Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics An in-depth look at the latest research, methods, and applications in the field of protein bioinformatics This book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and techniques for analyzing and interpreting protein data and solving a variety of biological problems. Featuring a collection of authoritative articles by leaders in the field, this work focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and AI methods. It also examines, in great detail, data preparation, simulation, experiments, evaluation methods, and applications. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics: Highlights protein analysis applications such as protein-related drug activity comparison Incorporates salient case studies illustrating how to apply the methods outlined in the book Tackles the complex relationship between proteins from a systems biology point of view Relates the topic to other emerging technologies such as data mining and visualization Includes many tables and illustrations demonstrating concepts and performance figures Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics is an essential reference for bioinformatics specialists in research and industry, and for anyone wishing to better understand the rich field of protein bioinformatics.

Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics An in-depth look at the latest research, methods, and applications in the field of protein bioinformatics This book presents the latest developments in protein bioinformatics, introducing for the first time cutting-edge research results alongside novel algorithmic and AI methods for the analysis of protein data. In one complete, self-contained volume, Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics addresses key challenges facing both computer scientists and biologists, arming readers with tools and techniques for analyzing and interpreting protein data and solving a variety of biological problems. Featuring a collection of authoritative articles by leaders in the field, this work focuses on the analysis of protein sequences, structures, and interaction networks using both traditional algorithms and AI methods. It also examines, in great detail, data preparation, simulation, experiments, evaluation methods, and applications. Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics: Highlights protein analysis applications such as protein-related drug activity comparison Incorporates salient case studies illustrating how to apply the methods outlined in the book Tackles the complex relationship between proteins from a systems biology point of view Relates the topic to other emerging technologies such as data mining and visualization Includes many tables and illustrations demonstrating concepts and performance figures Algorithmic and Artificial Intelligence Methods for Protein Bioinformatics is an essential reference for bioinformatics specialists in research and industry, and for anyone wishing to better understand the rich field of protein bioinformatics.

The 14 papers consider how various methods in artificial intelligence are applied to problems in bioinformatics. Among the topics are statistical learning and kernel methods in bioinformatics, new machine learning methods for predicting protein topologies, multiple sequence alignments information in structure and function prediction, pattern discovery and the algorithms of surprise, the computational identification of regulatory sites in DNA sequences, computer system gene discovery for promoter structure analysis, and data acquisition and analysis in near-genome-wide expressions screening of tumor suppressor pathways using model cell lines with inducible transcription factors. There is no subject index. Annotation : 2004 Book News, Inc., Portland, OR (booknews.com).

"This book is a comprehensive and in-depth reference to the most recent developments in the field covering theoretical developments, techniques, technologies, among others"--Provided by publisher.

Available in print and online, this unique reference brings together all four fields of genetics, genomics, proteomics, and bioinformatics to meet your dynamic research requirements. It brings together the latest concepts in these vibrant areas and ensures a truly multidisciplinary approach. Topics include genetic variation and evolution, epigenetics, the human genome, expression profiling, proteome families, structural proteomics, gene finding/gene structure, protein function and annotation, and more. The work incorporates a vast amount of topical information, profiles cutting-edge techniques, and presents the very latest findings from an international team of over five hundred contributors. With articles for both students and more experienced scientists, this is a key reference source for everyone. Contains more than 450 articles covering all aspects of genomics, proteomics, bioinformatics and related technologies Includes a glossary containing over 550 clear and concise definitions "I am pleased to recommend it heartily as a essential reference tool...should remain the definitive work...for many years to come." THE CHEMICAL EDUCATOR "Jorde...and co-editors have done a remarkable job in coordinating this information, distilling it into a package that is both easy to navigate and over-flowing in discovery." ELECTRIC REVIEW

V.1: Basic technologies: From Genomes to drugs with bioinformatics (Thomas Lengauer); Sequence analysis (Martin Vingron); Structure, properties and computer identification of eukaryotic genes (Victor Solovyev). Analyzing regulatory regions in genomes (Thomas Werner). Homology modeling in biology and medicine (Roland L. Dunbrack, Jr.). Protein structure prediction (Ralf Zimmer and Thomas Lengauer). Protein-ligand docking in drug design (Matthias Rarey). Modellimg protein-protein and protein-DNA docking (Michael J. E. Sternberg and Gidon Moont). v.2: Applications: Integrating and accessing molecular biology resources (David P. Hansen and Thure Etzold). Bioinformatics support of genome sequencing projects (Xiaoqiu Huang). Analysis of sequence variations (Christopher S. Carlson, Mark J. Rieder and Deborah A. Nickerson). Proteome analysis (Pierre-Alain Binz, Elisabeth Gasteiger, Jean-Charles Sanchez, Amos Bairoch, Denis F. Hochstrasser, Ron D. Appel). Target finding in genomes and proteomes (Stephanie Fuhrman Liang, Xiling Wen and Roland Somogyi). Screening of drug databases (Martin Stahl, Matthias Rarey and Gerhard Klebe). Future trends (Thomas Lengauer).

The papers included in this volume provide a forum for researchers in computational intelligence field to exchange ideas on smart engineering systems architecting and design.