Morphometric Analysis of Mass Spectrometry Imaging Data: Application to Biomarker Discovery

NASA Astrophysics Data System (ADS)

Picard de Muller, Gaël; Ait-Belkacem, Rima; Bonnel, David; Longuespée, Rémi; Stauber, Jonathan

2017-12-01

Mass spectrometry imaging datasets are mostly analyzed in terms of average intensity in regions of interest. However, biological tissues have different morphologies with several sizes, shapes, and structures. The important biological information, contained in this highly heterogeneous cellular organization, could be hidden by analyzing the average intensities. Finding an analytical process of morphology would help to find such information, describe tissue model, and support identification of biomarkers. This study describes an informatics approach for the extraction and identification of mass spectrometry image features and its application to sample analysis and modeling. For the proof of concept, two different tissue types (healthy kidney and CT-26 xenograft tumor tissues) were imaged and analyzed. A mouse kidney model and tumor model were generated using morphometric - number of objects and total surface - information. The morphometric information was used to identify m/z that have a heterogeneous distribution. It seems to be a worthwhile pursuit as clonal heterogeneity in a tumor is of clinical relevance. This study provides a new approach to find biomarker or support tissue classification with more information. [Figure not available: see fulltext.

Image processing tools dedicated to quantification in 3D fluorescence microscopy

NASA Astrophysics Data System (ADS)

Dieterlen, A.; De Meyer, A.; Colicchio, B.; Le Calvez, S.; Haeberlé, O.; Jacquey, S.

2006-05-01

3-D optical fluorescent microscopy now becomes an efficient tool for the volume investigation of living biological samples. Developments in instrumentation have permitted to beat off the conventional Abbe limit. In any case the recorded image can be described by the convolution equation between the original object and the Point Spread Function (PSF) of the acquisition system. Due to the finite resolution of the instrument, the original object is recorded with distortions and blurring, and contaminated by noise. This induces that relevant biological information cannot be extracted directly from raw data stacks. If the goal is 3-D quantitative analysis, then to assess optimal performance of the instrument and to ensure the data acquisition reproducibility, the system characterization is mandatory. The PSF represents the properties of the image acquisition system; we have proposed the use of statistical tools and Zernike moments to describe a 3-D PSF system and to quantify the variation of the PSF. This first step toward standardization is helpful to define an acquisition protocol optimizing exploitation of the microscope depending on the studied biological sample. Before the extraction of geometrical information and/or intensities quantification, the data restoration is mandatory. Reduction of out-of-focus light is carried out computationally by deconvolution process. But other phenomena occur during acquisition, like fluorescence photo degradation named "bleaching", inducing an alteration of information needed for restoration. Therefore, we have developed a protocol to pre-process data before the application of deconvolution algorithms. A large number of deconvolution methods have been described and are now available in commercial package. One major difficulty to use this software is the introduction by the user of the "best" regularization parameters. We have pointed out that automating the choice of the regularization level; also greatly improves the reliability of the measurements although it facilitates the use. Furthermore, to increase the quality and the repeatability of quantitative measurements a pre-filtering of images improves the stability of deconvolution process. In the same way, the PSF prefiltering stabilizes the deconvolution process. We have shown that Zemike polynomials can be used to reconstruct experimental PSF, preserving system characteristics and removing the noise contained in the PSF.

Generation of computationally predicted Adverse Outcome Pathway networks through integration of publicly available in vivo, in vitro, phenotype, and biological pathway data.

EPA Science Inventory

The Adverse Outcome Pathway (AOP) framework is becoming a widely used tool for organizing and summarizing the mechanistic information connecting molecular perturbations by environmental stressors with adverse ecological and human health outcomes. However, the conventional process...

Apes have eyes to the future.

PubMed

Vonk, Jennifer

2016-09-01

Kano and Hirata (Current Biology, 25, 2513-2517, 2015) recently showed that apes process object and location information and anticipate the repeated presentation of such events in short film clips. Their methodology, using eyetracking, can provide a foundation for further explications of long-term prospective and episodic memory in nonverbal species.

NCI-CPTAC DREAM Proteogenomics Challenge (Registration Now Open) | Office of Cancer Clinical Proteomics Research

Cancer.gov

Proteogenomics, integration of proteomics, genomics, and transcriptomics, is an emerging approach that promises to advance basic, translational and clinical research.  By combining genomic and proteomic information, leading scientists are gaining new insights due to a more complete and unified understanding of complex biological processes.

Adaptive Neurons For Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Tawel, Raoul

1990-01-01

Training time decreases dramatically. In improved mathematical model of neural-network processor, temperature of neurons (in addition to connection strengths, also called weights, of synapses) varied during supervised-learning phase of operation according to mathematical formalism and not heuristic rule. Evidence that biological neural networks also process information at neuronal level.

COMPLEX HOST-PARASITE SYSTEMS IN MARTES: IMPLICATIONS FOR CONSERVATION BIOLOGY OF ENDEMIC FAUNAS.

USDA-ARS?s Scientific Manuscript database

Complex assemblages of hosts and parasites reveal insights about biogeography and ecology and inform us about processes which serve to structure faunal diversity and the biosphere in space and time. Exploring aspects of parasite diversity among martens (species of Martes) and other mustelids reveal...

Reading Phylogenetic Trees: The Effects of Tree Orientation and Text Processing on Comprehension

ERIC Educational Resources Information Center

Novick, Laura R.; Stull, Andrew T.; Catley, Kefyn M.

2012-01-01

Although differently formatted cladograms (hierarchical diagrams depicting evolutionary relationships among taxa) depict the same information, they may not be equally easy to comprehend. Undergraduate biology students attempted to translate cladograms from the diagonal to the rectangular format. The "backbone" line of each diagonal…

Molecular Thermodynamics for Cell Biology as Taught with Boxes

ERIC Educational Resources Information Center

Mayorga, Luis S.; Lopez, Maria Jose; Becker, Wayne M.

2012-01-01

Thermodynamic principles are basic to an understanding of the complex fluxes of energy and information required to keep cells alive. These microscopic machines are nonequilibrium systems at the micron scale that are maintained in pseudo-steady-state conditions by very sophisticated processes. Therefore, several nonstandard concepts need to be…

Automatic Classification Using Supervised Learning in a Medical Document Filtering Application.

ERIC Educational Resources Information Center

Mostafa, J.; Lam, W.

2000-01-01

Presents a multilevel model of the information filtering process that permits document classification. Evaluates a document classification approach based on a supervised learning algorithm, measures the accuracy of the algorithm in a neural network that was trained to classify medical documents on cell biology, and discusses filtering…

Two Dream Machines: Television and the Human Brain.

ERIC Educational Resources Information Center

Deming, Caren J.

Research into brain physiology and dream psychology have helped to illuminate the biological purposes and processes of dreaming. Physical and functional characteristics shared by dreaming and television include the perception of visual and auditory images, operation in a binary mode, and the encoding of visual information. Research is needed in…

Biological tooth replacement

PubMed Central

Sartaj, Rachel; Sharpe, Paul

2006-01-01

Teeth develop from a series of reciprocal interactions that take place between epithelium and mesenchyme during development of the mouth that begin early in mammalian embryogenesis. The molecular control of key processes in tooth development such as initiation, morphogenesis and cytodifferentiation are being increasingly better understood, to the point where this information can be used as the basis for approaches to produce biological replacement teeth (BioTeeth). This review outlines the current approaches, ideas and progress towards the production of BioTeeth that could form an alternative method for replacing lost or damaged teeth. PMID:17005022

Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering.

PubMed

Menolascina, Filippo; Bellomo, Domenico; Maiwald, Thomas; Bevilacqua, Vitoantonio; Ciminelli, Caterina; Paradiso, Angelo; Tommasi, Stefania

2009-10-15

Mechanistic models are becoming more and more popular in Systems Biology; identification and control of models underlying biochemical pathways of interest in oncology is a primary goal in this field. Unfortunately the scarce availability of data still limits our understanding of the intrinsic characteristics of complex pathologies like cancer: acquiring information for a system understanding of complex reaction networks is time consuming and expensive. Stimulus response experiments (SRE) have been used to gain a deeper insight into the details of biochemical mechanisms underlying cell life and functioning. Optimisation of the input time-profile, however, still remains a major area of research due to the complexity of the problem and its relevance for the task of information retrieval in systems biology-related experiments. We have addressed the problem of quantifying the information associated to an experiment using the Fisher Information Matrix and we have proposed an optimal experimental design strategy based on evolutionary algorithm to cope with the problem of information gathering in Systems Biology. On the basis of the theoretical results obtained in the field of control systems theory, we have studied the dynamical properties of the signals to be used in cell stimulation. The results of this study have been used to develop a microfluidic device for the automation of the process of cell stimulation for system identification. We have applied the proposed approach to the Epidermal Growth Factor Receptor pathway and we observed that it minimises the amount of parametric uncertainty associated to the identified model. A statistical framework based on Monte-Carlo estimations of the uncertainty ellipsoid confirmed the superiority of optimally designed experiments over canonical inputs. The proposed approach can be easily extended to multiobjective formulations that can also take advantage of identifiability analysis. Moreover, the availability of fully automated microfluidic platforms explicitly developed for the task of biochemical model identification will hopefully reduce the effects of the 'data rich--data poor' paradox in Systems Biology.

Predicting PDZ domain mediated protein interactions from structure

PubMed Central

2013-01-01

Background PDZ domains are structural protein domains that recognize simple linear amino acid motifs, often at protein C-termini, and mediate protein-protein interactions (PPIs) in important biological processes, such as ion channel regulation, cell polarity and neural development. PDZ domain-peptide interaction predictors have been developed based on domain and peptide sequence information. Since domain structure is known to influence binding specificity, we hypothesized that structural information could be used to predict new interactions compared to sequence-based predictors. Results We developed a novel computational predictor of PDZ domain and C-terminal peptide interactions using a support vector machine trained with PDZ domain structure and peptide sequence information. Performance was estimated using extensive cross validation testing. We used the structure-based predictor to scan the human proteome for ligands of 218 PDZ domains and show that the predictions correspond to known PDZ domain-peptide interactions and PPIs in curated databases. The structure-based predictor is complementary to the sequence-based predictor, finding unique known and novel PPIs, and is less dependent on training–testing domain sequence similarity. We used a functional enrichment analysis of our hits to create a predicted map of PDZ domain biology. This map highlights PDZ domain involvement in diverse biological processes, some only found by the structure-based predictor. Based on this analysis, we predict novel PDZ domain involvement in xenobiotic metabolism and suggest new interactions for other processes including wound healing and Wnt signalling. Conclusions We built a structure-based predictor of PDZ domain-peptide interactions, which can be used to scan C-terminal proteomes for PDZ interactions. We also show that the structure-based predictor finds many known PDZ mediated PPIs in human that were not found by our previous sequence-based predictor and is less dependent on training–testing domain sequence similarity. Using both predictors, we defined a functional map of human PDZ domain biology and predict novel PDZ domain function. Users may access our structure-based and previous sequence-based predictors at http://webservice.baderlab.org/domains/POW. PMID:23336252

Intracellular subsurface imaging using a hybrid shear-force feedback/scanning quantitative phase microscopy technique

NASA Astrophysics Data System (ADS)

Edward, Kert

Quantitative phase microscopy (QPM) allows for the imaging of translucent or transparent biological specimens without the need for exogenous contrast agents. This technique is usually applied towards the investigation of simple cells such as red blood cells which are typically enucleated and can be considered to be homogenous. However, most biological cells are nucleated and contain other interesting intracellular organelles. It has been established that the physical characteristics of certain subsurface structures such as the shape and roughness of the nucleus is well correlated with onset and progress of pathological conditions such as cancer. Although the acquired quantitative phase information of biological cells contains surface information as well as coupled subsurface information, the latter has been ignored up until now. A novel scanning quantitative phase imaging system unencumbered by 2pi ambiguities is hereby presented. This system is incorporated into a shear-force feedback scheme which allows for simultaneous phase and topography determination. It will be shown how subsequent image processing of these two data sets allows for the extraction of the subsurface component in the phase data and in vivo cell refractometry studies. Both fabricated samples and biological cells ranging from rat fibroblast cells to malaria infected human erythrocytes were investigated as part of this research. The results correlate quite well with that obtained via other microscopy techniques.

On the integration of protein-protein interaction networks with gene expression and 3D structural data: What can be gained?

NASA Astrophysics Data System (ADS)

Bertolazzi, Paola; Bock, Mary Ellen; Guerra, Concettina; Paci, Paola; Santoni, Daniele

2014-06-01

The biological role of proteins has been analyzed from different perspectives, initially by considering proteins as isolated biological entities, then as cooperating entities that perform their function by interacting with other molecules. There are other dimensions that are important for the complete understanding of the biological processes: time and location. However a protein is rarely annotated with temporal and spatial information. Experimental Protein-Proteins Interaction (PPI) data are static; furthermore they generally do not include transient interactions which are a considerable fraction of the interactome of many organisms. One way to incorporate temporal and condition information is to use other sources of information, such as gene expression data and 3D structural data. Here we review work done to understand the insight that can be gained by enriching PPI data with gene expression and 3D structural data. In particular, we address the following questions: Can the dynamics of a single protein or of an interaction be accurately derived from these data? Can the assembly-disassembly of protein complexes be traced over time? What type of topological changes occur in a PPI network architecture over time?

ChlamyCyc: an integrative systems biology database and web-portal for Chlamydomonas reinhardtii.

PubMed

May, Patrick; Christian, Jan-Ole; Kempa, Stefan; Walther, Dirk

2009-05-04

The unicellular green alga Chlamydomonas reinhardtii is an important eukaryotic model organism for the study of photosynthesis and plant growth. In the era of modern high-throughput technologies there is an imperative need to integrate large-scale data sets from high-throughput experimental techniques using computational methods and database resources to provide comprehensive information about the molecular and cellular organization of a single organism. In the framework of the German Systems Biology initiative GoFORSYS, a pathway database and web-portal for Chlamydomonas (ChlamyCyc) was established, which currently features about 250 metabolic pathways with associated genes, enzymes, and compound information. ChlamyCyc was assembled using an integrative approach combining the recently published genome sequence, bioinformatics methods, and experimental data from metabolomics and proteomics experiments. We analyzed and integrated a combination of primary and secondary database resources, such as existing genome annotations from JGI, EST collections, orthology information, and MapMan classification. ChlamyCyc provides a curated and integrated systems biology repository that will enable and assist in systematic studies of fundamental cellular processes in Chlamydomonas. The ChlamyCyc database and web-portal is freely available under http://chlamycyc.mpimp-golm.mpg.de.

Artificial retina model for the retinally blind based on wavelet transform

NASA Astrophysics Data System (ADS)

Zeng, Yan-an; Song, Xin-qiang; Jiang, Fa-gang; Chang, Da-ding

2007-01-01

Artificial retina is aimed for the stimulation of remained retinal neurons in the patients with degenerated photoreceptors. Microelectrode arrays have been developed for this as a part of stimulator. Design such microelectrode arrays first requires a suitable mathematical method for human retinal information processing. In this paper, a flexible and adjustable human visual information extracting model is presented, which is based on the wavelet transform. With the flexible of wavelet transform to image information processing and the consistent to human visual information extracting, wavelet transform theory is applied to the artificial retina model for the retinally blind. The response of the model to synthetic image is shown. The simulated experiment demonstrates that the model behaves in a manner qualitatively similar to biological retinas and thus may serve as a basis for the development of an artificial retina.

The study on serum and urine of renal interstitial fibrosis rats induced by unilateral ureteral obstruction based on metabonomics and network analysis methods.

PubMed

Xiang, Zheng; Sun, Hao; Cai, Xiaojun; Chen, Dahui

2016-04-01

Transmission of biological information is a biochemical process of multistep cascade from genes/proteins to metabolites. However, because most metabolites reflect the terminal information of the biochemical process, it is difficult to describe the transmission process of disease information in terms of the metabolomics strategy. In this paper, by incorporating network and metabolomics methods, an integrated approach was proposed to systematically investigate and explain the molecular mechanism of renal interstitial fibrosis. Through analysis of the network, the cascade transmission process of disease information starting from genes/proteins to metabolites was putatively identified and uncovered. The results indicated that renal fibrosis was involved in metabolic pathways of glycerophospholipid metabolism, biosynthesis of unsaturated fatty acids and arachidonic acid metabolism, riboflavin metabolism, tyrosine metabolism, and sphingolipid metabolism. These pathways involve kidney disease genes such as TGF-β1 and P2RX7. Our results showed that combining metabolomics and network analysis can provide new strategies and ideas for the interpretation of pathogenesis of disease with full consideration of "gene-protein-metabolite."

Oxygen isotopes and P cycle in the soil/plant system: where are we heading?

NASA Astrophysics Data System (ADS)

Tamburini, Federica; Pfahler, Verena; von Sperber, Christian; Bernasconi, Stefano; Frossard, Emmanuel

2014-05-01

Phosphorus (P) is a major nutrient for all living organisms. In the terrestrial environment, P is a double-edged sword. For this reason, a better understanding of P cycling in the soil/plant system and the processes influencing its transfers and transformations is needed to provide agricultural and environmental managers with better concepts for P use. In fact, whereas the effect of abiotic reactions on the P concentration in the soil solution are well understood, we still know too little about the forms of soil organic P, and about the importance of soil biological processes (e.g. on organic matter mineralization-immobilization, or on the role of microorganisms) in controlling P availability. Together with more traditional and routine analysis for P, in the last 20 years researchers have started using the ratio of stable oxygen isotopes in phosphate (δ18O-P) to investigate P cycle in the soil/plant system. The scientific community interested in using this isotopic tracer is expanding because δ18O-P has proven to provide important information on biological processes. A large part of the published studies has shown how δ18O-P can be used to track P in the environment, providing information on P transfer from one pool and/or sink to the other. The other part has used this tool as a tracer of biological activity, clarifying how P is cycled through the microbial biomass or by plants. Together with a short review of the most relevant published results, we will discuss whether, and under which conditions, the δ18O-P can be applied to study P cycling and transformations from the process to the ecosystem level.

FFPred 2.0: Improved Homology-Independent Prediction of Gene Ontology Terms for Eukaryotic Protein Sequences

PubMed Central

Minneci, Federico; Piovesan, Damiano; Cozzetto, Domenico; Jones, David T.

2013-01-01

To understand fully cell behaviour, biologists are making progress towards cataloguing the functional elements in the human genome and characterising their roles across a variety of tissues and conditions. Yet, functional information – either experimentally validated or computationally inferred by similarity – remains completely missing for approximately 30% of human proteins. FFPred was initially developed to bridge this gap by targeting sequences with distant or no homologues of known function and by exploiting clear patterns of intrinsic disorder associated with particular molecular activities and biological processes. Here, we present an updated and improved version, which builds on larger datasets of protein sequences and annotations, and uses updated component feature predictors as well as revised training procedures. FFPred 2.0 includes support vector regression models for the prediction of 442 Gene Ontology (GO) terms, which largely expand the coverage of the ontology and of the biological process category in particular. The GO term list mainly revolves around macromolecular interactions and their role in regulatory, signalling, developmental and metabolic processes. Benchmarking experiments on newly annotated proteins show that FFPred 2.0 provides more accurate functional assignments than its predecessor and the ProtFun server do; also, its assignments can complement information obtained using BLAST-based transfer of annotations, improving especially prediction in the biological process category. Furthermore, FFPred 2.0 can be used to annotate proteins belonging to several eukaryotic organisms with a limited decrease in prediction quality. We illustrate all these points through the use of both precision-recall plots and of the COGIC scores, which we recently proposed as an alternative numerical evaluation measure of function prediction accuracy. PMID:23717476

Natural pigments: carotenoids, anthocyanins, and betalains--characteristics, biosynthesis, processing, and stability.

PubMed

Delgado-Vargas, F; Jiménez, A R; Paredes-López, O

2000-05-01

Pigments are present in all living matter and provide attractive colors and play basic roles in the development of organisms. Human beings, like most animals, come in contact with their surroundings through color, and things can or cannot be acceptable based on their color characteristics. This review presents the basic information about pigments focusing attention on the natural ones; it emphasizes the principal plant pigments: carotenoids, anthocyanins, and betalains. Special considerations are given to their salient characteristics; to their biosynthesis, taking into account the biochemical and molecular biology information generated in their elucidation; and to the processing and stability properties of these compounds as food colorants.

Brains are not just neurons. Comment on “Toward a computational framework for cognitive biology: Unifying approaches from cognitive neuroscience and comparative cognition” by Fitch

NASA Astrophysics Data System (ADS)

Huber, Ludwig

2014-09-01

This comment addresses the first component of Fitch's framework: the computational power of single neurons [3]. Although I agree that traditional models of neural computation have vastly underestimated the computational power of single neurons, I am hesitant to follow him completely. The exclusive focus on neurons is likely to underestimate the importance of other cells in the brain. In the last years, two such cell types have received appropriate attention by neuroscientists: interneurons and glia. Interneurons are small, tightly packed cells involved in the control of information processing in learning and memory. Rather than transmitting externally (like motor or sensory neurons), these neurons process information within internal circuits of the brain (therefore also called 'relay neurons'). Some specialized interneuron subtypes temporally regulate the flow of information in a given cortical circuit during relevant behavioral events [4]. In the human brain approx. 100 billion interneurons control information processing and are implicated in disorders such as epilepsy and Parkinson's.

On the nature of global classification

NASA Technical Reports Server (NTRS)

Wheelis, M. L.; Kandler, O.; Woese, C. R.

1992-01-01

Molecular sequencing technology has brought biology into the era of global (universal) classification. Methodologically and philosophically, global classification differs significantly from traditional, local classification. The need for uniformity requires that higher level taxa be defined on the molecular level in terms of universally homologous functions. A global classification should reflect both principal dimensions of the evolutionary process: genealogical relationship and quality and extent of divergence within a group. The ultimate purpose of a global classification is not simply information storage and retrieval; such a system should also function as an heuristic representation of the evolutionary paradigm that exerts a directing influence on the course of biology. The global system envisioned allows paraphyletic taxa. To retain maximal phylogenetic information in these cases, minor notational amendments in existing taxonomic conventions should be adopted.

Using the WWW to supply the molecular biology lab.

PubMed

Labant, M; Anderson, R

2000-01-01

The World Wide Web is changing the face of business today and will continue to reshape it in the coming years. Nonvalue-added processes are being eliminated as organizations reengineer their internal ways of doing business in a continual effort to reduce costs and remain competitive. Current electronic market followers claim that gateways, or portals, of information will be the wave of the future. This does not mean that individual suppliers' websites will become extinct. It means that content will continue to change and adapt so that sites will continue to be more useful. If gateways do turn out to be the user's choice for product information presentation in the future, expect more consolidated sites devoted to specific product categories, such as chemicals, molecular biology supplies, and the like.

Increasing rigor in NMR-based metabolomics through validated and open source tools

PubMed Central

Eghbalnia, Hamid R; Romero, Pedro R; Westler, William M; Baskaran, Kumaran; Ulrich, Eldon L; Markley, John L

2016-01-01

The metabolome, the collection of small molecules associated with an organism, is a growing subject of inquiry, with the data utilized for data-intensive systems biology, disease diagnostics, biomarker discovery, and the broader characterization of small molecules in mixtures. Owing to their close proximity to the functional endpoints that govern an organism’s phenotype, metabolites are highly informative about functional states. The field of metabolomics identifies and quantifies endogenous and exogenous metabolites in biological samples. Information acquired from nuclear magnetic spectroscopy (NMR), mass spectrometry (MS), and the published literature, as processed by statistical approaches, are driving increasingly wider applications of metabolomics. This review focuses on the role of databases and software tools in advancing the rigor, robustness, reproducibility, and validation of metabolomics studies. PMID:27643760

Mining meiosis and gametogenesis with DNA microarrays.

PubMed

Schlecht, Ulrich; Primig, Michael

2003-04-01

Gametogenesis is a key developmental process that involves complex transcriptional regulation of numerous genes including many that are conserved between unicellular eukaryotes and mammals. Recent expression-profiling experiments using microarrays have provided insight into the co-ordinated transcription of several hundred genes during mitotic growth and meiotic development in budding and fission yeast. Furthermore, microarray-based studies have identified numerous loci that are regulated during the cell cycle or expressed in a germ-cell specific manner in eukaryotic model systems like Caenorhabditis elegans, Mus musculus as well as Homo sapiens. The unprecedented amount of information produced by post-genome biology has spawned novel approaches to organizing biological knowledge using currently available information technology. This review outlines experiments that contribute to an emerging comprehensive picture of the molecular machinery governing sexual reproduction in eukaryotes.

Increasing rigor in NMR-based metabolomics through validated and open source tools.

PubMed

Eghbalnia, Hamid R; Romero, Pedro R; Westler, William M; Baskaran, Kumaran; Ulrich, Eldon L; Markley, John L

2017-02-01

The metabolome, the collection of small molecules associated with an organism, is a growing subject of inquiry, with the data utilized for data-intensive systems biology, disease diagnostics, biomarker discovery, and the broader characterization of small molecules in mixtures. Owing to their close proximity to the functional endpoints that govern an organism's phenotype, metabolites are highly informative about functional states. The field of metabolomics identifies and quantifies endogenous and exogenous metabolites in biological samples. Information acquired from nuclear magnetic spectroscopy (NMR), mass spectrometry (MS), and the published literature, as processed by statistical approaches, are driving increasingly wider applications of metabolomics. This review focuses on the role of databases and software tools in advancing the rigor, robustness, reproducibility, and validation of metabolomics studies. Copyright © 2016. Published by Elsevier Ltd.

Social insect colony as a biological regulatory system: modelling information flow in dominance networks.

PubMed

Nandi, Anjan K; Sumana, Annagiri; Bhattacharya, Kunal

2014-12-06

Social insects provide an excellent platform to investigate flow of information in regulatory systems since their successful social organization is essentially achieved by effective information transfer through complex connectivity patterns among the colony members. Network representation of such behavioural interactions offers a powerful tool for structural as well as dynamical analysis of the underlying regulatory systems. In this paper, we focus on the dominance interaction networks in the tropical social wasp Ropalidia marginata-a species where behavioural observations indicate that such interactions are principally responsible for the transfer of information between individuals about their colony needs, resulting in a regulation of their own activities. Our research reveals that the dominance networks of R. marginata are structurally similar to a class of naturally evolved information processing networks, a fact confirmed also by the predominance of a specific substructure-the 'feed-forward loop'-a key functional component in many other information transfer networks. The dynamical analysis through Boolean modelling confirms that the networks are sufficiently stable under small fluctuations and yet capable of more efficient information transfer compared to their randomized counterparts. Our results suggest the involvement of a common structural design principle in different biological regulatory systems and a possible similarity with respect to the effect of selection on the organization levels of such systems. The findings are also consistent with the hypothesis that dominance behaviour has been shaped by natural selection to co-opt the information transfer process in such social insect species, in addition to its primal function of mediation of reproductive competition in the colony. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Students Mental Representation of Biology Diagrams/Pictures Conventions Based on Formation of Causal Network

NASA Astrophysics Data System (ADS)

Sampurno, A. W.; Rahmat, A.; Diana, S.

2017-09-01

Diagrams/pictures conventions is one form of visual media that often used to assist students in understanding the biological concepts. The effectiveness of use diagrams/pictures in biology learning at school level has also been mostly reported. This study examines the ability of high school students in reading diagrams/pictures biological convention which is described by Mental Representation based on formation of causal networks. The study involved 30 students 11th grade MIA senior high school Banten Indonesia who are studying the excretory system. MR data obtained by Instrument worksheet, developed based on CNET-protocol, in which there are diagrams/drawings of nephron structure and urinary mechanism. Three patterns formed MR, namely Markov chain, feedback control with a single measurement, and repeated feedback control with multiple measurement. The third pattern is the most dominating pattern, differences in the pattern of MR reveal the difference in how and from which point the students begin to uncover important information contained in the diagram to establish a causal networks. Further analysis shows that a difference in the pattern of MR relate to how complex the students process the information contained in the diagrams/pictures.

In search of mitochondrial mechanisms: interfield excursions between cell biology and biochemistry.

PubMed

Bechtel, William; Abrahamsen, Adele

2007-01-01

Developing models of biological mechanisms, such as those involved in respiration in cells, often requires collaborative effort drawing upon techniques developed and information generated in different disciplines. Biochemists in the early decades of the 20th century uncovered all but the most elusive chemical operations involved in cellular respiration, but were unable to align the reaction pathways with particular structures in the cell. During the period 1940-1965 cell biology was emerging as a new discipline and made distinctive contributions to understanding the role of the mitochondrion and its component parts in cellular respiration. In particular, by developing techniques for localizing enzymes or enzyme systems in specific cellular components, cell biologists provided crucial information about the organized structures in which the biochemical reactions occurred. Although the idea that biochemical operations are intimately related to and depend on cell structures was at odds with the then-dominant emphasis on systems of soluble enzymes in biochemistry, a reconceptualization of energetic processes in the 1960s and 1970s made it clear why cell structure was critical to the biochemical account. This paper examines how numerous excursions between biochemistry and cell biology contributed a new understanding of the mechanism of cellular respiration.

Informing DSM-5: biological boundaries between bipolar I disorder, schizoaffective disorder, and schizophrenia

PubMed Central

2013-01-01

Background The fifth version of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) opted to retain existing diagnostic boundaries between bipolar I disorder, schizoaffective disorder, and schizophrenia. The debate preceding this decision focused on understanding the biologic basis of these major mental illnesses. Evidence from genetics, neuroscience, and pharmacotherapeutics informed the DSM-5 development process. The following discussion will emphasize some of the key factors at the forefront of the debate. Discussion Family studies suggest a clear genetic link between bipolar I disorder, schizoaffective disorder, and schizophrenia. However, large-scale genome-wide association studies have not been successful in identifying susceptibility genes that make substantial etiological contributions. Boundaries between psychotic disorders are not further clarified by looking at brain morphology. The fact that symptoms of bipolar I disorder, but not schizophrenia, are often responsive to medications such as lithium and other anticonvulsants must be interpreted within a larger framework of biological research. Summary For DSM-5, existing nosological boundaries between bipolar I disorder and schizophrenia were retained and schizoaffective disorder preserved as an independent diagnosis since the biological data are not yet compelling enough to justify a move to a more neurodevelopmentally continuous model of psychosis. PMID:23672587

Interfacing cellular networks of S. cerevisiae and E. coli: Connecting dynamic and genetic information

PubMed Central

2013-01-01

Background In recent years, various types of cellular networks have penetrated biology and are nowadays used omnipresently for studying eukaryote and prokaryote organisms. Still, the relation and the biological overlap among phenomenological and inferential gene networks, e.g., between the protein interaction network and the gene regulatory network inferred from large-scale transcriptomic data, is largely unexplored. Results We provide in this study an in-depth analysis of the structural, functional and chromosomal relationship between a protein-protein network, a transcriptional regulatory network and an inferred gene regulatory network, for S. cerevisiae and E. coli. Further, we study global and local aspects of these networks and their biological information overlap by comparing, e.g., the functional co-occurrence of Gene Ontology terms by exploiting the available interaction structure among the genes. Conclusions Although the individual networks represent different levels of cellular interactions with global structural and functional dissimilarities, we observe crucial functions of their network interfaces for the assembly of protein complexes, proteolysis, transcription, translation, metabolic and regulatory interactions. Overall, our results shed light on the integrability of these networks and their interfacing biological processes. PMID:23663484

Biocharts: a visual formalism for complex biological systems

PubMed Central

Kugler, Hillel; Larjo, Antti; Harel, David

2010-01-01

We address one of the central issues in devising languages, methods and tools for the modelling and analysis of complex biological systems, that of linking high-level (e.g. intercellular) information with lower-level (e.g. intracellular) information. Adequate ways of dealing with this issue are crucial for understanding biological networks and pathways, which typically contain huge amounts of data that continue to grow as our knowledge and understanding of a system increases. Trying to comprehend such data using the standard methods currently in use is often virtually impossible. We propose a two-tier compound visual language, which we call Biocharts, that is geared towards building fully executable models of biological systems. One of the main goals of our approach is to enable biologists to actively participate in the computational modelling effort, in a natural way. The high-level part of our language is a version of statecharts, which have been shown to be extremely successful in software and systems engineering. The statecharts can be combined with any appropriately well-defined language (preferably a diagrammatic one) for specifying the low-level dynamics of the pathways and networks. We illustrate the language and our general modelling approach using the well-studied process of bacterial chemotaxis. PMID:20022895

Electrophysiological differences in the processing of affective information in words and pictures.

PubMed

Hinojosa, José A; Carretié, Luis; Valcárcel, María A; Méndez-Bértolo, Constantino; Pozo, Miguel A

2009-06-01

It is generally assumed that affective picture viewing is related to higher levels of physiological arousal than is the reading of emotional words. However, this assertion is based mainly on studies in which the processing of either words or pictures has been investigated under heterogenic conditions. Positive, negative, relaxing, neutral, and background (stimulus fragments) words and pictures were presented to subjects in two experiments under equivalent experimental conditions. In Experiment 1, neutral words elicited an enhanced late positive component (LPC) that was associated with an increased difficulty in discriminating neutral from background stimuli. In Experiment 2, high-arousing pictures elicited an enhanced early negativity and LPC that were related to a facilitated processing for these stimuli. Thus, it seems that under some circumstances, the processing of affective information captures attention only with more biologically relevant stimuli. Also, these data might be better interpreted on the basis of those models that postulate a different access to affective information for words and pictures.