Computational Methods for Protein Structure Prediction and Modeling

Computational Methods for Protein Structure Prediction and Modeling
Author: Ying Xu
Publisher: Springer Science & Business Media
Total Pages: 408
Release: 2007-08-24
Genre: Science
ISBN: 0387683720

Download Computational Methods for Protein Structure Prediction and Modeling Book in PDF, Epub and Kindle

Volume One of this two-volume sequence focuses on the basic characterization of known protein structures, and structure prediction from protein sequence information. Eleven chapters survey of the field, covering key topics in modeling, force fields, classification, computational methods, and structure prediction. Each chapter is a self contained review covering definition of the problem and historical perspective; mathematical formulation; computational methods and algorithms; performance results; existing software; strengths, pitfalls, challenges, and future research.

Computational Methods for Protein Structure Prediction and Modeling

Computational Methods for Protein Structure Prediction and Modeling
Author: Ying Xu
Publisher: Springer Science & Business Media
Total Pages: 335
Release: 2010-05-05
Genre: Science
ISBN: 0387688250

Download Computational Methods for Protein Structure Prediction and Modeling Book in PDF, Epub and Kindle

Volume Two of this two-volume sequence presents a comprehensive overview of protein structure prediction methods and includes protein threading, De novo methods, applications to membrane proteins and protein complexes, structure-based drug design, as well as structure prediction as a systems problem. A series of appendices review the biological and chemical basics related to protein structure, computer science for structural informatics, and prerequisite mathematics and statistics.

Computational Methods for Protein Structure Prediction and Modeling

Computational Methods for Protein Structure Prediction and Modeling
Author: Ying Xu
Publisher: Springer
Total Pages: 0
Release: 2010-12-01
Genre: Science
ISBN: 9781441922069

Download Computational Methods for Protein Structure Prediction and Modeling Book in PDF, Epub and Kindle

Volume Two of this two-volume sequence presents a comprehensive overview of protein structure prediction methods and includes protein threading, De novo methods, applications to membrane proteins and protein complexes, structure-based drug design, as well as structure prediction as a systems problem. A series of appendices review the biological and chemical basics related to protein structure, computer science for structural informatics, and prerequisite mathematics and statistics.

Computational Methods in Protein Evolution

Computational Methods in Protein Evolution
Author: Tobias Sikosek
Publisher: Humana
Total Pages: 0
Release: 2018-10-09
Genre: Science
ISBN: 9781493987351

Download Computational Methods in Protein Evolution Book in PDF, Epub and Kindle

This volume presents a diverse collection of methodologies used to study various problems at the protein sequence and structure level. The chapters in this book look at issues ranging from broad concepts like protein space to specifics like antibody modeling. Topics include point mutations, gene duplication, de novo emergence of new genes, pairwise correlated mutations, ancestral protein reconstruction, homology modelling, protein stability and dynamics, and protein-protein interactions. The book also covers a wide range of computational approaches, including sequence and structure alignments, phylogenies, physics-based and mathematical approaches, machine learning, and more. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and prerequisites, step-by-step, readily reproducible computational protocols (using command line or graphical user interfaces, sometimes including computer code), and tips on troubleshooting and avoiding known pitfalls. Cutting-edge and authoritative, Computational Methods in Protein Evolution is a valuable resource that offers useful workflows and techniques that will help both novice and expert researchers working with proteins computationally.

Practical Bioinformatics

Practical Bioinformatics
Author: Janusz M. Bujnicki
Publisher: Springer
Total Pages: 265
Release: 2007-09-12
Genre: Science
ISBN: 3540742689

Download Practical Bioinformatics Book in PDF, Epub and Kindle

This book presents applications of bioinformatics tools that experimental research scientists use in "daily practice." Its interdisciplinary approach combines computational and experimental methods to solve scientific problems. The book begins with reviews of computational methods for protein sequence-structure-function analysis, followed by methods that use experimental data obtained in the laboratory to improve functional predictions.

Introduction to Protein Structure Prediction

Introduction to Protein Structure Prediction
Author: Huzefa Rangwala
Publisher: John Wiley & Sons
Total Pages: 611
Release: 2011-03-16
Genre: Science
ISBN: 111809946X

Download Introduction to Protein Structure Prediction Book in PDF, Epub and Kindle

A look at the methods and algorithms used to predict protein structure A thorough knowledge of the function and structure of proteins is critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this reference sheds light on the methods used for protein structure prediction and reveals the key applications of modeled structures. This indispensable book covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology. With this resource, readers will find an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction and they will acquire unique insight into the future applications of the modeled protein structures. The book begins with a thorough introduction to the protein structure prediction problem and is divided into four themes: a background on structure prediction, the prediction of structural elements, tertiary structure prediction, and functional insights. Within those four sections, the following topics are covered: Databases and resources that are commonly used for protein structure prediction The structure prediction flagship assessment (CASP) and the protein structure initiative (PSI) Definitions of recurring substructures and the computational approaches used for solving sequence problems Difficulties with contact map prediction and how sophisticated machine learning methods can solve those problems Structure prediction methods that rely on homology modeling, threading, and fragment assembly Hybrid methods that achieve high-resolution protein structures Parts of the protein structure that may be conserved and used to interact with other biomolecules How the loop prediction problem can be used for refinement of the modeled structures The computational model that detects the differences between protein structure and its modeled mutant Whether working in the field of bioinformatics or molecular biology research or taking courses in protein modeling, readers will find the content in this book invaluable.

Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications

Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications
Author: K. G. Srinivasa
Publisher: Springer Nature
Total Pages: 318
Release: 2020-01-30
Genre: Technology & Engineering
ISBN: 9811524459

Download Statistical Modelling and Machine Learning Principles for Bioinformatics Techniques, Tools, and Applications Book in PDF, Epub and Kindle

This book discusses topics related to bioinformatics, statistics, and machine learning, presenting the latest research in various areas of bioinformatics. It also highlights the role of computing and machine learning in knowledge extraction from biological data, and how this knowledge can be applied in fields such as drug design, health supplements, gene therapy, proteomics and agriculture.

Protein Structure Prediction

Protein Structure Prediction
Author: Mohammed Zaki
Publisher: Springer Science & Business Media
Total Pages: 338
Release: 2007-09-12
Genre: Science
ISBN: 1588297527

Download Protein Structure Prediction Book in PDF, Epub and Kindle

This book covers elements of both the data-driven comparative modeling approach to structure prediction and also recent attempts to simulate folding using explicit or simplified models. Despite the unsolved mystery of how a protein folds, advances are being made in predicting the interactions of proteins with other molecules. Also rapidly advancing are the methods for solving the inverse folding problem, the problem of finding a sequence to fit a structure. This book focuses on the various computational methods for prediction, their successes and their limitations, from the perspective of their most well known practitioners.