Computational Methods For Biological Models

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Biological Modeling and Simulation

Author : Russell Schwartz
Publisher : MIT Press
ISBN 13 : 0262303396
Total Pages : 403 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Biological Modeling and Simulation by : Russell Schwartz

Download or read book Biological Modeling and Simulation written by Russell Schwartz and published by MIT Press. This book was released on 2008-07-25 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practice-oriented survey of techniques for computational modeling and simulation suitable for a broad range of biological problems. There are many excellent computational biology resources now available for learning about methods that have been developed to address specific biological systems, but comparatively little attention has been paid to training aspiring computational biologists to handle new and unanticipated problems. This text is intended to fill that gap by teaching students how to reason about developing formal mathematical models of biological systems that are amenable to computational analysis. It collects in one place a selection of broadly useful models, algorithms, and theoretical analysis tools normally found scattered among many other disciplines. It thereby gives the aspiring student a bag of tricks that will serve him or her well in modeling problems drawn from numerous subfields of biology. These techniques are taught from the perspective of what the practitioner needs to know to use them effectively, supplemented with references for further reading on more advanced use of each method covered. The text, which grew out of a class taught at Carnegie Mellon University, covers models for optimization, simulation and sampling, and parameter tuning. These topics provide a general framework for learning how to formulate mathematical models of biological systems, what techniques are available to work with these models, and how to fit the models to particular systems. Their application is illustrated by many examples drawn from a variety of biological disciplines and several extended case studies that show how the methods described have been applied to real problems in biology.

Quantitative Biology

Author : Brian Munsky
Publisher : MIT Press
ISBN 13 : 0262347113
Total Pages : 729 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Quantitative Biology by : Brian Munsky

Download or read book Quantitative Biology written by Brian Munsky and published by MIT Press. This book was released on 2018-08-21 with total page 729 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the quantitative modeling of biological processes, presenting modeling approaches, methodology, practical algorithms, software tools, and examples of current research. The quantitative modeling of biological processes promises to expand biological research from a science of observation and discovery to one of rigorous prediction and quantitative analysis. The rapidly growing field of quantitative biology seeks to use biology's emerging technological and computational capabilities to model biological processes. This textbook offers an introduction to the theory, methods, and tools of quantitative biology. The book first introduces the foundations of biological modeling, focusing on some of the most widely used formalisms. It then presents essential methodology for model-guided analyses of biological data, covering such methods as network reconstruction, uncertainty quantification, and experimental design; practical algorithms and software packages for modeling biological systems; and specific examples of current quantitative biology research and related specialized methods. Most chapters offer problems, progressing from simple to complex, that test the reader's mastery of such key techniques as deterministic and stochastic simulations and data analysis. Many chapters include snippets of code that can be used to recreate analyses and generate figures related to the text. Examples are presented in the three popular computing languages: Matlab, R, and Python. A variety of online resources supplement the the text. The editors are long-time organizers of the Annual q-bio Summer School, which was founded in 2007. Through the school, the editors have helped to train more than 400 visiting students in Los Alamos, NM, Santa Fe, NM, San Diego, CA, Albuquerque, NM, and Fort Collins, CO. This book is inspired by the school's curricula, and most of the contributors have participated in the school as students, lecturers, or both. Contributors John H. Abel, Roberto Bertolusso, Daniela Besozzi, Michael L. Blinov, Clive G. Bowsher, Fiona A. Chandra, Paolo Cazzaniga, Bryan C. Daniels, Bernie J. Daigle, Jr., Maciej Dobrzynski, Jonathan P. Doye, Brian Drawert, Sean Fancer, Gareth W. Fearnley, Dirk Fey, Zachary Fox, Ramon Grima, Andreas Hellander, Stefan Hellander, David Hofmann, Damian Hernandez, William S. Hlavacek, Jianjun Huang, Tomasz Jetka, Dongya Jia, Mohit Kumar Jolly, Boris N. Kholodenko, Markek Kimmel, Michał Komorowski, Ganhui Lan, Heeseob Lee, Herbert Levine, Leslie M Loew, Jason G. Lomnitz, Ard A. Louis, Grant Lythe, Carmen Molina-París, Ion I. Moraru, Andrew Mugler, Brian Munsky, Joe Natale, Ilya Nemenman, Karol Nienałtowski, Marco S. Nobile, Maria Nowicka, Sarah Olson, Alan S. Perelson, Linda R. Petzold, Sreenivasan Ponnambalam, Arya Pourzanjani, Ruy M. Ribeiro, William Raymond, William Raymond, Herbert M. Sauro, Michael A. Savageau, Abhyudai Singh, James C. Schaff, Boris M. Slepchenko, Thomas R. Sokolowski, Petr Šulc, Andrea Tangherloni, Pieter Rein ten Wolde, Philipp Thomas, Karen Tkach Tuzman, Lev S. Tsimring, Dan Vasilescu, Margaritis Voliotis, Lisa Weber

Computational Modeling of Biological Systems

Author : Nikolay V Dokholyan
Publisher : Springer Science & Business Media
ISBN 13 : 1461421454
Total Pages : 360 pages
Book Rating : 4.4/5 (614 download)

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Book Synopsis Computational Modeling of Biological Systems by : Nikolay V Dokholyan

Download or read book Computational Modeling of Biological Systems written by Nikolay V Dokholyan and published by Springer Science & Business Media. This book was released on 2012-02-12 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational modeling is emerging as a powerful new approach to study and manipulate biological systems. Multiple methods have been developed to model, visualize, and rationally alter systems at various length scales, starting from molecular modeling and design at atomic resolution to cellular pathways modeling and analysis. Higher time and length scale processes, such as molecular evolution, have also greatly benefited from new breeds of computational approaches. This book provides an overview of the established computational methods used for modeling biologically and medically relevant systems.

Methods in Computational Biology

Author : Ross Carlson
Publisher : MDPI
ISBN 13 : 3039211633
Total Pages : 214 pages
Book Rating : 4.0/5 (392 download)

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Book Synopsis Methods in Computational Biology by : Ross Carlson

Download or read book Methods in Computational Biology written by Ross Carlson and published by MDPI. This book was released on 2019-07-03 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern biology is rapidly becoming a study of large sets of data. Understanding these data sets is a major challenge for most life sciences, including the medical, environmental, and bioprocess fields. Computational biology approaches are essential for leveraging this ongoing revolution in omics data. A primary goal of this Special Issue, entitled “Methods in Computational Biology”, is the communication of computational biology methods, which can extract biological design principles from complex data sets, described in enough detail to permit the reproduction of the results. This issue integrates interdisciplinary researchers such as biologists, computer scientists, engineers, and mathematicians to advance biological systems analysis. The Special Issue contains the following sections: • Reviews of Computational Methods • Computational Analysis of Biological Dynamics: From Molecular to Cellular to Tissue/Consortia Levels • The Interface of Biotic and Abiotic Processes • Processing of Large Data Sets for Enhanced Analysis • Parameter Optimization and Measurement

Computational Methods for Estimating the Kinetic Parameters of Biological Systems

Author : Quentin Vanhaelen
Publisher : Humana
ISBN 13 : 9781071617694
Total Pages : 0 pages
Book Rating : 4.6/5 (176 download)

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Book Synopsis Computational Methods for Estimating the Kinetic Parameters of Biological Systems by : Quentin Vanhaelen

Download or read book Computational Methods for Estimating the Kinetic Parameters of Biological Systems written by Quentin Vanhaelen and published by Humana. This book was released on 2022-12-24 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This detailed book provides an overview of various classes of computational techniques, including machine learning techniques, commonly used for evaluating kinetic parameters of biological systems. Focusing on three distinct situations, the volume covers the prediction of the kinetics of enzymatic reactions, the prediction of the kinetics of protein-protein or protein-ligand interactions (binding rates, dissociation rates, binding affinities), and the prediction of relatively large set of kinetic rates of reactions usually found in quantitative models of large biological networks. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of expert implementation advice that leads to successful results. Authoritative and practical, Computational Methods for Estimating the Kinetic Parameters of Biological Systems will be of great interest for researchers working through the challenge of identifying the best type of algorithm and who would like to use or develop a computational method for the estimation of kinetic parameters.

A Course in Mathematical Biology

Author : Gerda de Vries
Publisher : SIAM
ISBN 13 : 0898718252
Total Pages : 307 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis A Course in Mathematical Biology by : Gerda de Vries

Download or read book A Course in Mathematical Biology written by Gerda de Vries and published by SIAM. This book was released on 2006-07-01 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the only book that teaches all aspects of modern mathematical modeling and that is specifically designed to introduce undergraduate students to problem solving in the context of biology. Included is an integrated package of theoretical modeling and analysis tools, computational modeling techniques, and parameter estimation and model validation methods, with a focus on integrating analytical and computational tools in the modeling of biological processes. Divided into three parts, it covers basic analytical modeling techniques; introduces computational tools used in the modeling of biological problems; and includes various problems from epidemiology, ecology, and physiology. All chapters include realistic biological examples, including many exercises related to biological questions. In addition, 25 open-ended research projects are provided, suitable for students. An accompanying Web site contains solutions and a tutorial for the implementation of the computational modeling techniques. Calculations can be done in modern computing languages such as Maple, Mathematica, and MATLAB?.

A Guide to Numerical Modelling in Systems Biology

Author : Peter Deuflhard
Publisher : Springer
ISBN 13 : 3319200593
Total Pages : 185 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis A Guide to Numerical Modelling in Systems Biology by : Peter Deuflhard

Download or read book A Guide to Numerical Modelling in Systems Biology written by Peter Deuflhard and published by Springer. This book was released on 2015-07-06 with total page 185 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for students of computational systems biology with only a limited background in mathematics. Typical books on systems biology merely mention algorithmic approaches, but without offering a deeper understanding. On the other hand, mathematical books are typically unreadable for computational biologists. The authors of the present book have worked hard to fill this gap. The result is not a book on systems biology, but on computational methods in systems biology. This book originated from courses taught by the authors at Freie Universität Berlin. The guiding idea of the courses was to convey those mathematical insights that are indispensable for systems biology, teaching the necessary mathematical prerequisites by means of many illustrative examples and without any theorems. The three chapters cover the mathematical modelling of biochemical and physiological processes, numerical simulation of the dynamics of biological networks and identification of model parameters by means of comparisons with real data. Throughout the text, the strengths and weaknesses of numerical algorithms with respect to various systems biological issues are discussed. Web addresses for downloading the corresponding software are also included.

Computational Methods in Cell Biology

Author :
Publisher : Academic Press
ISBN 13 : 0123884217
Total Pages : 427 pages
Book Rating : 4.1/5 (238 download)

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Book Synopsis Computational Methods in Cell Biology by :

Download or read book Computational Methods in Cell Biology written by and published by Academic Press. This book was released on 2012-05-31 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational methods are playing an ever increasing role in cell biology. This volume of Methods in Cell Biology focuses on Computational Methods in Cell Biology and consists of two parts: (1) data extraction and analysis to distill models and mechanisms, and (2) developing and simulating models to make predictions and testable hypotheses. - Focuses on computational methods in cell biology - Split into 2 parts--data extraction and analysis to distill models and mechanisms, and developing and simulating models to make predictions and testable hypotheses - Emphasizes the intimate and necessary connection with interpreting experimental data and proposing the next hypothesis and experiment

Computational Methods in Synthetic Biology

Author : Mario Andrea Marchisio
Publisher : Humana
ISBN 13 : 9781071608241
Total Pages : 255 pages
Book Rating : 4.6/5 (82 download)

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Book Synopsis Computational Methods in Synthetic Biology by : Mario Andrea Marchisio

Download or read book Computational Methods in Synthetic Biology written by Mario Andrea Marchisio and published by Humana. This book was released on 2021-11-27 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition book provides complete coverage of the computational approaches currently used in Synthetic Biology. New chapters detail computational methods and algorithms for the design of bio-components, insight on CAD programs, analysis techniques, and distributed systems. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, application details for both the expert and non-expert reader, and tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Computational Methods in Synthetic Biology, Second Edition aims to feature a broad overview of the research areas that can be met in the area of in silico Synthetic Biology.

Computational Methods for Biological Models

Author : Harendra Singh
Publisher : Springer Nature
ISBN 13 : 9819950015
Total Pages : 254 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Computational Methods for Biological Models by : Harendra Singh

Download or read book Computational Methods for Biological Models written by Harendra Singh and published by Springer Nature. This book was released on 2023-11-05 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses computational methods related to biological models using mathematical tools and techniques. The book chapters concentrate on numerical and analytical techniques that provide a global solution for biological models while keeping long-term benefits in mind. The solutions are useful in closely understanding biological models, and the results will be very useful for mathematicians, engineers, doctors, scientists and researchers working on real-life biological models. This book provides significant and current knowledge of biological models related to real-life applications. The book covers both methods and applications.

Learning and Inference in Computational Systems Biology

Author : Neil D. Lawrence
Publisher :
ISBN 13 :
Total Pages : 384 pages
Book Rating : 4.F/5 ( download)

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Book Synopsis Learning and Inference in Computational Systems Biology by : Neil D. Lawrence

Download or read book Learning and Inference in Computational Systems Biology written by Neil D. Lawrence and published by . This book was released on 2010 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Computational Structural Biology

Author : Torsten Schwede
Publisher : World Scientific
ISBN 13 : 9812778780
Total Pages : 790 pages
Book Rating : 4.8/5 (127 download)

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Book Synopsis Computational Structural Biology by : Torsten Schwede

Download or read book Computational Structural Biology written by Torsten Schwede and published by World Scientific. This book was released on 2008 with total page 790 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a comprehensive introduction to Landau-Lifshitz equations and Landau-Lifshitz-Maxwell equations, beginning with the work by Yulin Zhou and Boling Guo in the early 1980s and including most of the work done by this Chinese group led by Zhou and Guo since. The book focuses on aspects such as the existence of weak solutions in multi dimensions, existence and uniqueness of smooth solutions in one dimension, relations with harmonic map heat flows, partial regularity and long time behaviors. The book is a valuable reference book for those who are interested in partial differential equations, geometric analysis and mathematical physics. It may also be used as an advanced textbook by graduate students in these fields.

Systems Biology and Bioinformatics

Author : Kayvan Najarian
Publisher : CRC Press
ISBN 13 : 1439882940
Total Pages : 192 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Systems Biology and Bioinformatics by : Kayvan Najarian

Download or read book Systems Biology and Bioinformatics written by Kayvan Najarian and published by CRC Press. This book was released on 2009-04-13 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: The availability of molecular imaging and measurement systems enables today's biologists to swiftly monitor thousands of genes involved in a host of diseases, a critical factor in specialized drug development. Systems Biology and Bioinformatics: A Computational Approach provides students with a comprehensive collection of the computational methods

Computational Systems Biology

Author : Andres Kriete
Publisher : Academic Press
ISBN 13 : 0124059384
Total Pages : 549 pages
Book Rating : 4.1/5 (24 download)

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Book Synopsis Computational Systems Biology by : Andres Kriete

Download or read book Computational Systems Biology written by Andres Kriete and published by Academic Press. This book was released on 2013-11-26 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Computational Cell Biology

Author : Christopher P. Fall
Publisher : Springer Science & Business Media
ISBN 13 : 0387224599
Total Pages : 484 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Computational Cell Biology by : Christopher P. Fall

Download or read book Computational Cell Biology written by Christopher P. Fall and published by Springer Science & Business Media. This book was released on 2007-06-04 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides an introduction to dynamic modeling in molecular cell biology, taking a computational and intuitive approach. Detailed illustrations, examples, and exercises are included throughout the text. Appendices containing mathematical and computational techniques are provided as a reference tool.

Computational Systems Biology of Cancer

Author : Emmanuel Barillot
Publisher : CRC Press
ISBN 13 : 1439831440
Total Pages : 463 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Computational Systems Biology of Cancer by : Emmanuel Barillot

Download or read book Computational Systems Biology of Cancer written by Emmanuel Barillot and published by CRC Press. This book was released on 2012-08-25 with total page 463 pages. Available in PDF, EPUB and Kindle. Book excerpt: The future of cancer research and the development of new therapeutic strategies rely on our ability to convert biological and clinical questions into mathematical models—integrating our knowledge of tumour progression mechanisms with the tsunami of information brought by high-throughput technologies such as microarrays and next-generation sequencing. Offering promising insights on how to defeat cancer, the emerging field of systems biology captures the complexity of biological phenomena using mathematical and computational tools. Novel Approaches to Fighting Cancer Drawn from the authors’ decade-long work in the cancer computational systems biology laboratory at Institut Curie (Paris, France), Computational Systems Biology of Cancer explains how to apply computational systems biology approaches to cancer research. The authors provide proven techniques and tools for cancer bioinformatics and systems biology research. Effectively Use Algorithmic Methods and Bioinformatics Tools in Real Biological Applications Suitable for readers in both the computational and life sciences, this self-contained guide assumes very limited background in biology, mathematics, and computer science. It explores how computational systems biology can help fight cancer in three essential aspects: Categorising tumours Finding new targets Designing improved and tailored therapeutic strategies Each chapter introduces a problem, presents applicable concepts and state-of-the-art methods, describes existing tools, illustrates applications using real cases, lists publically available data and software, and includes references to further reading. Some chapters also contain exercises. Figures from the text and scripts/data for reproducing a breast cancer data analysis are available at www.cancer-systems-biology.net.

Biological Sequence Analysis

Author : Richard Durbin
Publisher : Cambridge University Press
ISBN 13 : 113945739X
Total Pages : 372 pages
Book Rating : 4.1/5 (394 download)

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Book Synopsis Biological Sequence Analysis by : Richard Durbin

Download or read book Biological Sequence Analysis written by Richard Durbin and published by Cambridge University Press. This book was released on 1998-04-23 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.