Homology modeling is an extremely useful and versatile technique that is gaining more and more space and demand in research in computational and theoretical biology. This book, “Homology Molecular Modeling - Perspectives and Applications”, brings together unpublished chapters on this technique. In this book, 7 chapters are intimately related to the theme of molecular modeling, carefully selected and edited for academic and scientific readers. It is an indispensable read for anyone interested in the areas of bioinformatics and computational biology. Divided into 4 sections, the reader will have a didactic and comprehensive view of the theme, with updated and relevant concepts on the subject. This book was organized from researchers to researchers with the aim of spreading the fascinating area of molecular modeling by homology.

Knowledge about protein tertiary structure can guide experiments, assist in the understanding of structure-function relationships, and aid the design of new therapeutics for disease. Homology modeling is an in silico method that predicts the tertiary structure of an amino acid sequence based on a homologous experimentally determined structure. In, Homology Modelling: Methods and Protocols experts in the field describe each homology modeling step from first principles, provide case studies for challenging modeling targets and describe methods for the prediction of how other molecules such as drugs can interact with the protein. Written in the highly successful Methods in Molecular BiologyTM series format, the chapters include the kind of detailed description and implementation advice that is crucial for getting optimal results in the laboratory. Thorough and intuitive, Homology Modelling: Methods and Protocols guides scientists in the available homology modeling methods.

This detailed volume provides state-of-the-art methodologies and reviews of important topics in the field of homology modeling. From homology modeling in the twilight zone and improving accuracy through sequence space analysis to approaches to construct multi-protein complex models, the book explores a wide variety of uses and applications of this valuable technique. Written for the highly successful Methods in Molecular Biology series, the chapters include introductions to their respective topics, lists of the necessary programs, webservers, and databases, step-by-step and readily reproducible protocols, as well as tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Homology Modeling: Methods and Protocols serves as an ideal guide to recent homology modeling procedures, assumptions made, and model quality assessment that will illuminate the black box of homology modeling for novice readers and broaden the knowledge of this methodology for professionals.

Structural Bioinformatics was the first major effort to show the application of the principles and basic knowledge of the larger field of bioinformatics to questions focusing on macromolecular structure, such as the prediction of protein structure and how proteins carry out cellular functions, and how the application of bioinformatics to these life science issues can improve healthcare by accelerating drug discovery and development. Designed primarily as a reference, the first edition nevertheless saw widespread use as a textbook in graduate and undergraduate university courses dealing with the theories and associated algorithms, resources, and tools used in the analysis, prediction, and theoretical underpinnings of DNA, RNA, and proteins. This new edition contains not only thorough updates of the advances in structural bioinformatics since publication of the first edition, but also features eleven new chapters dealing with frontier areas of high scientific impact, including: sampling and search techniques; use of mass spectrometry; genome functional annotation; and much more. Offering detailed coverage for practitioners while remaining accessible to the novice, Structural Bioinformatics, Second Edition is a valuable resource and an excellent textbook for a range of readers in the bioinformatics and advanced biology fields. Praise for the previous edition: "This book is a gold mine of fundamental and practical information in an area not previously well represented in book form." —Biochemistry and Molecular Education "... destined to become a classic reference work for workers at all levels in structural bioinformatics...recommended with great enthusiasm for educators, researchers, and graduate students." —BAMBED "...a useful and timely summary of a rapidly expanding field." —Nature Structural Biology "...a terrific job in this timely creation of a compilation of articles that appropriately addresses this issue." —Briefings in Bioinformatics

This is a comprehensive introduction to Landau-Lifshitz equations and Landau-Lifshitz-Maxwell equations, beginning with the work by Yulin Zhou and Boling Guo in the early 1980s and including most of the work done by this Chinese group led by Zhou and Guo since. The book focuses on aspects such as the existence of weak solutions in multi dimensions, existence and uniqueness of smooth solutions in one dimension, relations with harmonic map heat flows, partial regularity and long time behaviors. The book is a valuable reference book for those who are interested in partial differential equations, geometric analysis and mathematical physics. It may also be used as an advanced textbook by graduate students in these fields.

Probabilistic models are becoming increasingly important in analysing the huge amount of data being produced by large-scale DNA-sequencing efforts such as the Human Genome Project. For example, hidden Markov models are used for analysing biological sequences, linguistic-grammar-based probabilistic models for identifying RNA secondary structure, and probabilistic evolutionary models for inferring phylogenies of sequences from different organisms. This book gives a unified, up-to-date and self-contained account, with a Bayesian slant, of such methods, and more generally to probabilistic methods of sequence analysis. Written by an interdisciplinary team of authors, it aims to be accessible to molecular biologists, computer scientists, and mathematicians with no formal knowledge of the other fields, and at the same time present the state-of-the-art in this new and highly important field.

This volume covers an array of techniques available for studying peptide-protein docking and design. The book is divided into four sections: peptide binding site prediction; peptide-protein docking; prediction and design of peptide binding specificity; and the design of inhibitory peptides. The chapters in Modeling Peptide-Protein Interactions: Methods and Protocols cover topics such as the usage of ACCLUSTER and PeptiMap for peptide binding site prediction; AnchorDock and ATTRACT for blind, flexible docking of peptides to proteins; flexible peptide docking using HADDOCK and FlexPepDock; identifying loop-mediated protein-protein interactions using LoopFinder; and protein-peptide interaction design using PinaColada. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary details for successful application of the different approaches and step-by-step, readily reproducible protocols, as well as tips on troubleshooting and avoiding known pitfalls. Cutting-edge and thorough, Modeling Peptide-Protein Interactions: Methods and Protocols provides a diverse and unified overview of this rapidly advancing field of major interest and applicability.