Computational Chemogenomics

ISBN-13: 9781493986385 / Angielski / Twarda / 2018 / 454 str.

J. B. Brown

Opis

This thorough book provides a collection of techniques used in the emerging field of computational chemogenomics, which is an integration of chemoinformatics, bioinformatics, computer science, statistics, automated pattern recognition and modeling, database usage with data retrieval, and systems integration.

Spis treści

Part I: Data Resources for Computational Chemogenomics

 

1. A Survey of Web-Based Chemogenomic Data Resources

            Rasel Al Mahmud, Rifat Ara Najnin, and Ahsan Habib Polash

 

2. Finding Potential Multi-Target Ligands Using PubChem

            Sunghwan Kim, Benjamin A. Shoemaker, Evan E. Bolton, and Stephen H. Bryant

 

Part II: Fundamental Data Processing

 

3. Fundamental Bioinformatic and Chemoinformatic Data Processing

            J.B. Brown

 

4. Parsing Compound-Protein Bioactivity Tables

            J.B. Brown

 

5. Impact of Molecular Descriptors on Computational Models

            Francesca Grisoni, Viviana Consonni, and Roberto Todeschini

 

6. Physicochemical Property Labels as Molecular Descriptors for Improved Analysis of Compound-Protein and Compound-Compound Networks

            Masaaki Kotera

 

7. Core Statistical Methods for Chemogenomic Data

            Christin Rakers

 

Part III: Structural Analysis Methods in 2D and 3D

 

8. Structure-Based Detection of Orthosteric and Allosteric Pockets at Protein-Protein Interfaces

            Franck Da Silva and Didier Rognan

 

9. Single Binding Pockets versus Allosteric Binding

            Kun Song and Jian Zhang

 

10. Mapping Biological Activities to Different Types of Molecular Scaffolds: Exemplary Application to Protein Kinase Inhibitors

            Dilyana Dimova and Jürgen Bajorath

 

11. SAR Matrix Method for Large-Scale Analysis of Compound Structure-Activity Relationships and Exploration of Multi-Target Activity Spaces

            Ye Hu and Jürgen Bajorath

 

Part IV: Statistical Pattern Recognition

 

12. Linear and Kernel Model Construction Methods for Predicting Drug-Target Interactions in a Chemogenomic Framework

            Yoshihiro Yamanishi

 

13. Selection of Informative Examples in Chemogenomic Datasets

            Daniel Reker and J.B. Brown

 

Part V: Emerging Topics

 

14. A Platform for Comprehensive Genomic Profiling in Human Cancers and Pharmacogenomics Therapy Selection

            Tadayuki Kou, Masashi Kanai, Mayumi Kamada, Masahiko Nakatsui, Shigemi Matsumoto, Yasushi Okuno, and Manabu Muto

 

15. The Future of Computational Chemogenomics

            Edgar Jacoby and J.B. Brown

Blurb

This thorough book provides a collection of techniques used in the emerging field of computational chemogenomics, which is an integration of chemoinformatics, bioinformatics, computer science, statistics, automated pattern recognition and modeling, database usage with data retrieval, and systems integration. Beginning with a section on public chemogenomic data resources, the volume continues by delving into the fundamentals of chemoinformatics, bioinformatics, and chemogenomic data processing.  After the reader is comfortable with a core skillset, the volume introduces techniques to analyze specific proteins or compound structures and statistical pattern recognition techniques.  Later chapters describe the future of chemogenomics including applications to medical care. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that serves as an ideal guide in the lab. 

Practical and authoritative, Computational Chemogenomics will greatly aid experimental sciences who are novices to data processing and modeling, as well as those with computationally-oriented backgrounds wishing to engage in this scientific area, which is continually growing and expected to contribute to industry, academic, and government research projects.