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In Silico Technologies in Drug Target Identification and Validation
Editor(s) :Darryl Leon, Scott Markel


ISBN : 9781138387515
Name : In Silico Technologies in Drug Target Identification and Validation
Price : 3495.00
Editor/s : Darryl Leon, Scott Markel
Type : Reference Book
Pages : 504
Year of Publication : Rpt. 2021
Publisher : CRC Press BSP Books
Binding : Hardback
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About the Book:

The pharmaceutical industry relies on numerous well-designed experiments involving high-throughput techniques and in silico approaches to analyze potential drug targets. These in silico methods are often predictive, yielding faster and less expensive analyses than traditional in vivo or in vitro procedures.

 

In Silico Technologies in Drug Target Identification and Validation addresses the challenge of testing a growing number of new potential targets and reviews currently available in silico approaches for identifying and validating these targets. The book emphasizes computational tools, public and commercial databases, mathematical methods, and software for interpreting complex experimental data. The book describes how these tools are used to visualize a target structure, identify binding sites, and predict behavior. World-renowned researchers cover many topics not typically found in most informatics books, including functional annotation, siRNA design, pathways, text mining, ontologies, systems biology, database management, data pipelining, and pharmacogenomics.

Features:

·         Presents the most recent trends based on significant advances made in genomics, proteomics, and bioinformatics since the 1970s

·         Examines genomic correlations between different organisms and various models that simulate disease progression in humans

·         Details the components of BioIT hardware configuration and architecture requirements, a key tool for supporting in silico research

·         Reviews the numerous tools, initiatives, projects, and standards for ontologies and how they can be used in the drug discovery process

·         Provides examples and tables to illustrate the use of a particular technology as well as recommended books, journal articles, and Web sites for further information

Covering issues that range from prescreening target selection to genetic modeling and valuable data integration, In Silico Technologies in Drug Target Identification and Validation is a self-contained and practical guide to the various computational tools that can accelerate the identification and validation stages of drug target discovery and determine the biological functionality of potential targets more effectively.

Contents:

Part I: Target Identification

1.    Introduction

2.    Pattern Matching

3.    Tools for Computational Protein Annotation and Functional Assignment

4.    The Impact of Genetic Variation on Drug Discovery and Development

5.    Mining of Gene Expression Data

Part II: Target Validation

6.    Text Mining

7.    Pathways and Networks

8.    Molecular Interactions: Learning from Protein Complexes

9.    In Silico siRNA Design

10.  Predicting Protein Subcellular Localization Using Intelligent Systems

11.  Three-Dimensional Structures in Target Discovery and Validation

PART III: Recent Trends

12.  Comparative Genomics

13.  Pharmacogenomics

14.  Target Identification and Validation Using Human Simulation Models

15.  Using Protein Targets for In Silico Structure-Based Drug Discovery

PART IV: Computational Infrastructure

16.  Database Management

17.  BioIT Hardware Configuration

18.  BioIT Architecture: Software Architecture for Bioinformatics Research

19.  Workflows and Data Pipelines

20. Ontologies

About the Editors: 

Darryl Leo’n, Ph. D., is currently director of bioinformatics marketing at SciTegic in San Diego, California, where he provides the vision software requirements for bioinformatics-related products. He is also on the Bioinformatics Advisory Committee for the university of California San Diego Extension. Previously, he was director of life sciences at LION Bioscience, and was a bioinformatics scientist at NetGenics, DoubleTwist, and Genset. He was a faculty member at California Polytechnic State University, San Luis Obispo, and has authored several papers. He is a co-author, with Scott Markel, of Sequence Analysis in a Nutshell: A Guide to Common Tools and Databases. He has also taught at the University of California Santa Cruz Extension and at other colleges in northern California. Dr. Leon received his Ph.D. in biochemistry from the University of California-San Diego, and he did his postdoctoral research at the University of California-Santa Cruz. 

Scott Markel, Ph.D., is the principal bioinformatics architect at SciTegic, a division of Accelrys. In this role he is responsible for the design and implementation of SciTegic’s bioinformatics products. He is a member of the Board of Directors of the International Society for Computational Biology. He was most recently a research fellow and principal architech at LION Bioscience, where he was responsible for providing architectural direction in the development of software for the life science, including the use and development of standards. He was member of the Board of Directors of the Object Management Group and co-chair of the Life Science Research Domain Task Force. Prior to working at LION, Scott worked at NetGenics, Johnson & Johnson Pharmaceutical Research & Development, and Sarnoff Corporation. He has a Ph. D. in mathematics from the University of Wisconsin-Madison. He is a co-author, with Darryl Leon, of Sequence Analysis in a Nutshell: A Guide to Common Tools and Databases. 

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