Bioinformatics and Drug Discovery / Edition 1

Bioinformatics and Drug Discovery / Edition 1

by Richard S. Larson
     
 

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ISBN-10: 1617375098

ISBN-13: 9781617375095

Pub. Date: 12/09/2010

Publisher: Springer-Verlag New York, LLC

Many of the new technologies that are transforming drug discovery require a high degree of interdisciplinary expertise in physical science, life science, and computer science for bioinformatic analysis of their output. In Bioinformatics and Drug Discovery, a panel of researchers from academic and pharmaceutical laboratories describes readily reproducible

Overview

Many of the new technologies that are transforming drug discovery require a high degree of interdisciplinary expertise in physical science, life science, and computer science for bioinformatic analysis of their output. In Bioinformatics and Drug Discovery, a panel of researchers from academic and pharmaceutical laboratories describes readily reproducible bioinformatic methods to advance the drug discovery process from gene identification to protein modeling to the identification of specific drug candidates. The authors demonstrate these techniques, including microarray analysis, the analysis of genes as potential drug targets, virtual screening and in silico protein design, and cheminformatics, in a variety of practical situations. Because these technologies are still emergent, each chapter contains an extended introduction that explains the theory and application of the technology and techniques described. The protocols follow the successful Methods in Molecular Biology™ series format, each offering step-by-step laboratory instructions, an introduction outlining the principles behind the technique, lists of the necessary equipment and reagents, and tips on troubleshooting and avoiding known pitfalls.

Cutting-edge and highly practical, Bioinformatics and Drug Discovery makes it possible to apply in the research laboratory the powerful new technologies that promise to greatly improve and speed up the discovery of new drugs.

Product Details

ISBN-13:
9781617375095
Publisher:
Springer-Verlag New York, LLC
Publication date:
12/09/2010
Series:
Methods in Molecular Biology Series, #316
Edition description:
Softcover reprint of hardcover 1st ed. 2006
Pages:
444
Product dimensions:
5.98(w) x 9.02(h) x 0.04(d)

Table of Contents

New Strategies in Drug Discovery

Eliot H. Ohlstein, Anthony G. Johnson, John D. Elliot, and Anne M. Romanic

Basic Microarray Analysis: Strategies for Successful Experiments

Scott A. Ness

From Microarray to Biological Networks: Analysis of Gene Expression Profiles

Xiwei Wu and T. Gregory Dewey

Microarray Analysis in Drug Discovery and Clinical Applications

Siqun Wang and Qiong Cheng

Ontology-Driven Approaches to Analyzing Data in Functional Genomics

Francisco Azuaje, Fatima Al-Shahrour, and Joaquin Dopazo

Gene Evolution and Drug Discovery

James O. McInerney, Caroline S. Finnerty, Jennifer M. Commins, and Gayle K. Philip

Standardization of Microarray and Pharmacogenomics Data

Casey S. Husser, Jeffrey R. Buchhalter, O. Scott Raffo, Amnon Shabo, Steven H. Brown, Karen E. Lee, and Peter L. Elkin

Clinical Applications of Bioinformatics, Genomics, and Pharmacogenomics

Omer Iqbal and Jawed Fareed

Protein Interactions Probed With Mass Spectrometry

Suma Kaveti and John R. Engen

Discovering New Drug Targeting Sites on Flexible Multidomain Protein Kinases: Combining Segmental Isotopic and Site-Directed Spin Labeling for Nuclear Magnetic Resonance Dectection of Interfacial Clefts

Thomas K. Harris

Nuclear Magnetic Resonance-Based Screening Methods for Drug Discovery

Laurel O. Sillerud and Richard S. Larson

Receptor-Binding Sites: Bioinformatic Approaches

Darren R. Flower

In Silico Protein Design: Fitting Sequence Onto Structure

Bassil I. Dahiyat

Chemical Database Preparation for Compound Acquisition or Virtual Screening

Cristian G. Bologna, Marius M. Olah, and Tudor I. Oprea

Bioinformatics Platform Development: From Gene to Lead Compound

Alexis S. Ivanov, Alexander V. Veselovsky, Alexander V. Dubanov, and Vladlen S. Skvortsov

Index

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