Bioinformatics and Computational Biology: Bottlenecks and Options : Market Research Report

Bioinformatics and Computational Biology: Bottlenecks and Options

Published by: CHI Insight Pharma Reports

Published: Jun. 1, 2009 - 134 Pages

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

FIGURES

Figure 1.1. Image of Cells and Connections Within the Neocortex Microcircuitry

Figure 1.2. Stanislaw Ulam at work.

Figure 1.3. The Reverend Thomas Bayes.

Figure 2.1. Image showing a microarray experiment.

Figure 3.1. Mapping of SNPs in an idealized section of a chromosome

Figure 3.2 Outline of the Immune System

Figure 3.3. Genome-wide integrative analysis to identify pathways disrupted in cancer.

Figure 3.4. Genomic changes associated with clonal progression of bladder cancer

TABLES

Table 1.1. Biological Disciplines Using Bioinformatics and Computational Biology Showing Examples of Applications

Table 2.1. Companies Offering Mass Spectrometry Devices and Equipment

Table 2.2. Sample Prep Technology for Mass Spectrometry

Table 2.3. Essential Tools for Bioimaging Technologies

Table 2.4. Major Companies with DNA Sequencing Technologies

Table 2.5. Research Opportunities and Forecast

Table 3.1. Companies Providing Consumer-Oriented DNA Analysis through Databases

Table 3.2. NCBI Databases

Table 3.3. Programs in Systems Biology

Table 3.4. List of Publicly-Available Databases

Table 3.5. Some Companies Pursuing Biomarker Technologies

Table 3.6. Options for High-throughput Screening Assays

Table 3.7. In Silico Systems for Toxicity Prediction

Table 3.8. Some Companies Pursuing In Silico Drug Modeling

Abstract

The interdisciplinary fields of Bioinformatics and Computational Biology are locked in a high stakes race with analytical instrument developers and innovators. The pace and scope of change in many fields of biomedical research rivals what we once associated only with semiconductor devices. This report explores the interlocking challenges facing instrumentation advances, computational demands and our evolving systems biology knowledge. Key challenges presented in this report include:

Instrumentation capable of generating terabytes of raw data daily
Storage requirements for human gene sequences
Need for cross platform data analysis standards
Appropriateness of analysis & modeling applications
Database data quality and annotation protocols

Bioinformatics and Computational Biology: Bottlenecks and Options reviews the state of the art and aims to determine the significant technological and market trends in the application of informatics and computation techniques to biological research and drug discovery. The progress of molecular biology has given us a profound understanding of human physiology and pathology at a molecular level. However, we understand that a functioning organism is more than simply a sum of chemical reactions. In recent years a concerted effort has been directed at moving from a reductionist approach to understanding physiology in an integrative systems framework complete with the associated mathematical-based models.

The growth of systems biology has been aided by the availability of constantly evolving computational capacity of cheap hardware as well as advances in analytical research instruments capable in some applications of generating terabytes of data each day. Such instruments are being used to make time series measurements of multiple-analyte fluxes during the perturbation of a physiological system. The robustness of such data are the building blocks for computational biology.

This report describes the tension the combined fields of Bioinformatics and Computational Biology are experiencing by first reviewing the capabilities of innovative analytical instrumentation to generate terabytes of data and then considering the availability of approaches, both in software and hardware, to compress, store, retrieve and combine these data. The report identifies this supply and demand as a strategic bottleneck issue. The discussion also considers issues of cross platform data analysis standards and the appropriate use of analysis and modeling applications on data quality.

Bioinformatics and Computational Biology: Bottlenecks and Options presents an analysis of the state of the field in terms of the current systems biology models and their applications, where the field is headed and the possible implications for applied biological science. The report also includes profiles of systems biology vendors and their products as well as a discussion of the applications in areas such as personalized medicine and drug discovery. The report closes with an overview of the strategy pressure points and the interlocking challenges inherent with instrumentation advances, computational demands and our evolving systems biology knowledge.

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Bioinformatics and Computational Biology: Bottlenecks and Options

Table of Contents

Abstract