Predictive Modeling of Drug Sensitivity

Ranadip Pal

ISBN 10: 0128052740 / ISBN 13: 9780128052747

Published by Elsevier Inc, 2016

About this Item

Predictive Modeling of Drug Sensitivity | Ranadip Pal | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2016 | Elsevier Inc | EAN 9780128052747 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.

Seller Inventory # 129934859

Bibliographic Details

• Title: Predictive Modeling of Drug Sensitivity
• Publisher: Elsevier Inc
• Publication Date: 2016
• Language: English
• ISBN 10: 0128052740
• ISBN 13: 9780128052747
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 191H x 19D millimeters 235 millimeters width by 191 millimeters height by 19 millimeters depth
• Weight: 613 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Predictive Modeling of Drug Sensitivity gives an overview of drug sensitivity modeling for personalized medicine that includes data characterizations, modeling techniques, applications, and research challenges. It covers the major mathematical techniques used for modeling drug sensitivity, and includes the requisite biological knowledge to guide a user to apply the mathematical tools in different biological scenarios.

This book is an ideal reference for computer scientists, engineers, computational biologists, and mathematicians who want to understand and apply multiple approaches and methods to drug sensitivity modeling. The reader will learn a broad range of mathematical and computational techniques applied to the modeling of drug sensitivity, biological concepts, and measurement techniques crucial to drug sensitivity modeling, how to design a combination of drugs under different constraints, and the applications of drug sensitivity prediction methodologies.

• Applies mathematical and computational approaches to biological problems
• Covers all aspects of drug sensitivity modeling, starting from initial data generation to final experimental validation
• Includes the latest results on drug sensitivity modeling that is based on updated research findings
• Provides information on existing data and software resources for applying the mathematical and computational tools available

About the Author

Ranadip Pal is an associate professor in the Electrical and Computer Engineering Department, at the Texas Tech University, USA. His research areas are stochastic modeling and control, genomic signal processing, and computational biology. He is the author of more than 60 peer-reviewed articles including publications in high impact journals such as Nature Medicine and Cancer Cell. He has contributed extensively to robustness analysis of genetic regulatory networks and predictive modeling of drug sensitivity. His research group was a top performer in NCI supported drug sensitivity prediction challenge.