Bioinformatics and Computational Biology: Bottlenecks and Options

Published by	Insight Pharma Reports
Published	June, 2009	Product code	90942
Content info	134 pages
Price	US $ 3195 PDF by E-mail ( Single User License) US $ 3995 PDF by E-mail (Single Site License) US $ 9950 PDF by E-mail ( Multi User License)

Introduction
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Bioinformatics and Computational Biology: Bottlenecks and Options published by Insight Pharma Reports in June, 2009. This report consists of 134 pages and the price starts from US $ 3195.

Introduction

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.

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