May 11, 2021

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Protein Function Prediction for Omics Era

Protein Function Prediction for Omics Era
Author : Daisuke Kihara
Publisher : Springer Science & Business Media
Release Date : 2011-04-19
Category : Medical
Total pages :310
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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

Protein Function Prediction

Protein Function Prediction
Author : Daisuke Kihara
Publisher : Humana Press
Release Date : 2017-05-20
Category : Science
Total pages :239
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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

New Approaches of Protein Function Prediction from Protein Interaction Networks

New Approaches of Protein Function Prediction from Protein Interaction Networks
Author : Jingyu Hou
Publisher : Academic Press
Release Date : 2017-01-13
Category : Mathematics
Total pages :124
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New Approaches of Protein Function Prediction from Protein Interaction Networks contains the critical aspects of PPI network based protein function prediction, including semantically assessing the reliability of PPI data, measuring the functional similarity between proteins, dynamically selecting prediction domains, predicting functions, and establishing corresponding prediction frameworks. Functional annotation of proteins is vital to biological and clinical research and other applications due to the important roles proteins play in various biological processes. Although the functions of some proteins have been annotated via biological experiments, there are still many proteins whose functions are yet to be annotated due to the limitations of existing methods and the high cost of experiments. To overcome experimental limitations, this book helps users understand the computational approaches that have been rapidly developed for protein function prediction. Provides innovative approaches and new developments targeting key issues in protein function prediction Presents heuristic ideas for further research in this challenging area

Prediction of Protein Structures, Functions, and Interactions

Prediction of Protein Structures, Functions, and Interactions
Author : Janusz M. Bujnicki
Publisher : John Wiley & Sons
Release Date : 2008-12-23
Category : Science
Total pages :302
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The growing flood of new experimental data generated by genome sequencing has provided an impetus for the development of automated methods for predicting the functions of proteins that have been deduced by sequence analysis and lack experimental characterization. Prediction of Protein Structures, Functions and Interactions presents a comprehensive overview of methods for prediction of protein structure or function, with the emphasis on their availability and possibilities for their combined use. Methods of modeling of individual proteins, prediction of their interactions, and docking of complexes are put in the context of predicting gene ontology (biological process, molecular function, and cellular component) and discussed in the light of their contribution to the emerging field of systems biology. Topics covered include: first steps of protein sequence analysis and structure prediction automated prediction of protein function from sequence template-based prediction of three-dimensional protein structures: fold-recognition and comparative modelling template-free prediction of three-dimensional protein structures quality assessment of protein models prediction of molecular interactions: from small ligands to large protein complexes macromolecular docking integrating prediction of structure, function, and interactions Prediction of Protein Structures, Functions and Interactions focuses on the methods that have performed well in CASPs, and which are constantly developed and maintained, and are freely available to academic researchers either as web servers or programs for local installation. It is an essential guide to the newest, best methods for prediction of protein structure and functions, for researchers and advanced students working in structural bioinformatics, protein chemistry, structural biology and drug discovery.

Computational Approaches to Protein Function Prediction

Computational Approaches to Protein Function Prediction
Author : Gaurav Pandey,Vipin Kumar,Michael Steinbach,Chad L. Meyers
Publisher : Wiley
Release Date : 2017-01-24
Category : Computers
Total pages :440
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This book provides a comprehensive overview of the field of automated protein function prediction. It covers many techniques for solving this problem by computational means and discusses the most important principles underlying these techniques. By clearly describing a wide variety of automated techniques for protein function prediction and summarizing the main concepts behind these techniques, this book greatly reduces the time and effort required to understand the problem of protein function predictions and the numerous bioinformatics solutions that have been developed for it.

Protein Function Prediction Using Decision Tree Technique

Protein Function Prediction Using Decision Tree Technique
Author : Venkata Rama Kumar Swamy Yedida
Publisher : Unknown
Release Date : 2008
Category : Computational biology
Total pages :80
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The human genome project and numerous other genome projects have produced a large and ever increasing amount of sequence data. One of the main research challenges in the post-genomic era is to understand the relationship between the nucleotide sequences of genes and the functions of the proteins they encode. The objective of this thesis is to develop an automated protein function prediction system that is based on a set of homologous proteins and gene ontology categories. A novel measure based on a set of best local alignments is used to identify the homologues. The biological functions of the homologous proteins are characterized with gene ontology annotations. The protein function prediction is performed based on data mining models using decision trees. The models are trained and tested using the complete proteome of model organism yeast. The results show that the prediction accuracy depends on individual functional groups of proteins. There is a general trend of decreased model accuracy with the level of a group on the gene ontology graph, but the accuracy at a fix level varies from group to group. The prediction accuracy varies from group to group, no obvious accuracy changes from one level to another. These variations of accuracy illustrate certain limitations of sequence-based protein function prediction methods. But the fundamental assumption used in this thesis, similar amino acid sequences implying similar biological functions, is largely valid. The prediction results based on the proteome of yeast indicate that the accuracies for most of the functional groups are over 75%. We conclude that the decision tree model can be used as a preliminary tool for protein function prediction although the prediction results need to be verified through other means.

From Protein Structure to Function with Bioinformatics

From Protein Structure to Function with Bioinformatics
Author : Daniel John Rigden
Publisher : Springer Science & Business Media
Release Date : 2008-12-11
Category : Science
Total pages :328
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Proteins lie at the heart of almost all biological processes and have an incredibly wide range of activities. Central to the function of all proteins is their ability to adopt, stably or sometimes transiently, structures that allow for interaction with other molecules. An understanding of the structure of a protein can therefore lead us to a much improved picture of its molecular function. This realisation has been a prime motivation of recent Structural Genomics projects, involving large-scale experimental determination of protein structures, often those of proteins about which little is known of function. These initiatives have, in turn, stimulated the massive development of novel methods for prediction of protein function from structure. Since model structures may also take advantage of new function prediction algorithms, the first part of the book deals with the various ways in which protein structures may be predicted or inferred, including specific treatment of membrane and intrinsically disordered proteins. A detailed consideration of current structure-based function prediction methodologies forms the second part of this book, which concludes with two chapters, focusing specifically on case studies, designed to illustrate the real-world application of these methods. With bang up-to-date texts from world experts, and abundant links to publicly available resources, this book will be invaluable to anyone who studies proteins and the endlessly fascinating relationship between their structure and function.

Prediction of Protein Structure and the Principles of Protein Conformation

Prediction of Protein Structure and the Principles of Protein Conformation
Author : G.D. Fasman
Publisher : Springer Science & Business Media
Release Date : 2012-12-06
Category : Science
Total pages :798
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The prediction of the conformation of proteins has developed from an intellectual exercise into a serious practical endeavor that has great promise to yield new stable enzymes, products of pharmacological significance, and catalysts of great potential. With the application of predic tion gaining momentum in various fields, such as enzymology and immunology, it was deemed time that a volume be published to make available a thorough evaluation of present methods, for researchers in this field to expound fully the virtues of various algorithms, to open the field to a wider audience, and to offer the scientific public an opportunity to examine carefully its successes and failures. In this manner the practitioners of the art could better evaluate the tools and the output so that their expectations and applications could be more realistic. The editor has assembled chapters by many of the main contributors to this area and simultaneously placed their programs at three national resources so that they are readily available to those who wish to apply them to their personal interests. These algorithms, written by their originators, when utilized on pes or larger computers, can instantaneously take a primary amino acid sequence and produce a two-or three-dimensional artistic image that gives satisfaction to one's esthetic sensibilities and food for thought concerning the structure and function of proteins. It is in this spirit that this volume was envisaged.

From Protein Structure to Function with Bioinformatics

From Protein Structure to Function with Bioinformatics
Author : Daniel J. Rigden
Publisher : Springer
Release Date : 2017-04-06
Category : Science
Total pages :503
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This book is about protein structural bioinformatics and how it can help understand and predict protein function. It covers structure-based methods that can assign and explain protein function based on overall folds, characteristics of protein surfaces, occurrence of small 3D motifs, protein-protein interactions and on dynamic properties. Such methods help extract maximum value from new experimental structures, but can often be applied to protein models. The book also, therefore, provides comprehensive coverage of methods for predicting or inferring protein structure, covering all structural classes from globular proteins and their membrane-resident counterparts to amyloid structures and intrinsically disordered proteins. The book is split into two broad sections, the first covering methods to generate or infer protein structure, the second dealing with structure-based function annotation. Each chapter is written by world experts in the field. The first section covers methods ranging from traditional homology modelling and fold recognition to fragment-based ab initio methods, and includes a chapter, new for the second edition, on structure prediction using evolutionary covariance. Membrane proteins and intrinsically disordered proteins are each assigned chapters, while two new chapters deal with amyloid structures and means to predict modes of protein-protein interaction. The second section includes chapters covering functional diversity within protein folds and means to assign function based on surface properties and recurring motifs. Further chapters cover the key roles of protein dynamics in protein function and use of automated servers for function inference. The book concludes with two chapters covering case studies of structure prediction, based respectively on crystal structures and protein models, providing numerous examples of real-world usage of the methods mentioned previously. This book is targeted at postgraduate students and academic researchers. It is most obviously of interest to protein bioinformaticians and structural biologists, but should also serve as a guide to biologists more broadly by highlighting the insights that structural bioinformatics can provide into proteins of their interest.

Introduction to Protein Structure Prediction

Introduction to Protein Structure Prediction
Author : Huzefa Rangwala,George Karypis
Publisher : John Wiley & Sons
Release Date : 2011-03-16
Category : Science
Total pages :520
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A look at the methods and algorithms used to predict proteinstructure A thorough knowledge of the function and structure of proteinsis critical for the advancement of biology and the life sciences aswell as the development of better drugs, higher-yield crops, andeven synthetic bio-fuels. To that end, this reference sheds lighton the methods used for protein structure prediction and revealsthe key applications of modeled structures. This indispensable bookcovers the applications of modeled protein structures and unravelsthe relationship between pure sequence information andthree-dimensional structure, which continues to be one of thegreatest challenges in molecular biology. With this resource, readers will find an all-encompassingexamination of the problems, methods, tools, servers, databases,and applications of protein structure prediction and they willacquire unique insight into the future applications of the modeledprotein structures. The book begins with a thorough introduction tothe protein structure prediction problem and is divided into fourthemes: a background on structure prediction, the prediction ofstructural elements, tertiary structure prediction, and functionalinsights. Within those four sections, the following topics arecovered: Databases and resources that are commonly used for proteinstructure prediction The structure prediction flagship assessment (CASP) and theprotein structure initiative (PSI) Definitions of recurring substructures and the computationalapproaches used for solving sequence problems Difficulties with contact map prediction and how sophisticatedmachine learning methods can solve those problems Structure prediction methods that rely on homology modeling,threading, and fragment assembly Hybrid methods that achieve high-resolution proteinstructures Parts of the protein structure that may be conserved and usedto interact with other biomolecules How the loop prediction problem can be used for refinement ofthe modeled structures The computational model that detects the differences betweenprotein structure and its modeled mutant Whether working in the field of bioinformatics or molecularbiology research or taking courses in protein modeling, readerswill find the content in this book invaluable.

Big Data Analytics in Genomics

Big Data Analytics in Genomics
Author : Ka-Chun Wong
Publisher : Springer
Release Date : 2016-10-24
Category : Computers
Total pages :428
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This contributed volume explores the emerging intersection between big data analytics and genomics. Recent sequencing technologies have enabled high-throughput sequencing data generation for genomics resulting in several international projects which have led to massive genomic data accumulation at an unprecedented pace. To reveal novel genomic insights from this data within a reasonable time frame, traditional data analysis methods may not be sufficient or scalable, forcing the need for big data analytics to be developed for genomics. The computational methods addressed in the book are intended to tackle crucial biological questions using big data, and are appropriate for either newcomers or veterans in the field.This volume offers thirteen peer-reviewed contributions, written by international leading experts from different regions, representing Argentina, Brazil, China, France, Germany, Hong Kong, India, Japan, Spain, and the USA. In particular, the book surveys three main areas: statistical analytics, computational analytics, and cancer genome analytics. Sample topics covered include: statistical methods for integrative analysis of genomic data, computation methods for protein function prediction, and perspectives on machine learning techniques in big data mining of cancer. Self-contained and suitable for graduate students, this book is also designed for bioinformaticians, computational biologists, and researchers in communities ranging from genomics, big data, molecular genetics, data mining, biostatistics, biomedical science, cancer research, medical research, and biology to machine learning and computer science. Readers will find this volume to be an essential read for appreciating the role of big data in genomics, making this an invaluable resource for stimulating further research on the topic.

Molecular Biology of the Cell

Molecular Biology of the Cell
Author : Bruce Alberts
Publisher : Unknown
Release Date : 2004
Category :
Total pages :129
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Protein Structure Prediction

Protein Structure Prediction
Author : Anna Tramontano
Publisher : John Wiley & Sons
Release Date : 2006-02-20
Category : Medical
Total pages :228
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While most textbooks on bioinformatics focus on genetic algorithms and treat protein structure prediction only superficially, this course book assumes a novel and unique focus. Adopting a didactic approach, the author explains all the current methods in terms of their reliability, limitations and user-friendliness. She provides practical examples to help first-time users become familiar with the possibilities and pitfalls of computer-based structure prediction, making this a must-have for students and researchers.

Essential Bioinformatics

Essential Bioinformatics
Author : Jin Xiong
Publisher : Cambridge University Press
Release Date : 2006-03-13
Category : Science
Total pages :129
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Essential Bioinformatics is a concise yet comprehensive textbook of bioinformatics, which provides a broad introduction to the entire field. Written specifically for a life science audience, the basics of bioinformatics are explained, followed by discussions of the state-of-the-art computational tools available to solve biological research problems. All key areas of bioinformatics are covered including biological databases, sequence alignment, genes and promoter prediction, molecular phylogenetics, structural bioinformatics, genomics and proteomics. The book emphasizes how computational methods work and compares the strengths and weaknesses of different methods. This balanced yet easily accessible text will be invaluable to students who do not have sophisticated computational backgrounds. Technical details of computational algorithms are explained with a minimum use of mathematical formulae; graphical illustrations are used in their place to aid understanding. The effective synthesis of existing literature as well as in-depth and up-to-date coverage of all key topics in bioinformatics make this an ideal textbook for all bioinformatics courses taken by life science students and for researchers wishing to develop their knowledge of bioinformatics to facilitate their own research.

Practical Protein Bioinformatics

Practical Protein Bioinformatics
Author : Florencio Pazos,Mónica Chagoyen
Publisher : Springer
Release Date : 2014-11-28
Category : Science
Total pages :106
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This book describes more than 60 web-accessible computational tools for protein analysis and is totally practical, with detailed explanations on how to use these tools and interpret their results and minimal mentions to their theoretical basis (only when that is required for making a better use of them). It covers a wide range of tools for dealing with different aspects of proteins, from their sequences, to their three-dimensional structures, and the biological networks they are immersed in. The selection of tools is based on the experience of the authors that lead a protein bioinformatics facility in a large research centre, with the additional constraint that the tools should be accessible through standard web browsers without requiring the local installation of specific software, command-line tools, etc. The web tools covered include those aimed to retrieve protein information, look for similar proteins, generate pair-wise and multiple sequence alignments of protein sequences, work with protein domains and motifs, study the phylogeny of a family of proteins, retrieve, manipulate and visualize protein three-dimensional structures, predict protein structural features as well as whole three-dimensional structures, extract biological information from protein structures, summarize large protein sets, study protein interaction and metabolic networks, etc. The book is associated to a dynamic web site that will reflect changes in the web addresses of the tools, updates of these, etc. It also contains QR codes that can be scanned with any device to direct its browser to the tool web site. This monograph will be most valuable for researchers in experimental labs without specific knowledge on bioinformatics or computing.