Combined Discrete and Continual Approaches in Biological Modelling

Combined Discrete and Continual Approaches in Biological Modelling
Author: Alexander E. Filippov
Publisher: Springer Nature
Total Pages: 327
Release: 2020-06-30
Genre: Science
ISBN: 3030415287
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Basic laws of nature are rather simple, but observed biological structures and their dynamic behaviors are unbelievably complicated. This book is devoted to a study of this “strange” relationship by applying mathematical modeling to various structures and phenomena in biology, such as surface patterns, bioadhesion, locomotion, predator-prey behavior, seed dispersal, etc. and revealing a kind of self-organization in these phenomena. In spite of diversity of biological systems considered, two main questions are (1) what does self-organization in biology mean mathematically and (2) how one can apply this knowledge to generate new knowledge about behavior of particular biological system? We believe that this kind of “biomimetics” in computer will lead to better understanding of biological phenomena and possibly towards development of technical implications based on our modeling.

Algebraic and Discrete Mathematical Methods for Modern Biology

Algebraic and Discrete Mathematical Methods for Modern Biology
Author: Raina Robeva
Publisher: Academic Press
Total Pages: 383
Release: 2015-05-09
Genre: Mathematics
ISBN: 0128012714
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Written by experts in both mathematics and biology, Algebraic and Discrete Mathematical Methods for Modern Biology offers a bridge between math and biology, providing a framework for simulating, analyzing, predicting, and modulating the behavior of complex biological systems. Each chapter begins with a question from modern biology, followed by the description of certain mathematical methods and theory appropriate in the search of answers. Every topic provides a fast-track pathway through the problem by presenting the biological foundation, covering the relevant mathematical theory, and highlighting connections between them. Many of the projects and exercises embedded in each chapter utilize specialized software, providing students with much-needed familiarity and experience with computing applications, critical components of the "modern biology" skill set. This book is appropriate for mathematics courses such as finite mathematics, discrete structures, linear algebra, abstract/modern algebra, graph theory, probability, bioinformatics, statistics, biostatistics, and modeling, as well as for biology courses such as genetics, cell and molecular biology, biochemistry, ecology, and evolution. - Examines significant questions in modern biology and their mathematical treatments - Presents important mathematical concepts and tools in the context of essential biology - Features material of interest to students in both mathematics and biology - Presents chapters in modular format so coverage need not follow the Table of Contents - Introduces projects appropriate for undergraduate research - Utilizes freely accessible software for visualization, simulation, and analysis in modern biology - Requires no calculus as a prerequisite - Provides a complete Solutions Manual - Features a companion website with supplementary resources

Formal Methods for Computational Systems Biology

Formal Methods for Computational Systems Biology
Author: Marco Bernardo
Publisher: Springer Science & Business Media
Total Pages: 533
Release: 2008-05-20
Genre: Computers
ISBN: 3540688927
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This book presents a set of 14 papers accompanying the lectures of leading researchers given at the 8th edition of the International School on Formal Methods for the Design of Computer, Communication and Software Systems, SFM 2008, held in Bertinoro, Italy in June 2008. SFM 2008 was devoted to formal techniques for computational systems biology and covered several aspects of the field, including computational models, calculi and logics for biological systems, and verification and simulation methods. The first part of this volume comprises nine papers based on regular lectures, the second part of this volume comprises five papers based on talks given by people involved in the Italian BISCA research project on Bio-Inspired Systems and Calculi with Applications.

Biological Modeling and Simulation

Biological Modeling and Simulation
Author: Russell Schwartz
Publisher: MIT Press
Total Pages: 403
Release: 2008-07-25
Genre: Science
ISBN: 0262195844
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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.

Simulation

Simulation
Author: Stewart Robinson
Publisher: Bloomsbury Publishing
Total Pages: 392
Release: 2014-09-22
Genre: Business & Economics
ISBN: 1137328037
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The new edition of this successful textbook provides a comprehensive introduction to simulation, foregrounding the topic as an applied problem-solving tool. Guiding readers through the key stages in a simulation project in terms of both the technical requirements and the project management issues surrounding it, the book will enable students to develop appropriate valid conceptual models, perform simulation experiments, analyse the results and draw insightful conclusions. The author's engaging style and authoritative knowledge of the subject make the book as accessible as it is essential, drawing on case studies and complementary online content to encourage a critical engagement with the topic. This is an ideal textbook for those studying on upper level undergraduate and postgraduate degree courses in business and management and MBA programmes, and is a core text for those specialising in operations management. In addition, it is an important text for students taking Simulation modules on engineering, computer science or mathematics degree programmes. New to this Edition: - A practical step-by-step guide to preparing a simple model - Improved cross referencing, navigation and design - Updated referencing and the inclusion of select new case studies - New material available via the companion website - Key concepts, on-page glossary terms and relevant further reading lists for each chapter

Quantitative Biology

Quantitative Biology
Author: Brian Munsky
Publisher: MIT Press
Total Pages: 729
Release: 2018-08-21
Genre: Science
ISBN: 0262347113
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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

Transactions on Computational Systems Biology I

Transactions on Computational Systems Biology I
Author: Corrado Priami
Publisher: Springer Science & Business Media
Total Pages: 118
Release: 2005-03-30
Genre: Computers
ISBN: 3540254226
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The LNCS journal Transactions on Computational Systems Biology is devoted to inter- and multidisciplinary research in the fields of computer science and life sciences and supports a paradigmatic shift in the techniques from computer and information science to cope with the new challenges arising from the systems oriented point of view of biological phenomena. This first volume of the Transactions on Computational Systems Biology is made up of papers by members of the journal's Editorial Board to provide a representative and smart start-up to the new journal.

Integrative Bioinformatics

Integrative Bioinformatics
Author: Ming Chen
Publisher: Springer Nature
Total Pages: 381
Release: 2022-04-15
Genre: Medical
ISBN: 9811667950
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This book provides an overview of the history of integrative bioinformatics and the actual situation and the relevant tools. Subjects cover the essential topics, basic introductions, and latest developments; biological data integration and manipulation; modeling and simulation of networks; as well as a number of applications of integrative bioinformatics. It aims to provide basic introduction of biological information systems and guidance for the computational analysis of systems biology. This book covers a range of issues and methods that unveil a multitude of omics data integration and relevance that integrative bioinformatics has today. It contains a unique compilation of invited and selected articles from the Journal of Integrative Bioinformatics (JIB) and annual meetings of the International Symposium on Integrative Bioinformatics.

Stochastic Modelling for Systems Biology, Third Edition

Stochastic Modelling for Systems Biology, Third Edition
Author: Darren J. Wilkinson
Publisher: CRC Press
Total Pages: 405
Release: 2018-12-07
Genre: Mathematics
ISBN: 135100090X
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Since the first edition of Stochastic Modelling for Systems Biology, there have been many interesting developments in the use of "likelihood-free" methods of Bayesian inference for complex stochastic models. Having been thoroughly updated to reflect this, this third edition covers everything necessary for a good appreciation of stochastic kinetic modelling of biological networks in the systems biology context. New methods and applications are included in the book, and the use of R for practical illustration of the algorithms has been greatly extended. There is a brand new chapter on spatially extended systems, and the statistical inference chapter has also been extended with new methods, including approximate Bayesian computation (ABC). Stochastic Modelling for Systems Biology, Third Edition is now supplemented by an additional software library, written in Scala, described in a new appendix to the book. New in the Third Edition New chapter on spatially extended systems, covering the spatial Gillespie algorithm for reaction diffusion master equation models in 1- and 2-d, along with fast approximations based on the spatial chemical Langevin equation Significantly expanded chapter on inference for stochastic kinetic models from data, covering ABC, including ABC-SMC Updated R package, including code relating to all of the new material New R package for parsing SBML models into simulatable stochastic Petri net models New open-source software library, written in Scala, replicating most of the functionality of the R packages in a fast, compiled, strongly typed, functional language Keeping with the spirit of earlier editions, all of the new theory is presented in a very informal and intuitive manner, keeping the text as accessible as possible to the widest possible readership. An effective introduction to the area of stochastic modelling in computational systems biology, this new edition adds additional detail and computational methods that will provide a stronger foundation for the development of more advanced courses in stochastic biological modelling.

Food Process Modelling

Food Process Modelling
Author: L M M Tijskens
Publisher: Woodhead Publishing
Total Pages: 516
Release: 2001-06-14
Genre: Business & Economics
ISBN: 9781855735651
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Food process modelling provides an authoritative review of one of the most exciting and influential developments in the food industry. The modelling of food processes allows analysts not only to understand such processes more clearly but also to control them more closely and make predictions about them. Modelling thus aids the search for greater and more consistent food quality. Written by a distinguished international team of experts, Food process modelling covers both the range of modelling techniques and their practical applications across the food chain.