
Pharmaceutical Data Mining : Approaches and Applications for Drug Discovery
by Konstantin V. Balakin; Series Editor: Sean EkinsRent Textbook
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Summary
Table of Contents
Preface | |
Acknowledgments | |
Contributors | |
Data Mining In The Pharmaceutical Industry: A General Overview | |
A History of the development of Data Mining in Pharmaceutical Research | |
Drug Gold and Data Dragons: Myths and Realities of Data Mining in the Pharmaceutical Industry | |
Application of Data Mining Algorithms in Pharmaceutical Research and Development | |
Chemoinformatics-Based Applications | |
Data Mining Approaches for Compound Selection and Iterative Screening | |
Prediction of Toxic Effects of Pharmaceutical Agents | |
Chemogenomics-Based Design of GPCR-Targeted Libraries Using Data Mining Techniques | |
Mining High-Throughput Screening Data by Novel Knowledge-Based Optimization Analysis | |
Bioinformatics-Based Applications | |
Mining DNA Microarray Gene Expression Data | |
Bioinformatics Approaches for Analysis of Protein-Ligand Interactions | |
Analysis of Toxicogenomic Databases | |
Bridging the Pharmaceutical Shortfall: Informatics Approaches to the Discovery of Vaccines, Antigens, Epitopes, and Adjuvants | |
Data Mining Methods In Clinical Development | |
Data Mining in Pharmacovigilance | |
Data Mining Methods as Tools for Predicting Individual Drug Response | |
Data Mining Methods in Pharmaceutical Formulation | |
Data Mining Algorithms And Technologies | |
Dimensionality Reduction Techniques for Pharmaceutical Data Mining | |
Advanced Artificial Intelligence Methods Used in the Design of Pharmaceutical Agents | |
Databases for Chemical and Biological Information | |
Mining Chemical Structural Information from the Literature | |
Index | |
Table of Contents provided by Publisher. All Rights Reserved. |
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