Author: K. John Morrow, Jr., PhD
Chapter One
INTRODUCTION TO BIOINFORMATICS AND COMPUTATIONAL BIOLOGY
1.1. Definitions; Principle and Applications
What are Bioinformatics and Computational Biology?
What Is an Algorithm?
Heuristics
Approximation Algorithms for Parsimony Models
Neural Networks
Markov Chains
B&CB Application of Markov Chain Modeling
B&CB Application of Markov Chain Modeling to Timing of Antiretroviral Therapy
Markov Chain Monte Carlo Algorithms
1.2. Scope of the Fields
Overview of Presently Available Software Tools
Managing Terabytes of Data
1.3. Product Categories
Content Databases
Data Mining
Analytical Software and Services
1.4. Subsequent Chapters
Chapter Two
TEAMING BIOINFORMATICS AND POWERFUL HARDWARE
2.1. Biomedical Imagery Hardware
Computerized Axial Tomography
Magnetic Resonance Imaging
Positron Emission Tomography
Ultrasonography
2.2. Mass Spectrometry
Theoretical Basis
Bioinformatics Applications
Sample Preparation for Mass Spectrometry
2.3. X-ray Crystallography
2.4. High-throughput Image Analysis
2.5. Sequencing
2.6. Microarrays
2.7. The Future of Imaging and B&CB
Chapter Three
OVERVIEW OF BIOINFORMATICS-DRIVEN APPLICATIONS
3.1. Genes, Genomes and Genomics
3.2. The Human Genome
DNA Sequence Analysis
Alignment
Databases
3.3. Disease Determination
Alzheimer’s Disease
Other Genomes
Comparative Genomics
3.4. Gene Regulation
The Proteome and Proteomics
Protein Structure Alignment
Protein Structure Prediction
Protein-Protein Interactions
Clustering Algorithms
The Future of the Proteome
3.5. Systems Biology
3.6. Biomedical Informatics
Infectious Diseases and B&CB
Epidemiology
Institutional Support for Infectious Disease B&CB
Population Dynamics of Drug Resistance
Immunoinformatics
3.7. The Nature of Cancer and the Contributions of B&CB to its Elucidation
Analysis of Mutations in Cancer
Cancer Biomarkers
Analysis of Bladder Cancer
3.8. Pharma Investigations
Cheminformatics
Drug Discovery
New Uses for Existing Drugs
Chiral Pharmaceuticals
Natural Products as New Therapeutics
In Silico Drug Development
In Silico Prediction Tools
Online Drug Resources
Pharmacogenomics
3.9. Forensic Investigations
Chapter Four
THE DILEMMA AHEAD FOR BIOINFORMATICS
4.1. Data Proliferation: The Good News and Challenges
4.2. Some Storage Solutions
4.3. Product and Market Implications
4.4. Personalized Medicine
Single-Gene Mutations and the Concept of Personalized Medicine
Box 4.1. A company based on a paradigm of personalized medicine
Genetic Determination by Multiple Factors and the Development of Personalized Medicine
4.5. Are GRID Networks the Answer?
Chapter Five
INTERVIEWS WITH BIOINFORMATICS SPECIALISTS
5.1. Interview with Tim Riley of Waters Corporation
5.2. Interview with Nasri G. Nahas, Chief Executive Officer, Geneva Bioinformatics (GeneBio) S.A.
5.3. Interview with Ruedi Aebersold, Chairman, Scientific Executive Board, SystemsX.ch Project, Zurich Switzerland
5.4. Interview with John Pestian, PhD, MBA, Director, Computational Medicine Center, Cincinnati Children’s Medical Center and the University of Cincinnati
5.5. Interview with Kevin Davies, Editor in Chief, BioIT World
Chapter Six
CONCLUSIONS
6.1. B&CB Progress is Driven by Hardware Improvements
6.2. Old, Simplistic Models of Biomedicine Needs to be Critically Reexamined
6.3. Why Has So Little Progress been Made on the “War on Cancer”?
6.4. Toward a Cancer Program Based on B&CB
6.5. The Limitations of In Silico Pharmacology
6.6. The Limitations of B&CB
References
Company Index with Web Addresses