Computational Systems Biology

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Computational Systems Biology


Computational Systems Biology
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Computational Systems Biology


Computational Systems Biology
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Author : Andres Kriete
language : en
Publisher: Academic Press
Release Date : 2013-11-26

Computational Systems Biology written by Andres Kriete and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-26 with Computers categories.


This comprehensively revised second edition of Computational Systems Biology discusses the experimental and theoretical foundations of the function of biological systems at the molecular, cellular or organismal level over temporal and spatial scales, as systems biology advances to provide clinical solutions to complex medical problems. In particular the work focuses on the engineering of biological systems and network modeling. Logical information flow aids understanding of basic building blocks of life through disease phenotypes Evolved principles gives insight into underlying organizational principles of biological organizations, and systems processes, governing functions such as adaptation or response patterns Coverage of technical tools and systems helps researchers to understand and resolve specific systems biology problems using advanced computation Multi-scale modeling on disparate scales aids researchers understanding of dependencies and constraints of spatio-temporal relationships fundamental to biological organization and function.

Transactions On Computational Systems Biology X


Transactions On Computational Systems Biology X
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Author : Corrado Priami
language : en
Publisher: Springer
Release Date : 2010-06-27

Transactions On Computational Systems Biology X written by Corrado Priami and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-06-27 with Computers categories.


Technology is taking us to a world where myriads of heavily networked devices interact with the physical world in multiple ways, and at many levels, from the globalInternetdowntomicroandnanodevices. Manyofthesedevicesarehighly mobile and autonomous and must adapt to the surrounding environment in a totally unsupervised way. A fundamental research challenge is the design of robust decentralized c- puting systemsthat arecapableofoperating in changing environmentsandwith noisy input, and yet exhibit the desired behavior and response time, under c- straints such as energy consumption, size, and processing power. These systems should be able to adapt and learn how to react to unforeseen scenarios as well as to display properties comparable to social entities. The observation of nature has brought us many great and unforeseen concepts. Biological systems are able to handle many of these challenges with an elegance and e?ciency far beyond currenthumanartifacts. Basedonthisobservation,bio-inspiredapproacheshave been proposed as a means of handling the complexity of such systems. The goal is to obtain methods to engineer technical systems, which are of a stability and e?ciency comparable to those found in biological entities. This Special Issue on Biological and Biologically-inspired Communication contains the best papers from the Second International Conference on Bio- Inspired Models of Network, Information, and Computing Systems (BIONET- ICS 2007). The BIONETICS conference aims to bring together researchers and scientistsfromseveraldisciplines incomputerscienceandengineeringwhereb- inspired methods are investigated, as well as from bioinformatics, to deepen the information exchange and collaboration among the di?erent communities.

An Introduction To Computational Systems Biology


An Introduction To Computational Systems Biology
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Author : Karthik Raman
language : en
Publisher: CRC Press
Release Date : 2021-05-30

An Introduction To Computational Systems Biology written by Karthik Raman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-30 with Computers categories.


This book delivers a comprehensive and insightful account of applying mathematical modelling approaches to very large biological systems and networks—a fundamental aspect of computational systems biology. The book covers key modelling paradigms in detail, while at the same time retaining a simplicity that will appeal to those from less quantitative fields. Key Features: A hands-on approach to modelling Covers a broad spectrum of modelling, from static networks to dynamic models and constraint-based models Thoughtful exercises to test and enable understanding of concepts State-of-the-art chapters on exciting new developments, like community modelling and biological circuit design Emphasis on coding and software tools for systems biology Companion website featuring lecture videos, figure slides, codes, supplementary exercises, further reading, and appendices: https://ramanlab.github.io/SysBioBook/ An Introduction to Computational Systems Biology: Systems-Level Modelling of Cellular Networks is highly multi-disciplinary and will appeal to biologists, engineers, computer scientists, mathematicians and others.

Transactions On Computational Systems Biology Vi


Transactions On Computational Systems Biology Vi
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Author : Gordon Plotkin
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-11-27

Transactions On Computational Systems Biology Vi written by Gordon Plotkin and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-11-27 with Computers categories.


The 5th Transactions on Computational Systems Biology volume, edited by Gordon Plotkin, features carefully selected and enhanced contributions initially presented at the 2005 IEEE International Conference on Granular Computing. The 9 papers selected for this special issue discuss various aspects of computational methods, algorithm and techniques in bioinformatics such as gene expression analysis, biomedical literature mining and natural language processing, protein structure prediction, biological database management and biomedical information retrieval.

Learning And Inference In Computational Systems Biology


Learning And Inference In Computational Systems Biology
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Author : Neil D. Lawrence
language : en
Publisher: Mit Press
Release Date : 2010

Learning And Inference In Computational Systems Biology written by Neil D. Lawrence and has been published by Mit Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with Computers categories.


Tools and techniques for biological inference problems at scales ranging from genome-wide to pathway-specific. Computational systems biology unifies the mechanistic approach of systems biology with the data-driven approach of computational biology. Computational systems biology aims to develop algorithms that uncover the structure and parameterization of the underlying mechanistic model--in other words, to answer specific questions about the underlying mechanisms of a biological system--in a process that can be thought of as learning or inference. This volume offers state-of-the-art perspectives from computational biology, statistics, modeling, and machine learning on new methodologies for learning and inference in biological networks.The chapters offer practical approaches to biological inference problems ranging from genome-wide inference of genetic regulation to pathway-specific studies. Both deterministic models (based on ordinary differential equations) and stochastic models (which anticipate the increasing availability of data from small populations of cells) are considered. Several chapters emphasize Bayesian inference, so the editors have included an introduction to the philosophy of the Bayesian approach and an overview of current work on Bayesian inference. Taken together, the methods discussed by the experts in Learning and Inference in Computational Systems Biology provide a foundation upon which the next decade of research in systems biology can be built. Florence d'Alch e-Buc, John Angus, Matthew J. Beal, Nicholas Brunel, Ben Calderhead, Pei Gao, Mark Girolami, Andrew Golightly, Dirk Husmeier, Johannes Jaeger, Neil D. Lawrence, Juan Li, Kuang Lin, Pedro Mendes, Nicholas A. M. Monk, Eric Mjolsness, Manfred Opper, Claudia Rangel, Magnus Rattray, Andreas Ruttor, Guido Sanguinetti, Michalis Titsias, Vladislav Vyshemirsky, David L. Wild, Darren Wilkinson, Guy Yosiphon

Transactions On Computational Systems Biology Xiii


Transactions On Computational Systems Biology Xiii
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Author : Ralph-Johan Back
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-03-28

Transactions On Computational Systems Biology Xiii written by Ralph-Johan Back and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-28 with Computers categories.


This book covers Computational Models for Cell Processes, featuring enhanced contributions from the CompMod workshop (2009). Covers a wide range of topics in systems biology, addressing the dynamics and the computational principles of this emerging field.

Computational Systems Biology


Computational Systems Biology
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Author : Paola Lecca
language : en
Publisher: Woodhead Publishing
Release Date : 2016-07-29

Computational Systems Biology written by Paola Lecca and has been published by Woodhead Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-29 with Science categories.


Computational Systems Biology: Inference and Modelling provides an introduction to, and overview of, network analysis inference approaches which form the backbone of the model of the complex behavior of biological systems. This book addresses the challenge to integrate highly diverse quantitative approaches into a unified framework by highlighting the relationships existing among network analysis, inference, and modeling. The chapters are light in jargon and technical detail so as to make them accessible to the non-specialist reader. The book is addressed at the heterogeneous public of modelers, biologists, and computer scientists. Provides a unified presentation of network inference, analysis, and modeling Explores the connection between math and systems biology, providing a framework to learn to analyze, infer, simulate, and modulate the behavior of complex biological systems Includes chapters in modular format for learning the basics quickly and in the context of questions posed by systems biology Offers a direct style and flexible formalism all through the exposition of mathematical concepts and biological applications