Pathway Analysis for Drug Discovery: Computational Infrastructure and Applications

Novel computational approaches to improve the effectiveness and efficiency of drug discovery
With chapters contributed by pioneers in the field, Pathway Analysis for Drug Discovery offers readers both important new research findings and state–of–the–science reviews. The book not only presents the latest developments in pathway analysis, it also explains how these developments can improve and accelerate drug discovery, highlighting new opportunities for drug development.
Rather than search for and pore through scores of articles published in disparate sources, readers can turn to Pathway Analysis for Drug Discovery. This single, carefully edited work:
Introduces drug discovery researchers to novel computational approaches that enable them to better understand molecular function
Focuses on cell and molecular signaling pathways, demonstrating how the underlying method theory and algorithm details are used in drug discovery
Offers a comprehensive overview and unbiased assessment of applied methods for the pharmaceutical industry
In addition to traditional computational methods and software for pathway analysis, the book also covers:
Pathway reconstruction of diseases and toxic states
Pathway analysis for selection of drug targets, lead compound validation, and prediction of compound ADMET properties
Dynamic modeling of drug responses
Pathway analysis for design of selective drug mixtures and promiscuous drugs
Researchers who turn to this book will discover a variety of leading–edge methods to improve both the effectiveness and efficiency of their drug discovery and design efforts and gain an understanding of the role of pathway analysis infrastructure in modern and future drug discovery.

Spis treści:
Preface.
Contributors.
1 Introduction to Pathway Analysis (Anton Yuryev).
2 Software Infrastructure and Data Mo del for Pathway Analysis (Fedor Bokov and Anton Yuryev).
3 Automatic Pathway Inference in Heterogeneous Biological Association Networks (Anton Yuryev, Andrey Kalinin, and Nikolai Daraselia).
4 Algorithmic Basis for Pathway Visualization (Sergey Simakov, Iaroslav Ispolatov, Sergei Maslov, and Alexander Nikitin).
5 Pathway Analysis of High–Throughput Experimental Data (Andrey Y. Sivachenko).
6 Integrative Pathway Analysis of Disease Molecular Data (Andrej Bugrim, Zoltan Dezso, Yuri Nikolsky, and Tatiana Nikolskaya).
7 Whole–Genome Expression Profi ling of Papillary Serous Ovarian Cancer: Activated Pathways, Potential Targets, and Noise (John Farley, Laurent L. Ozbun, and Michael J. Birrer).
8 Mammalian Proteome and Toxicant Network Analysis (Sean Ekins and Craig N. Giroux).
9 Unraveling Mechanisms of Toxicity with the Power of Pathways: ToxWiz Tool as an Illustrative Example (Mark P. Kühnel, Bojana Cosovic, Goran Medic, Robert B. Russell, and Gordana Apic).
10 Impact of Chemistry Information on Pathway Analysis (Sreenivas Devidas).
11 Propagation of Concentration Perturbations in Equilibrium Protein Binding Networks (Sergei Maslov and Iaroslav Ispolatov).
12 An Adaptive System Model of the Yeast Glucose Sensor System (Todor Vujasinovic and André Siniša Žampera).
13 Present and Future of Pathway Analysis in Drug Discovery (Anton Yuryev).
Index.

Nota biograficzna:
ANTON YURYEV, PhD, is the Senior Director of Application Science at Ariadne Genomics Inc. His department studies the topological and evolutionary properties of biological networks and develops algorithms for pathway reconstruction and analysis of high–throughput data. Dr. Yuryev has published more than thirty scientific publications and is the author of several algorithms for primer design and pathway analysis.

Okła dka tylna:
Novel computational approaches to improve the effectiveness and efficiency of drug discovery
With chapters contributed by pioneers in the field, Pathway Analysis for Drug Discovery offers readers both important new research findings and state–of–the–science reviews. The book not only presents the latest developments in pathway analysis, it also explains how these developments can improve and accelerate drug discovery, highlighting new opportunities for drug development.
Rather than search for and pore through scores of articles published in disparate sources, readers can turn to Pathway Analysis for Drug Discovery. This single, carefully edited work:
Introduces drug discovery researchers to novel computational approaches that enable them to better understand molecular function
Focuses on cell and molecular signaling pathways, demonstrating how the underlying method theory and algorithm details are used in drug discovery
Offers a comprehensive overview and unbiased assessment of applied methods for the pharmaceutical industry
In addition to traditional computational methods and software for pathway analysis, the book also covers:
Pathway reconstruction of diseases and toxic states
Pathway analysis for selection of drug targets, lead compound validation, and prediction of compound ADMET properties
Dynamic modeling of drug responses
Pathway analysis for design of selective drug mixtures and promiscuous drugs
Researchers who turn to this book will discover a variety of leading–edge methods to improve both the effectiveness and efficiency of their drug discovery and design efforts and gain an understanding of the role of pathway analysis infrastructure in modern and future drug discovery.