Bioinformatics and drug discovery
Author(s)
Bibliographic Information
Bioinformatics and drug discovery
(Methods in molecular biology / John M. Walker, series editor, 1939)(Springer protocols)
Humana Press, c2019
3rd ed
Available at 3 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
Includes bibliographical references and index
Description and Table of Contents
Description
This third edition volume expands on the previous editions with new topics that cover drug discovery through translational bioinformatics, informatics, clinical research informatics, as well as clinical informatics. The chapters discuss new methods to study target identification, genome analysis, cheminformatics, protein analysis, and text mining. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials, software workflows, reagents and on-line resources, together with step-by-step, readily reproducible laboratory and computational protocols, and tips on troubleshooting and avoiding known pitfalls.
Cutting-edge and thorough, Bioinformatics and Drug Discovery, Third Edition is a valuable resource for anyone interested in drug design, including academicians (biologists, informaticists and data scientists, chemists, and biochemists), clinicians, and pharmaceutical scientists.
Table of Contents
Preface...
Table of Contents...
Contributing Authors...
Part I Translational Bioinformatics in Drug Discovery
1. Miniaturized Checkerboard Assays to Measure Antibiotic Interactions
Melike Cokol-Cakmak and Murat Cokol
2. High-Throughput Screening for Drug Combinations
Paul Shinn, Lu Chen, Marc Ferrer, Zina Itkin, Carleen Klumpp-Thomas, Crystal McKnight, Sam Michael, Tim Mierzwa, Craig Thomas, Kelli Wilson, Rajarshi Guha
3. Post-Processing of Large Bioactivity Data
Jason Bret Harris
4. How to Develop a Drug Target Ontology: KNowledge Acquisition and Representation Methodology (KNARM)
Hande Kucuk-McGinty, Ubbo Visser, and Stephan Schurer S.
Part II Informatics in Drug Discovery
5. A Guide to Dictionary-Based Text Mining
Helen V. Cook and Lars Juhl Jensen
6. Leveraging Big Data to Transform Drug Discovery
Benjamin S. Glicksberg, Li Li, Rong Chen, Joel T. Dudley, and Bin Chen
7. How to Prepare a Compound Collection Prior to Virtual Screening
Cristian G. Bologa, Oleg Ursu, and Tudor I. Oprea
8. Building a Quantitative Structure-Property Relationship (QSPR) Model
Robert D. Clark and Pankaj R. Daga
9. Isomeric and Conformational Analysis of Small Drug and Drug-Like Molecules by Ion Mobility Mass Spectrometry (IM-MS)
Shawn T. Phillips, James N. Dodds, Jody C. May, and John A. McLean
Part III Clinical Research Informatics in Drug Discovery
10. A Computational Platform and Guide for Acceleration of Novel Medicines and Personalized Medicine
Ioannis N. Melas, Theodore Sakellaropoulos, Junguk Hur, Dimitris Messinis, Ellen Y. Guo, Leonidas G. Alexopoulos, Jane P.F. Bai
11. Omics Data Integration and Analysis for Systems Pharmacology
Hansaim Lim and Lei Xie
12. Bioinformatics Based Tools and Software in Clinical Research: A New Emerging Area
Parveen Bansal, Malika Arora, Vikas Gupta, and Mukesh Maithani
13. Text Mining for Drug Discovery
Si Zheng, Shazia Dharssi, Meng Wu, Jiao Li, Zhiyong Lu
Part IV Clinical Informatics in Drug Discovery
14. Big Data Cohort Extraction for Personalized Statin Treatment and Machine Learning
Terrence J. Adam and Chih-Lin Chi
15. Drug Signature Detection Based on L1000 Genomic and Proteomic Big Data
Wei Chen and Xiaobo Zhou
16. Drug Effect Prediction by Integrating L1000 Genomic and Proteomic Big Data
Wei Chen and Xiaobo Zhou
17. A Bayesian Network Approach to Disease Subtype Discovery
Mei-Sing Ong
by "Nielsen BookData"