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Bioinformatics and Drug Discovery
Overview of attention for book
Table of Contents
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Book Overview
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Chapter 1
Miniaturized Checkerboard Assays to Measure Antibiotic Interactions
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Chapter 2
High-Throughput Screening for Drug Combinations
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Chapter 3
Post-processing of Large Bioactivity Data
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Chapter 4
How to Develop a Drug Target Ontology: KNowledge Acquisition and Representation Methodology (KNARM)
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Chapter 5
A Guide to Dictionary-Based Text Mining
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Chapter 6
Leveraging Big Data to Transform Drug Discovery
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Chapter 7
How to Prepare a Compound Collection Prior to Virtual Screening
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Chapter 8
Building a Quantitative Structure-Property Relationship (QSPR) Model
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Chapter 9
Isomeric and Conformational Analysis of Small Drug and Drug-Like Molecules by Ion Mobility-Mass Spectrometry (IM-MS)
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Chapter 10
A Computational Platform and Guide for Acceleration of Novel Medicines and Personalized Medicine
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Chapter 11
Omics Data Integration and Analysis for Systems Pharmacology
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Chapter 12
Bioinformatics-Based Tools and Software in Clinical Research: A New Emerging Area
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Chapter 13
Text Mining for Drug Discovery
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Chapter 14
Big Data Cohort Extraction for Personalized Statin Treatment and Machine Learning
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Chapter 15
Drug Signature Detection Based on L1000 Genomic and Proteomic Big Data
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Chapter 16
Drug Effect Prediction by Integrating L1000 Genomic and Proteomic Big Data
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Chapter 17
A Bayesian Network Approach to Disease Subtype Discovery
Overall attention for this book and its chapters
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Book overview
1. Miniaturized Checkerboard Assays to Measure Antibiotic Interactions
2. High-Throughput Screening for Drug Combinations
3. Post-processing of Large Bioactivity Data
4. How to Develop a Drug Target Ontology: KNowledge Acquisition and Representation Methodology (KNARM)
5. A Guide to Dictionary-Based Text Mining
6. Leveraging Big Data to Transform Drug Discovery
7. How to Prepare a Compound Collection Prior to Virtual Screening
8. Building a Quantitative Structure-Property Relationship (QSPR) Model
9. Isomeric and Conformational Analysis of Small Drug and Drug-Like Molecules by Ion Mobility-Mass Spectrometry (IM-MS)
10. A Computational Platform and Guide for Acceleration of Novel Medicines and Personalized Medicine
11. Omics Data Integration and Analysis for Systems Pharmacology
12. Bioinformatics-Based Tools and Software in Clinical Research: A New Emerging Area
13. Text Mining for Drug Discovery
14. Big Data Cohort Extraction for Personalized Statin Treatment and Machine Learning
15. Drug Signature Detection Based on L1000 Genomic and Proteomic Big Data
16. Drug Effect Prediction by Integrating L1000 Genomic and Proteomic Big Data
17. A Bayesian Network Approach to Disease Subtype Discovery
Summary
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MSU Pharmacology & Toxicology,
12 Mar 2019
Leveraging Big Data to Transform Drug…