Quantitative Biology: Theory, Computational Methods, and Models (The MIT Press)

Munsky, Brian [Editor]; Hlavacek, William S. [Editor]; Tsimring, Lev S. [Editor]; Tuzman, Karen Tkach [Contributor]; Fey, Dirk [Contributor]; Dobrzynski, Maciej [Contributor]; Kholodenko, Boris N [Contributor]; Olson, Sarah [Contributor]; Huang, Jianjun [Contributor]; Fox, Zachary [Contributor]; Munsky, Brian [Contributor]; Singh, Abhyudai [Contributor]; Grima, Ramon [Contributor]; Bertolusso, Roberto [Contributor]; Kimmel, Marek [Contributor]; Voliotis, Margaritis [Contributor]; Thomas, Philipp [Contributor]; Bowsher, Clive G [Contributor]; Sokolowski, Thomas R [Contributor]; Wolde, Pieter Rein ten [Contributor]; ??ulc, Petr [Contributor]; Doye, Jonathan P [Contributor]; Louis, Ard A [Contributor]; Natale, Joe [Contributor]; Hofmann, David

ISBN 10: 0262038080 / ISBN 13: 9780262038089

Verlag: The MIT Press, 2018

Beschreibung

Bestandsnummer des Verkäufers HC-MIT-N-0262038080

Bibliografische Details

Titel: Quantitative Biology: Theory, Computational ...

Verlag: The MIT Press

Erscheinungsdatum: 2018

Einband: hardcover

Zustand: New

Über diesen Titel

Inhaltsangabe:

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

Über die Autorin bzw. den Autor:

Brian Munsky is Assistant Professor in the Department of Chemical and Biological Engineering and the School of Biomedical Engineering at Colorado State University.

William S. Hlavacek is a Scientist in the Theoretical Biology and Biophysics Group at Los Alamos National Laboratory.

Lev S. Tsimring is a Research Scientist and Associate Director of the BioCircuits Institute at the University of California, San Diego.

Brian Munsky is Assistant Professor in the Department of Chemical and Biological Engineering and the School of Biomedical Engineering at Colorado State University.

Terrence J. Sejnowski holds the Francis Crick Chair at the Salk Institute for Biological Studies and is a Distinguished Professor at the University of California, San Diego. He was a member of the advisory committee for the Obama administration's BRAIN initiative and is President of the Neural Information Processing (NIPS) Foundation. He is the author of The Deep Learning Revolution (MIT Press) and other books.

Brian Munsky is Assistant Professor in the Department of Chemical and Biological Engineering and the School of Biomedical Engineering at Colorado State University.