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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.
List of contents
A Survey of Web-Based Chemogenomic Data Resources.- Finding Potential Multi-Target Ligands Using PubChem.- Fundamental Bioinformatic and Chemoinformatic Data Processing.- Parsing Compound-Protein Bioactivity Tables.- Impact of Molecular Descriptors on Computational Models.- Physicochemical Property Labels as Molecular Descriptors for Improved Analysis of Compound-Protein and Compound-Compound Networks.- Core Statistical Methods for Chemogenomic Data.- Structure-Based Detection of Orthosteric and Allosteric Pockets at Protein-Protein Interfaces.- Single Binding Pockets versus Allosteric Binding.- Mapping Biological Activities to Different Types of Molecular Scaffolds: Exemplary Application to Protein Kinase Inhibitors.- SAR Matrix Method for Large-Scale Analysis of Compound Structure-Activity Relationships and Exploration of Multi-Target Activity Spaces.- Linear and Kernel Model Construction Methods for Predicting Drug-Target Interactions in a Chemogenomic Framework.- Selection of Informative Examples in Chemogenomic Datasets.- A Platform for Comprehensive Genomic Profiling in Human Cancers and Pharmacogenomics Therapy Selection.- The Future of Computational Chemogenomics.
