From Computational Logic to Computational Biology
Author : Domenico Cantone
Publisher : Springer Nature
Page : 280 pages
File Size : 31,52 MB
Release :
Category :
ISBN : 3031552482
Integer Linear Programming in Computational and Systems Biology
Author : Dan Gusfield
Publisher : Cambridge University Press
Page : 431 pages
File Size : 13,63 MB
Release : 2019-06-13
Category : Computers
ISBN : 1108421768
Book Description
This hands-on tutorial text for non-experts demonstrates biological applications of a versatile modeling and optimization technique.
Applications Of Fuzzy Logic In Bioinformatics
Author : Dong Xu
Publisher : World Scientific
Page : 246 pages
File Size : 36,8 MB
Release : 2008-08-11
Category : Science
ISBN : 1908978716
Book Description
Many biological systems and objects are intrinsically fuzzy as their properties and behaviors contain randomness or uncertainty. In addition, it has been shown that exact or optimal methods have significant limitation in many bioinformatics problems. Fuzzy set theory and fuzzy logic are ideal to describe some biological systems/objects and provide good tools for some bioinformatics problems. This book comprehensively addresses several important bioinformatics topics using fuzzy concepts and approaches, including measurement of ontological similarity, protein structure prediction/analysis, and microarray data analysis. It also reviews other bioinformatics applications using fuzzy techniques./a
An Introduction to Computational Systems Biology
Author : Karthik Raman
Publisher : CRC Press
Page : 359 pages
File Size : 33,59 MB
Release : 2021-05-30
Category : Computers
ISBN : 0429944527
Book Description
This book delivers a comprehensive and insightful account of applying mathematical modelling approaches to very large biological systems and networks—a fundamental aspect of computational systems biology. The book covers key modelling paradigms in detail, while at the same time retaining a simplicity that will appeal to those from less quantitative fields. Key Features: A hands-on approach to modelling Covers a broad spectrum of modelling, from static networks to dynamic models and constraint-based models Thoughtful exercises to test and enable understanding of concepts State-of-the-art chapters on exciting new developments, like community modelling and biological circuit design Emphasis on coding and software tools for systems biology Companion website featuring lecture videos, figure slides, codes, supplementary exercises, further reading, and appendices: https://ramanlab.github.io/SysBioBook/ An Introduction to Computational Systems Biology: Systems-Level Modelling of Cellular Networks is highly multi-disciplinary and will appeal to biologists, engineers, computer scientists, mathematicians and others.
Computational Biology
Author : Röbbe Wünschiers
Publisher : Springer Science & Business Media
Page : 291 pages
File Size : 19,72 MB
Release : 2012-12-06
Category : Science
ISBN : 3642185525
Book Description
-Teaches the reader how to use Unix, which is the key to basic computing and allows the most flexibility for bioinformatics applications -Written specifically with the needs of molecular biologists in mind -Easy to follow, written for beginners with no computational knowledge -Includes examples from biological data analysis -Can be use either for self-teaching or in courses
Python Programming for Biology
Author : Tim J. Stevens
Publisher : Cambridge University Press
Page : 721 pages
File Size : 36,57 MB
Release : 2015-02-12
Category : Science
ISBN : 1316194140
Book Description
Do you have a biological question that could be readily answered by computational techniques, but little experience in programming? Do you want to learn more about the core techniques used in computational biology and bioinformatics? Written in an accessible style, this guide provides a foundation for both newcomers to computer programming and those interested in learning more about computational biology. The chapters guide the reader through: a complete beginners' course to programming in Python, with an introduction to computing jargon; descriptions of core bioinformatics methods with working Python examples; scientific computing techniques, including image analysis, statistics and machine learning. This book also functions as a language reference written in straightforward English, covering the most common Python language elements and a glossary of computing and biological terms. This title will teach undergraduates, postgraduates and professionals working in the life sciences how to program with Python, a powerful, flexible and easy-to-use language.
Computational Logic and Human Thinking
Author : Robert Kowalski
Publisher :
Page : 310 pages
File Size : 35,49 MB
Release : 2011
Category : Communication
ISBN : 9781107214453
Book Description
"The practical benefits of computational logic need not be limited to mathematics and computing. As this book shows, ordinary people in their everyday lives can profit from the recent advances that have been developed for artificial intelligence. The book draws upon related developments in various fields from philosophy to psychology and law. It pays special attention to the integration of logic with decision theory, and the use of logic to improve the clarity and coherence of communication in natural languages such as English. This book is essential reading for teachers and researchers who may be out of touch with the latest developments in computational logic. It will also be useful in any undergraduate course that teaches practical thinking, problem solving or communication skills. Its informal presentation makes the book accessible to readers from any background, but optional, more formal, chapters are also included for those who are more technically oriented"--
Cancer Systems Biology
Author : Edwin Wang
Publisher : CRC Press
Page : 458 pages
File Size : 16,19 MB
Release : 2010-05-04
Category : Computers
ISBN : 1439811865
Book Description
The unprecedented amount of data produced with high-throughput experimentation forces biologists to employ mathematical representation and computation to glean meaningful information in systems-level biology. Applying this approach to the underlying molecular mechanisms of tumorgenesis, cancer research is enjoying a series of new discoveries and biological insights. Unique in its dualistic approach, this book introduces the concepts and theories of systems biology and their applications in cancer research. It presents basic cancer biology and cutting-edge topics of cancer research for computational biologists alongside systems biology analysis tools for experimental biologists.
Computing for Biologists
Author : Ran Libeskind-Hadas
Publisher : Cambridge University Press
Page : 289 pages
File Size : 37,71 MB
Release : 2014-09-22
Category : Science
ISBN : 1316061337
Book Description
Computing is revolutionizing the practice of biology. This book, which assumes no prior computing experience, provides students with the tools to write their own Python programs and to understand fundamental concepts in computational biology and bioinformatics. Each major part of the book begins with a compelling biological question, followed by the algorithmic ideas and programming tools necessary to explore it: the origins of pathogenicity are examined using gene finding, the evolutionary history of sex determination systems is studied using sequence alignment, and the origin of modern humans is addressed using phylogenetic methods. In addition to providing general programming skills, this book explores the design of efficient algorithms, simulation, NP-hardness, and the maximum likelihood method, among other key concepts and methods. Easy-to-read and designed to equip students with the skills to write programs for solving a range of biological problems, the book is accompanied by numerous programming exercises, available at www.cs.hmc.edu/CFB.
Emerging Trends in Computational Biology, Bioinformatics, and Systems Biology
Author : Hamid R Arabnia
Publisher : Morgan Kaufmann
Page : 670 pages
File Size : 33,34 MB
Release : 2015-08-11
Category : Computers
ISBN : 0128026464
Book Description
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.
