Clinical Bioinformatics

ISBN-13: 9781588297914 / Angielski / Twarda / 2007 / 382 str.

Opis

With the ever-increasing volume of information in clinical medicine, researchers and health professionals need computer-based storage, processing and dissemination. In this book, leading experts in the field provide a series of articles focusing on software applications used to translate information into outcomes of clinical relevance. This book is the perfect guide for researchers and clinical scientists working in this emerging "omics" era.

Spis treści

Table of Contents Clinical Bioinformatics In Silico Gene Discovery Bing Yu Whole Genome Wide Association Study Using Affymetrix SNP Chip: a Two-Stage Sequential Selection Method to Identify Genes that Increase the Risk to Develop Complex Diseases. Howard H. Yang, Nan Hu, Philip R. Taylor and Maxwell P. Lee Utilizing HapMap and Tagging SNPs Christopher A. Haiman and Daniel O. Stram Measuring the Effects of Genes and Environment on Complex Traits Jennifer H. Barrett Microarrays – Planning your Experiment Jean Y. H. Yang Clinical Uses of Microarrays in Cancer Research Carl Virtanen and James Woodgett Microarrays – Analysis of Signaling Pathways Anassuya Ramachandran, Michael A. Black. Andrew N. Shelling and Donald R. Love Microarrays – Identifying Molecular Portraits for Prostate Tumors with Different Gleason Patterns Alexandre Mendes, Rodney J. Scott and Pablo Moscato Microarrays for the Study of Viral Gene Expression During Human Cytomegalovirus Latent Infection. Barry Slobedman and Allen K. L. Cheung Computer-Assisted Reading of DNA sequences Huong Le, Marcus Hinchliffe, Bing Yu and Ronald J. Trent Evaluating DNA Sequence Variants of Unknown Biological Significance Scott A. Grist, Andrew Dubowsky and Graeme Suthers Developing a DNA Variant Database David C. Y. Fung Protein Comparative Sequence Analysis and Computer Modeling Brett D. Hambly, Cecily E. Oakley and Piotr G.Fajer Identification and Characterization of Microbial Proteins Using Peptide Mass Fingerprinting Strategies Jonathan W. Arthur Statistical Analysis of Image Data Provided by Two-Dimensional Gel Electrophoresis for Discovery Proteomics Ben Crossett, Alistair V. G. Edwards, Melanie Y. White and Stuart J. Cordwell Online Resources for the Molecular Contextualization of Disease Chin N. I. Pang and Marc R. Wilkins Web Based Resources for Clinical Bioinformatics Anthony Joshua and Paul Boutros Developing Decision Support Systems in Clinical Bioinformatics Vitali Sintchenko and Enrico Coiera eConsulting Siaw-Teng Liaw and Peter Schattner

O autorze

In this volume of the Methods in Molecular Medicine, a number of strategies utilizing clinical bioinformatics are described. This series of articles focuses on software applications that can be used to translate information into outcomes of clinical relevance. Step-by-step instructions ensure successful results. The themes covered include gene discovery, gene function (microarrays), DNA mutation analysis, Proteomics, online approaches and resources, and Informatics in clinical practice. A challenge in clinical medicine is dealing with an ever increasing volume of information. This is particularly so in the emerging "omics" era, and impacts on researchers, health professionals and the broader community. To respond to this challenge requires computer-based storage, processing and dissemination i.e. bioinformatics.

Blurb

With the ever-increasing volume of information in clinical medicine, researchers and health professionals need computer-based storage, processing and dissemination.  In Clinical Bioinformatics, leading experts in the field provide a series of articles focusing on software applications used to translate information into outcomes of clinical relevance. Covering such topics as gene discovery, gene function (microarrays), DNA mutation analysis, proteomics, online approaches and resources, and informatics in clinical practice, this volume concisely yet thoroughly explores its cutting edge subject. 

In this emerging "omics" era, Clinical Bioinformatics is the perfect guide for researchers and clinical scientists to unlock the complex, dense, and ever-growing accumulation of medical information.