Catalogue


Introduction to computational proteomics /
Golan Yona.
imprint
Boca Raton : CRC Press/Taylor & Francis Group, c2011.
description
xxii, 739 p. : ill. (some col.)
ISBN
1584885556 (hardcover : alkaline paper), 9781584885559 (hardcover : alkaline paper)
format(s)
Book
Holdings
More Details
author
imprint
Boca Raton : CRC Press/Taylor & Francis Group, c2011.
isbn
1584885556 (hardcover : alkaline paper)
9781584885559 (hardcover : alkaline paper)
general note
"A Chapman & Hall book."
catalogue key
7375259
 
Includes bibliographical references and index.
A Look Inside
Reviews
This item was reviewed in:
Reference & Research Book News, April 2011
To find out how to look for other reviews, please see our guides to finding book reviews in the Sciences or Social Sciences and Humanities.
Summaries
Main Description
Introduction to Computational Proteomicsintroduces the field of computational biology through a focused approach that tackles the different steps and problems involved with protein analysis, classification, and meta-organization. The book starts with the analysis of individual entities and works its way through the analysis of more complex entities, from protein families to interactions, cellular pathways, and gene networks. The first part of the book presents methods for identifying the building blocks of the protein space, such as motifs and domains. It also describes algorithms for assessing similarity between proteins based on sequence and structure analysis as well as mathematical models, such as hidden Markov models and support vector machines, that are used to represent protein families and classify new instances. The second part covers methods that investigate higher order structure in the protein space through the application of unsupervised learning algorithms, such as clustering and embedding. The book also explores the broader context of proteins. It discusses methods for analyzing gene expression data, predicting protein-protein interactions, elucidating cellular pathways, and reconstructing gene networks. This book provides a coherent and thorough introduction to proteome analysis. It offers rigorous, formal descriptions, along with detailed algorithmic solutions and models. Each chapter includes problem sets from courses taught by the author at Cornell University and the Technion. Software downloads, data sets, and other material are available at biozon.org
Back Cover Copy
Focusing on protein classification and meta-organization, Computational Proteomics describes detailed methods for detecting self-organization in complex biological systems. This book presents the analysis of biological entities and their cellular counterparts and discusses methods for detecting the building blocks of proteins and for prediction and analysis of protein-protein interactions, expression data analysis, and pathway analysis. It also examines protein space and prediction of protein function. This book includes chapters on the analysis of protein-related data types, such as expression, as well as special chapters on Bayesian networks and their application to the protein space.
Bowker Data Service Summary
Focusing on protein classification and meta-organization, Golan Yona describes detailed methods for detecting self-organization in complex biological systems.
Back Cover Copy
Focusing on protein classification and meta-organization, this book describes detailed methods for detecting self-organization in complex biological systems. It presents analysis of biological entities and their cellular counterparts and discusses methods for detecting the building blocks of proteins and for prediction and analysis of protein-protein interactions, expression data analysis, and pathway analysis.
Unpaid Annotation
"This book tackles the steps and problems involved with protein analysis, classification, and meta-organization. It starts with the analysis of individual entities and proceeds to the analysis of more complex entities, from protein families to interactions, cellular pathways, and gene networks. The first part of the book presents methods for identifying the building blocks of the protein space, algorithms for assessing similarity between proteins, and mathematical models for representing protein families and classifying new instances. The second part covers methods that investigate higher order structure in the protein space through the application of unsupervised learning algorithms"--Provided by publisher.
Main Description
Introduction to Computational Proteomics introduces the field of computational biology through a focused approach that tackles the different steps and problems involved with protein analysis, classification, and meta-organization. The book starts with the analysis of individual entities and works its way through the analysis of more complex entities, from protein families to interactions, cellular pathways, and gene networks. The first part of the book presents methods for identifying the building blocks of the protein space, such as motifs and domains. It also describes algorithms for assessing similarity between proteins based on sequence and structure analysis as well as mathematical models, such as hidden Markov models and support vector machines, that are used to represent protein families and classify new instances. The second part covers methods that investigate higher order structure in the protein space through the application of unsupervised learning algorithms, such as clustering and embedding. The book also explores the broader context of proteins. It discusses methods for analyzing gene expression data, predicting protein-protein interactions, elucidating cellular pathways, and reconstructing gene networks. This book provides a coherent and thorough introduction to proteome analysis. It offers rigorous, formal descriptions, along with detailed algorithmic solutions and models. Each chapter includes problem sets from courses taught by the author at Cornell University and the Technion. Software downloads, data sets, and other material are available at biozon.org

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