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Computational Biophysics
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Book Synopsis Computational Biochemistry and Biophysics by : Oren M. Becker
Download or read book Computational Biochemistry and Biophysics written by Oren M. Becker and published by CRC Press. This book was released on 2001-02-09 with total page 534 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering theoretical methods and computational techniques in biomolecular research, this book focuses on approaches for the treatment of macromolecules, including proteins, nucleic acids, and bilayer membranes. It uses concepts in free energy calculations, conformational analysis, reaction rates, and transition pathways to calculate and interpret b
Book Synopsis Biophysics of Computation by : Christof Koch
Download or read book Biophysics of Computation written by Christof Koch and published by Oxford University Press. This book was released on 2004-10-28 with total page 587 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural network research often builds on the fiction that neurons are simple linear threshold units, completely neglecting the highly dynamic and complex nature of synapses, dendrites, and voltage-dependent ionic currents. Biophysics of Computation: Information Processing in Single Neurons challenges this notion, using richly detailed experimental and theoretical findings from cellular biophysics to explain the repertoire of computational functions available to single neurons. The author shows how individual nerve cells can multiply, integrate, or delay synaptic inputs and how information can be encoded in the voltage across the membrane, in the intracellular calcium concentration, or in the timing of individual spikes.Key topics covered include the linear cable equation; cable theory as applied to passive dendritic trees and dendritic spines; chemical and electrical synapses and how to treat them from a computational point of view; nonlinear interactions of synaptic input in passive and active dendritic trees; the Hodgkin-Huxley model of action potential generation and propagation; phase space analysis; linking stochastic ionic channels to membrane-dependent currents; calcium and potassium currents and their role in information processing; the role of diffusion, buffering and binding of calcium, and other messenger systems in information processing and storage; short- and long-term models of synaptic plasticity; simplified models of single cells; stochastic aspects of neuronal firing; the nature of the neuronal code; and unconventional models of sub-cellular computation.Biophysics of Computation: Information Processing in Single Neurons serves as an ideal text for advanced undergraduate and graduate courses in cellular biophysics, computational neuroscience, and neural networks, and will appeal to students and professionals in neuroscience, electrical and computer engineering, and physics.
Book Synopsis From Computational Biophysics to Systems Biology (CBSB11) – Celebrating Harold Scheraga’s 90th Birthday by : Paolo Carloni
Download or read book From Computational Biophysics to Systems Biology (CBSB11) – Celebrating Harold Scheraga’s 90th Birthday written by Paolo Carloni and published by Forschungszentrum Jülich. This book was released on 2012 with total page 267 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Primer for Computational Biology by : Shawn T. O'Neil
Download or read book A Primer for Computational Biology written by Shawn T. O'Neil and published by . This book was released on 2017-12-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Primer for Computational Biology aims to provide life scientists and students the skills necessary for research in a data-rich world. The text covers accessing and using remote servers via the command-line, writing programs and pipelines for data analysis, and provides useful vocabulary for interdisciplinary work. The book is broken into three parts: Introduction to Unix/Linux: The command-line is the "natural environment" of scientific computing, and this part covers a wide range of topics, including logging in, working with files and directories, installing programs and writing scripts, and the powerful "pipe" operator for file and data manipulation. Programming in Python: Python is both a premier language for learning and a common choice in scientific software development. This part covers the basic concepts in programming (data types, if-statements and loops, functions) via examples of DNA-sequence analysis. This part also covers more complex subjects in software development such as objects and classes, modules, and APIs. Programming in R: The R language specializes in statistical data analysis, and is also quite useful for visualizing large datasets. This third part covers the basics of R as a programming language (data types, if-statements, functions, loops and when to use them) as well as techniques for large-scale, multi-test analyses. Other topics include S3 classes and data visualization with ggplot2.
Book Synopsis Computational Biophysics of Membrane Proteins by : Carmen Domene
Download or read book Computational Biophysics of Membrane Proteins written by Carmen Domene and published by Royal Society of Chemistry. This book was released on 2016-12-05 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring current themes in modern computational and membrane protein biophysics, this book is ideal for researchers in computational chemistry and computational biophysics.
Book Synopsis Computational Biophysics of the Skin by : Bernard Querleux
Download or read book Computational Biophysics of the Skin written by Bernard Querleux and published by CRC Press. This book was released on 2016-04-19 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: The accessibility of the skin in vivo has resulted in the development of non-invasive methods in the past 40 years that offer accurate measurements of skin properties and structures from microscopic to macroscopic levels. However, the mechanisms involved in these properties are still only partly understood. Similar to many other domains, including
Book Synopsis Stochastic Dynamics in Computational Biology by : Stefanie Winkelmann
Download or read book Stochastic Dynamics in Computational Biology written by Stefanie Winkelmann and published by Springer Nature. This book was released on 2021-01-04 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to provide a well-structured and coherent overview of existing mathematical modeling approaches for biochemical reaction systems, investigating relations between both the conventional models and several types of deterministic-stochastic hybrid model recombinations. Another main objective is to illustrate and compare diverse numerical simulation schemes and their computational effort. Unlike related works, this book presents a broad scope in its applications, from offering a detailed introduction to hybrid approaches for the case of multiple population scales to discussing the setting of time-scale separation resulting from widely varying firing rates of reaction channels. Additionally, it also addresses modeling approaches for non well-mixed reaction-diffusion dynamics, including deterministic and stochastic PDEs and spatiotemporal master equations. Finally, by translating and incorporating complex theory to a level accessible to non-mathematicians, this book effectively bridges the gap between mathematical research in computational biology and its practical use in biological, biochemical, and biomedical systems.
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.
Book Synopsis Cellular Biophysics and Modeling by : Greg Conradi Smith
Download or read book Cellular Biophysics and Modeling written by Greg Conradi Smith and published by Cambridge University Press. This book was released on 2019-03-14 with total page 395 pages. Available in PDF, EPUB and Kindle. Book excerpt: What every neuroscientist should know about the mathematical modeling of excitable cells, presented at an introductory level.
Book Synopsis Computational Biochemistry and Biophysics by : Oren M. Becker
Download or read book Computational Biochemistry and Biophysics written by Oren M. Becker and published by CRC Press. This book was released on 2001-02-09 with total page 525 pages. Available in PDF, EPUB and Kindle. Book excerpt: Covering theoretical methods and computational techniques in biomolecular research, this book focuses on approaches for the treatment of macromolecules, including proteins, nucleic acids, and bilayer membranes. It uses concepts in free energy calculations, conformational analysis, reaction rates, and transition pathways to calculate and interpret biomolecular properties gleaned from computer-generated membrane simulations. It also demonstrates comparative protein structure modeling, outlines computer-aided drug design, discusses Bayesian statistics in molecular and structural biology, and examines the RISM-SCF/MCSCF approach to chemical processes in solution.
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
Book Synopsis Statistical Modeling and Machine Learning for Molecular Biology by : Alan Moses
Download or read book Statistical Modeling and Machine Learning for Molecular Biology written by Alan Moses and published by CRC Press. This book was released on 2017-01-06 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: • Assumes no background in statistics or computers • Covers most major types of molecular biological data • Covers the statistical and machine learning concepts of most practical utility (P-values, clustering, regression, regularization and classification) • Intended for graduate students beginning careers in molecular biology, systems biology, bioengineering and genetics
Book Synopsis Computational Biophysics of Membrane Proteins by : Carmen Domene
Download or read book Computational Biophysics of Membrane Proteins written by Carmen Domene and published by Royal Society of Chemistry. This book was released on 2016-11-30 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Exploring current themes in modern computational and membrane protein biophysics, this book presents a comprehensive account of the fundamental principles underlying different methods and techniques used to describe the intriguing mechanisms by which membrane proteins function. The book discusses the experimental approaches employed to study these proteins, with chapters reviewing recent crucial structural advances that have allowed computational biophysicists to discern how these molecular machines work. The book then explores what computational methods are available to researchers and what these have taught us about three key families of membrane proteins: ion channels, transporters and receptors. The book is ideal for researchers in computational chemistry and computational biophysics.
Book Synopsis Biophysical and Computational Tools in Drug Discovery by : Anil Kumar Saxena
Download or read book Biophysical and Computational Tools in Drug Discovery written by Anil Kumar Saxena and published by Springer Nature. This book was released on 2021-10-18 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reviews recent physicochemical and biophysical techniques applied in drug discovery research, and it outlines the latest advances in computational drug design. Divided into 10 chapters, the book discusses about the role of structural biology in drug discovery, and offers useful application cases of several biophysical and computational methods, including time-resolved fluorometry (TRF) with Förster resonance energy transfer (FRET), X-Ray crystallography, nuclear magnetic resonance spectroscopy, mass spectroscopy, generative machine learning for inverse molecular design, quantum mechanics/molecular mechanics (QM/MM,ONIOM) and quantum molecular dynamics (QMT) methods. Particular attention is given to computational search techniques applied to peptide vaccines using novel mathematical descriptors and structure and ligand-based virtual screening techniques in drug discovery research. Given its scope, the book is a valuable resource for students, researchers and professionals from pharmaceutical industry interested in drug design and discovery.
Book Synopsis Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology by : Hamid R Arabnia
Download or read book Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology written by Hamid R Arabnia and published by Morgan Kaufmann. This book was released on 2016-03-25 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emerging Trends in Applications and Infrastructures for Computational Biology, Bioinformatics, and Systems Biology: Systems and Applications covers the latest trends in the field with special emphasis on their applications. The first part covers the major areas of computational biology, development and application of data-analytical and theoretical methods, mathematical modeling, and computational simulation techniques for the study of biological and behavioral systems. The second part covers bioinformatics, an interdisciplinary field concerned with methods for storing, retrieving, organizing, and analyzing biological data. The book also explores the software tools used to generate useful biological knowledge. The third part, on systems biology, explores how to obtain, integrate, and analyze complex datasets from multiple experimental sources using interdisciplinary tools and techniques, with the final section focusing on big data and the collection of datasets so large and complex that it becomes difficult to process using conventional database management systems or traditional data processing applications. Explores all the latest advances in this fast-developing field from an applied perspective Provides the only coherent and comprehensive treatment of the subject available Covers the algorithm development, software design, and database applications that have been developed to foster research
Book Synopsis Algorithms for Computational Biology by : Carlos Martín-Vide
Download or read book Algorithms for Computational Biology written by Carlos Martín-Vide and published by Springer Nature. This book was released on 2020-03-23 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 7th International Conference on Algorithms for Computational Biology, AlCoB 2020, was planned to be held in Missoula, MT, USA in April 2020. Due to the corona pandemic the conference was postponed to be held together with AlCoB 2021. The 15 full papers included in this volume were carefully reviewed and selected from 24 submissions. They were organized in topical sections on genomics, phylogenetics, and RNA-Seq and other biological processes.
Book Synopsis Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology by : Hamid R Arabnia
Download or read book Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology written by Hamid R Arabnia and published by Morgan Kaufmann. This book was released on 2015-08-11 with total page 670 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology discusses the latest developments in all aspects of computational biology, bioinformatics, and systems biology and the application of data-analytics and algorithms, mathematical modeling, and simu- lation techniques. • Discusses the development and application of data-analytical and theoretical methods, mathematical modeling, and computational simulation techniques to the study of biological and behavioral systems, including applications in cancer research, computational intelligence and drug design, high-performance computing, and biology, as well as cloud and grid computing for the storage and access of big data sets. • Presents a systematic approach for storing, retrieving, organizing, and analyzing biological data using software tools with applications to general principles of DNA/RNA structure, bioinformatics and applications, genomes, protein structure, and modeling and classification, as well as microarray analysis. • Provides a systems biology perspective, including general guidelines and techniques for obtaining, integrating, and analyzing complex data sets from multiple experimental sources using computational tools and software. Topics covered include phenomics, genomics, epigenomics/epigenetics, metabolomics, cell cycle and checkpoint control, and systems biology and vaccination research. • Explains how to effectively harness the power of Big Data tools when data sets are so large and complex that it is difficult to process them using conventional database management systems or traditional data processing applications. Discusses the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological and behavioral systems. Presents a systematic approach for storing, retrieving, organizing and analyzing biological data using software tools with applications. Provides a systems biology perspective including general guidelines and techniques for obtaining, integrating and analyzing complex data sets from multiple experimental sources using computational tools and software.
