Emergent Collective Properties, Networks and Information in Biology

Emergent Collective Properties, Networks and Information in Biology

Author: J. Ricard

Publisher: Elsevier

Published: 2006-02-10

Total Pages: 295

ISBN-13: 0080462154

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The concept of network as a mathematical description of a set of states, or events, linked according to a certain topology has been developed recently and has led to a novel approach of real world. This approach is no doubt important in the field of biology. In fact biological systems can be considered networks. Thus, for instance, an enzyme-catalysed reaction is a network that links, according to a certain topology, the various states of the protein and of its complexes with the substrates and products of the chemical reaction. Connections between neurons, social relations in animal and human populations are also examples of networks. Hence there is little doubt that the concept of network transgresses the boundaries between traditional scientific disciplines. This book is aimed at discussing in physical terms these exciting new topics on simple protein model lattices, supramolecular protein edifices, multienzyme and gene networks. *Physical and mathematical approach of biological phenomena.*Offers biochemists and biologists the mathematical background required to understand the text.*Associates in the same general formulation, the ideas of communication of a message and organization of a system.*Provides a clear-cut definition and mathematical expression of the concepts of reduction, integration, emergence and complexity that were so far time-honoured and vague


Molecular Theory of the Living Cell

Molecular Theory of the Living Cell

Author: Sungchul Ji

Publisher: Springer Science & Business Media

Published: 2012-04-05

Total Pages: 751

ISBN-13: 1461421527

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The book presents the first comprehensive molecular theory of the living cell ever published since the cell doctrine was formulated in 1838-1839. It introduces into cell biology over thirty key concepts, principles and laws imported from physics, chemistry, computer science, linguistics, semiotics and philosophy. The author formulates physically, chemically and enzymologically realistic molecular mechanisms to account for basic living processes such as ligand-receptor interactions, enzymic catalysis, force-generating mechanisms in molecular motors, chromatin remodelling, and signal transduction. Possible solutions to basic and practical problems facing contemporary biology and biomedical sciences have been suggested, including pharmacotherapeutics and personalized medicine.


Feynman And Computation

Feynman And Computation

Author: Anthony Hey

Publisher: CRC Press

Published: 2018-03-08

Total Pages: 463

ISBN-13: 0429969007

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Computational properties of use to biological organisms or to the construction of computers can emerge as collective properties of systems having a large number of simple equivalent components (or neurons). The physical meaning of content-addressable memory is described by an appropriate phase space flow of the state of a system. A model of such a system is given, based on aspects of neurobiology but readily adapted to integrated circuits. The collective properties of this model produce a content-addressable memory which correctly yields an entire memory from any subpart of sufficient size. The algorithm for the time evolution of the state of the system is based on asynchronous parallel processing. Additional emergent collective properties include some capacity for generalization, familiarity recognition, categorization, error correction, and time sequence retention. The collective properties are only weakly sensitive to details of the modeling or the failure of individual devices.


From System Complexity to Emergent Properties

From System Complexity to Emergent Properties

Author: Moulay Aziz-Alaoui

Publisher: Springer Science & Business Media

Published: 2009-08-07

Total Pages: 365

ISBN-13: 3642021999

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Emergence and complexity refer to the appearance of higher-level properties and behaviours of a system that obviously comes from the collective dynamics of that system's components. These properties are not directly deducible from the lower-level motion of that system. Emergent properties are properties of the "whole'' that are not possessed by any of the individual parts making up that whole. Such phenomena exist in various domains and can be described, using complexity concepts and thematic knowledges. This book highlights complexity modelling through dynamical or behavioral systems. The pluridisciplinary purposes, developed along the chapters, are able to design links between a wide-range of fundamental and applicative Sciences. Developing such links - instead of focusing on specific and narrow researches - is characteristic of the Science of Complexity that we try to promote by this contribution.


Biological Systems: Complexity and Artificial Life

Biological Systems: Complexity and Artificial Life

Author: Jacques Ricard

Publisher: Bentham Science Publishers

Published: 2014-05-06

Total Pages: 209

ISBN-13: 1608058123

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The exponential increase in computing power in the late twentieth century has allowed researchers to gather, process and analyze large volumes of information and construct rational paradigms of systems. Life sciences are no exception and computing advances have led to the birth of fields such as functional genomics and bioinformatics and facilitated an expansion of our understanding of biological systems. Biological Systems: Complexity and Artificial Life is an essential primer on systems biology for biologists and researchers having a multidisciplinary background. The volume covers a variety of theoretical models explaining biological processes. The book starts with an introductory chapter on the classical molecular biology paradigm and progresses towards concepts related to enzyme kinetics, non equilibrium dynamics, cellular thermodynamics, molecular motion in cells and more. The book concludes with a philosophical note on the concept of the biological system.


Proceedings of the Winter, 1990, International Joint Conference on Neural Networks

Proceedings of the Winter, 1990, International Joint Conference on Neural Networks

Author: Maureen Caudill

Publisher: Taylor & Francis

Published: 2022-03-10

Total Pages: 1588

ISBN-13: 1317728335

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This two volume set provides the complete proceedings of the 1990 International Joint Conference on Neural Networks held in Washington, D.C. Complete with subject, author, and title indices, it provides an invaluable reference to the current state-of-the-art in neural networks. Included in this volume are the latest research results, applications, and products from over 2,000 researchers and application developers from around the world. Ideal as a reference for researchers and practitioners of neuroscience, the two volumes are divided into eight sections: * Neural and Cognitive Sciences * Pattern Recognition and Analysis of Network Dynamics * Learning Theory * Plenary Lecture by Bernard Widrow * Special Lectures on Self-Organizing Neural Architectures * Application Systems and Network Implementations * Robotics, Speech, Signal Processing, and Vision * Expert Systems and Other Real-World Applications


Optimality in Biological and Artificial Networks?

Optimality in Biological and Artificial Networks?

Author: Daniel S. Levine

Publisher: Psychology Press

Published: 2013-06-17

Total Pages: 528

ISBN-13: 113478645X

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This book is the third in a series based on conferences sponsored by the Metroplex Institute for Neural Dynamics, an interdisciplinary organization of neural network professionals in academia and industry. The topics selected are of broad interest to both those interested in designing machines to perform intelligent functions and those interested in studying how these functions are actually performed by living organisms and generate discussion of basic and controversial issues in the study of mind. The topic of optimality was chosen because it has provoked considerable discussion and controversy in many different academic fields. There are several aspects to the issue of optimality. First, is it true that actual behavior and cognitive functions of living animals, including humans, can be considered as optimal in some sense? Second, what is the utility function for biological organisms, if any, and can it be described mathematically? Rather than organize the chapters on a "biological versus artificial" basis or by what stance they took on optimality, it seemed more natural to organize them either by what level of questions they posed or by what intelligent functions they dealt with. The book begins with some general frameworks for discussing optimality, or the lack of it, in biological or artificial systems. The next set of chapters deals with some general mathematical and computational theories that help to clarify what the notion of optimality might entail in specific classes of networks. The final section deals with optimality in the context of many different high-level issues, including exploring one's environment, understanding mental illness, linguistic communication, and social organization. The diversity of topics covered in this book is designed to stimulate interdisciplinary thinking and speculation about deep problems in intelligent system organization.


Advancing Artificial Intelligence through Biological Process Applications

Advancing Artificial Intelligence through Biological Process Applications

Author: Porto Pazos, Ana B.

Publisher: IGI Global

Published: 2008-07-31

Total Pages: 460

ISBN-13: 159904997X

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As science continues to advance, researchers are continually gaining new insights into the way living beings behave and function, and into the composition of the smallest molecules. Most of these biological processes have been imitated by many scientific disciplines with the purpose of trying to solve different problems, one of which is artificial intelligence. Advancing Artificial Intelligence through Biological Process Applications presents recent advances in the study of certain biological processes related to information processing that are applied to artificial intelligence. Describing the benefits of recently discovered and existing techniques to adaptive artificial intelligence and biology, this book will be a highly valued addition to libraries in the neuroscience, molecular biology, and behavioral science spheres.


Time, Emergences and Communications

Time, Emergences and Communications

Author: Bernard Dugué

Publisher: John Wiley & Sons

Published: 2018-04-16

Total Pages: 166

ISBN-13: 1119522552

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This book presents an attempt to understand emergences in various situations where material components interact by coordinating their actions to "make system" with emerging properties (or functions) accessible to experimental investigation. I will endeavor to show that communications play a decisive role in these processes. A strategy will be implemented. If communications are so important, then we must show that they are an essential property of matter. This justifies the detailed analyses on the quantum world developed in the first five chapters. Also includes a study of the strange property of entanglement as well as an interpretation of the chemical bonds which cannot be circumvented in order to understand the functioning of complex systems; Living cells and animals. So the strategy consolidates as much as possible the physical foundations and the understanding of the primordial matter and then passing to the realities based on very large numbers of elementary components.


Plausible Neural Networks for Biological Modelling

Plausible Neural Networks for Biological Modelling

Author: H.A. Mastebroek

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 264

ISBN-13: 9401006741

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The expression 'Neural Networks' refers traditionally to a class of mathematical algorithms that obtain their proper performance while they 'learn' from examples or from experience. As a consequence, they are suitable for performing straightforward and relatively simple tasks like classification, pattern recognition and prediction, as well as more sophisticated tasks like the processing of temporal sequences and the context dependent processing of complex problems. Also, a wide variety of control tasks can be executed by them, and the suggestion is relatively obvious that neural networks perform adequately in such cases because they are thought to mimic the biological nervous system which is also devoted to such tasks. As we shall see, this suggestion is false but does not do any harm as long as it is only the final performance of the algorithm which counts. Neural networks are also used in the modelling of the functioning of (sub systems in) the biological nervous system. It will be clear that in such cases it is certainly not irrelevant how similar their algorithm is to what is precisely going on in the nervous system. Standard artificial neural networks are constructed from 'units' (roughly similar to neurons) that transmit their 'activity' (similar to membrane potentials or to mean firing rates) to other units via 'weight factors' (similar to synaptic coupling efficacies).