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

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

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.

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.

Download or read book Handbook of Computational Molecular Biology written by Srinivas Aluru and published by CRC Press. This book was released on 2005-12-21 with total page 1108 pages. Available in PDF, EPUB and Kindle. Book excerpt: The enormous complexity of biological systems at the molecular level must be answered with powerful computational methods. Computational biology is a young field, but has seen rapid growth and advancement over the past few decades. Surveying the progress made in this multidisciplinary field, the Handbook of Computational Molecular Biology of

Download or read book Logical Modeling of Cellular Processes From Software Development to Network Dynamics written by Matteo Barberis and published by Frontiers Media SA. This book was released on 2019-08-16 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematical models have become invaluable tools for understanding the intricate dynamic behavior of complex biochemical and biological systems. Among computational strategies, logical modeling has been recently gaining interest as an alternative approach to address network dynamics. Due to its advantages, including scalability and independence of kinetic parameters, the logical modeling framework is becoming increasingly popular to study the dynamics of highly interconnected systems, such as cell cycle progression, T cell differentiation and gene regulation. Novel tools and standards have been developed to increase the interoperability of logical models, which can now be employ to respond a variety of biological questions. This Research Topic brings together the most recent and cutting-edge approaches in the area of logical modeling including, among others, novel biological applications, software development and model analysis techniques.

Download or read book Research in Computational Molecular Biology written by Bonnie Berger and published by Springer Science & Business Media. This book was released on 2010-04-20 with total page 595 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the papers presented at RECOMB 2010: the 14th Annual International Conference on Research in Computational Molecular Biology held in Lisbon, Portugal, during April 25–28, 2010. The RECOMB conference series was started in 1997 by Sorin Istrail, Pavel Pevzner, and Michael Waterman. RECOMB 2010 was hosted by INESC-ID and Instituto Superior Tecnico, or- nized by a committee chaired by Arlindo Oliveira and took place at the Int- national Fair of Lisbon Meeting Centre. This year, 36 papers were accepted for presentation out of 176 submissions. The papers presented were selected by the Program Committee (PC) assisted by a number of external reviewers. Each paper was reviewed by three members of the PC, or by external reviewers, and there was an extensive Web-based discussion over a period of two weeks, leading to the ?nal decisions. RECOMB 2010 also introduced a Highlights Track, in which six additional presentations by senior authors were chosen from papers published in 2009. The RECOMB conferenceseriesiscloselyassociatedwiththeJournalofComputational Biology, which traditionally publishes special issues devoted to presenting full versions of selected conference papers.

Download or read book Books in Print written by and published by . This book was released on 1982 with total page 2376 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computational Modeling of Signaling Networks written by Lan K. Nguyen and published by Springer Nature. This book was released on 2023-04-19 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume focuses on the computational modeling of cell signaling networks and the application of these models and model-based analysis to systems and personalized medicine. Chapters guide readers through various modeling approaches for signaling networks, new methods and techniques that facilitate model development and analysis, and new applications of signaling network modeling towards systems and personalized treatment of cancer. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and methods, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols. Authoritative and cutting-edge, Computational Modeling of Signaling Networks aims to benefit a wide spectrum of readers including researchers from the biological as well as computational systems biology communities.

Download or read book Complex Systems and Computational Biology Approaches to Acute Inflammation written by Yoram Vodovotz and published by Springer Nature. This book was released on 2020-11-04 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition expands upon and updates the vital research covered in its predecessor, by presenting state-of-the-art multidisciplinary and systems-oriented approaches to complex diseases arising from and driven by the acute inflammatory response. The chapters in this volume provide an introduction to different types of computational modeling, and how these methods can be applied to specific inflammatory diseases, with a focus on providing readers a roadmap for integrating advanced mathematical and computational techniques with traditional experimental methods. In this second edition, we cover both well-established and emerging modeling methods, especially state-of-the-art machine learning approaches and the integration of data-driven and mechanistic modeling. This volume introduces the concept of Model-based Precision Medicine as an alternative approach to the current view of Precision Medicine, based on leveraging mechanistic computational modeling to decrease cost while increasing the information value of the data being obtained. By presenting the role of computational modeling as an integrated component of the research process, Complex Systems and Computational Biology Approaches to Acute Inflammation: A Framework for Model-based Precision Medicine offers a window into the recent past, the present, and the future of computationally-augmented biomedical research.

Download or read book Catalyzing Inquiry at the Interface of Computing and Biology written by National Research Council and published by National Academies Press. This book was released on 2006-01-01 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in computer science and technology and in biology over the last several years have opened up the possibility for computing to help answer fundamental questions in biology and for biology to help with new approaches to computing. Making the most of the research opportunities at the interface of computing and biology requires the active participation of people from both fields. While past attempts have been made in this direction, circumstances today appear to be much more favorable for progress. To help take advantage of these opportunities, this study was requested of the NRC by the National Science Foundation, the Department of Defense, the National Institutes of Health, and the Department of Energy. The report provides the basis for establishing cross-disciplinary collaboration between biology and computing including an analysis of potential impediments and strategies for overcoming them. The report also presents a wealth of examples that should encourage students in the biological sciences to look for ways to enable them to be more effective users of computing in their studies.

Download or read book Biometrics written by and published by . This book was released on 1995 with total page 824 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Encyclopedia of Bioinformatics and Computational Biology written by and published by Elsevier. This book was released on 2018-08-21 with total page 3421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics, Three Volume Set combines elements of computer science, information technology, mathematics, statistics and biotechnology, providing the methodology and in silico solutions to mine biological data and processes. The book covers Theory, Topics and Applications, with a special focus on Integrative –omics and Systems Biology. The theoretical, methodological underpinnings of BCB, including phylogeny are covered, as are more current areas of focus, such as translational bioinformatics, cheminformatics, and environmental informatics. Finally, Applications provide guidance for commonly asked questions. This major reference work spans basic and cutting-edge methodologies authored by leaders in the field, providing an invaluable resource for students, scientists, professionals in research institutes, and a broad swath of researchers in biotechnology and the biomedical and pharmaceutical industries. Brings together information from computer science, information technology, mathematics, statistics and biotechnology Written and reviewed by leading experts in the field, providing a unique and authoritative resource Focuses on the main theoretical and methodological concepts before expanding on specific topics and applications Includes interactive images, multimedia tools and crosslinking to further resources and databases

Download or read book Math and Bio 2010 written by Lynn Arthur Steen and published by MAA. This book was released on 2005 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Math and bio 2010 grew out of 'Meeting the Challenges: Education across the Biological, Mathematical and Computer Sciences,' a joint project of the Mathematical Association of America (MAA), the National Science Foundation Division of Undergraduate Education (NSF DUE), the National Institute of General Medical Sciences (NIGMS), the American Association for the Advancement of Science (AAAS), and the American Society for Microbiology (ASM)."--Foreword, p. vi

Download or read book Cellular Automaton Modeling of Biological Pattern Formation written by Andreas Deutsch and published by Birkhäuser. This book was released on 2018-03-09 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text explores the use of cellular automata in modeling pattern formation in biological systems. It describes several mathematical modeling approaches utilizing cellular automata that can be used to study the dynamics of interacting cell systems both in simulation and in practice. New in this edition are chapters covering cell migration, tissue development, and cancer dynamics, as well as updated references and new research topic suggestions that reflect the rapid development of the field. The book begins with an introduction to pattern-forming principles in biology and the various mathematical modeling techniques that can be used to analyze them. Cellular automaton models are then discussed in detail for different types of cellular processes and interactions, including random movement, cell migration, adhesive cell interaction, alignment and cellular swarming, growth processes, pigment cell pattern formation, tissue development, tumor growth and invasion, and Turing-type patterns and excitable media. In the final chapter, the authors critically discuss possibilities and limitations of the cellular automaton approach in modeling various biological applications, along with future research directions. Suggestions for research projects are provided throughout the book to encourage additional engagement with the material, and an accompanying simulator is available for readers to perform their own simulations on several of the models covered in the text. QR codes are included within the text for easy access to the simulator. With its accessible presentation and interdisciplinary approach, Cellular Automaton Modeling of Biological Pattern Formation is suitable for graduate and advanced undergraduate students in mathematical biology, biological modeling, and biological computing. It will also be a valuable resource for researchers and practitioners in applied mathematics, mathematical biology, computational physics, bioengineering, and computer science. PRAISE FOR THE FIRST EDITION “An ideal guide for someone with a mathematical or physical background to start exploring biological modelling. Importantly, it will also serve as an excellent guide for experienced modellers to innovate and improve their methodologies for analysing simulation results.” —Mathematical Reviews

Download or read book Computational Methods in Cell Biology written by Anand R. Asthagiri and published by Academic Press. This book was released on 2012-04-13 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

Download or read book Dynamic Models in Biology written by Stephen P. Ellner and published by Princeton University Press. This book was released on 2011-09-19 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: From controlling disease outbreaks to predicting heart attacks, dynamic models are increasingly crucial for understanding biological processes. Many universities are starting undergraduate programs in computational biology to introduce students to this rapidly growing field. In Dynamic Models in Biology, the first text on dynamic models specifically written for undergraduate students in the biological sciences, ecologist Stephen Ellner and mathematician John Guckenheimer teach students how to understand, build, and use dynamic models in biology. Developed from a course taught by Ellner and Guckenheimer at Cornell University, the book is organized around biological applications, with mathematics and computing developed through case studies at the molecular, cellular, and population levels. The authors cover both simple analytic models--the sort usually found in mathematical biology texts--and the complex computational models now used by both biologists and mathematicians. Linked to a Web site with computer-lab materials and exercises, Dynamic Models in Biology is a major new introduction to dynamic models for students in the biological sciences, mathematics, and engineering.