Gene function annotation has been a central question in molecular biology. The importance of computational function prediction is increasing because more and more large scale biological data, including genome sequences, protein structures, protein-protein interaction data, microarray expression data, and mass spectrometry data, are awaiting biological interpretation. Traditionally when a genome is sequenced, function annotation of genes is done by homology search methods, such as BLAST or FASTA. However, since these methods are developed before the genomics era, conventional use of them is not necessarily most suitable for analyzing a large scale data. Therefore we observe emerging development of computational gene function prediction methods, which are targeted to analyze large scale data, and also those which use such omics data as additional source of function prediction. In this book, we overview this emerging exciting field. The authors have been selected from 1) those who develop novel purely computational methods 2) those who develop function prediction methods which use omics data 3) those who maintain and update data base of function annotation of particular model organisms (E. coli), which are frequently referred

This volume presents established bioinformatics tools and databases for function prediction of proteins. Reflecting the diversity of this active field in bioinformatics, the chapters in this book discuss a variety of tools and resources such as sequence-, structure-, systems-, and interaction-based function prediction methods, tools for functional analysis of metagenomics data, detecting moonlighting-proteins, sub-cellular localization prediction, and pathway and comparative genomics databases. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step instructions of how to use software and web resources, use cases, and tips on troubleshooting and avoiding known pitfalls. Thorough and cutting-edge, Protein Function Prediction: Methods and Protocols is a valuable and practical guide for using bioinformatics tools for investigating protein function

Protein Structure Prediction, Third Edition expands on previous editions by focusing on software and web servers. With new chapters that provide instructions on how to use a computational method with examples of prediction by the method. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials, step-by-step, readily reproducible protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Protein Structure Prediction, Third Edition provides diverse methods detailing the expansion of the computational protein structure prediction field.

Protein Structure Prediction, Third Edition expands on previous editions by focusing on software and web servers. With new chapters that provide instructions on how to use a computational method with examples of prediction by the method. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials, step-by-step, readily reproducible protocols, and key tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, Protein Structure Prediction, Third Edition provides diverse methods detailing the expansion of the computational protein structure prediction field.

Gene function annotation has been a central question in molecular biology. The importance of computational function prediction is increasing because more and more large scale biological data, including genome sequences, protein structures, protein-protein interaction data, microarray expression data, and mass spectrometry data, are awaiting biological interpretation. Traditionally when a genome is sequenced, function annotation of genes is done by homology search methods, such as BLAST or FASTA. However, since these methods are developed before the genomics era, conventional use of them is not necessarily most suitable for analyzing a large scale data. Therefore we observe emerging development of computational gene function prediction methods, which are targeted to analyze large scale data, and also those which use such omics data as additional source of function prediction. In this book, we overview this emerging exciting field. The authors have been selected from 1) those who develop novel purely computational methods 2) those who develop function prediction methods which use omics data 3) those who maintain and update data base of function annotation of particular model organisms (E. coli), which are frequently referred

This volume presents established bioinformatics tools and databases for function prediction of proteins. Reflecting the diversity of this active field in bioinformatics, the chapters in this book discuss a variety of tools and resources such as sequence-, structure-, systems-, and interaction-based function prediction methods, tools for functional analysis of metagenomics data, detecting moonlighting-proteins, sub-cellular localization prediction, and pathway and comparative genomics databases. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, step-by-step instructions of how to use software and web resources, use cases, and tips on troubleshooting and avoiding known pitfalls. Thorough and cutting-edge, Protein Function Prediction: Methods and Protocols is a valuable and practical guide for using bioinformatics tools for investigating protein function