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Bioinformatics: Players; Problems; and Processes in Computational Biology (Technical Insights)


Description: Research Overview

Over the last few years, as genomes have been sequenced and proteins have been studied with renewed enthusiasm, researchers in the life sciences and pharmaceuticals development have been inundated with massive quantities of data. With the amount of data rapidly approaching a petabyte (over a quadrillion bytes), the question becomes, what do you do with it all once you have it stored in various computers? The answer: use those same computers to manage, retrieve, organize, compare, and integrate the data. In a word: bioinformatics.

With the goal of the new field of proteomics being to study the function and interactions of every protein in every type of cell, good bioinformatics tools have become even more essential. Researchers anticipate that the amount of data generated by these studies will soon exceed the capacity of even the best supercomputers currently available. Thus the task becomes almost like that of constructing a living organism. You need processes (including, software algorithms) that can organize information into coherent, accessible structures. Just as a living cell is more than a simple bag of fluids, proteins, and lipids, the whole of a good informatics system will be greater than the sum of its parts.

Pharmaceutical Applications

Mining the large databases of protein structures and biological activity that have now been accumulated is an increasingly important source of drug leads. Bioinformatics specialists, or computational biochemists, are experts in sophisticated computational algorithms and statistical techniques that help them build, subset, and focus huge libraries of potential lead compounds to produce better drug leads.

High-throughput genomics and proteomics systems generate several types of data, including gene sequence, gene expression, gene polymorphism (different forms of the same gene), and protein structure data, as well as functional data (active sites of enzymes, receptor-binding sites, and others). Combining these data sets will enable researchers to better identify and characterize potential drug targets, disease susceptibility, drug toxicity and efficacy, as well as individual responses to medication.

It has been calculated that bioinformatics will raise the hundreds of targets (human enzymes, receptors, and ion channels) that drug companies now work with by at least an order of magnitude. Sorting out the complicated molecular pathways that lead to disease will be more methodical with bioinformatics. If a big pharma company gets two or three targets that yield marketable drugs from a collaboration, it will be worthwhile.

Bioinformatics Systems

The increasing IT (information technology) infrastructure needs of biotech companies require the following: accessible databases, analytical applications in order to sort and organize the data, middleware that links information from various separate databases, and systems to store and distribute the information to researchers. These systems are described below and in more detail in this report.

Technical Insights Reports

This Technical Insights report separates the good news from the mundane by providing the following:

- A detailed overview of technological advances in development laboratories

- Identification of key companies and developers and estimates of timelines for commercializing technology

- Definitions of key markets and applications

- Reporting on technology drivers as well as obstacles in the way of commercial success
- A detailed list of key contacts in the field, including names, titles, addresses, phone numbers, e-mail addresses, and URLs



Contents: 1 Executive Summary
A. Overview

1 Introduction

2 Scope

2 Introduction
A. Bioinformatics Background

1 Introduction
2 The Birth of Bioinformatics: Too Much Data
3 Now: Still Too Much Data
4 Bioinformatics: What Is It Good For?

5 Pharmaceuticals Applications

6 IT Companies Enter the Fray

3 Technology Synopsis
A. Technology Description

1 Bioinformatics Systems
2 Background: Proteomics; Genomics; and Combinatorial Chemistry

4 Markets Overview
A. Market Analysis

1 Introduction

2 Bioinformatics Markets

3 Other Markets That Will Affect Bioinformatics
4 Case Study: Bioinformatics in Asia

5 Market Dynamics
A. Challenges And Barriers

1 Investors Fall Out of Love

2 Standardization

3 Genes Were Easy--Proteins Are Hard

4 Help Wanted

5 Too Many Bytes

6 From Skills to Skill Sets

7 Error Breeds Error

8 Other Challenges
9 Conclusion: Just Three Things

6 Profiles of Major Players
A. Key Companies and Research Groups, A through M

1 3-D Pharmaceuticals

2 3rd Millennium

3 Asia Pacific Bioinformatics Network

4 Alphagene
5 ArQule Inc.
6 Automated Cell Inc.
7 Cadus Pharmaceutical Corp.

8 California Institute of Technology
9 Caprion Pharmaceuticals Inc.

10 Case Western Reserve University

11 Celera Genomics
12 Cellnomica Inc.
13 Cellomics Inc.

14 Cognia Corporation

15 Cold Spring Harbor Laboratory

16 Compugen

17 Cornell University
18 Cray Inc.

19 CuraGen Corporation

20 Brookhaven National Laboratory
21 Entelos Inc.
22 European Molecular Biology Organization (EMBO)
23 Exelixis Inc.
24 ExonHit Therapeutics Inc.

25 Genaissance Pharmaceuticals Inc

26 Gene Network Sciences

27 GeneData AG

28 Gene Logic
29 GeneFormatics Inc.

30 Genostar Consortium

31 Genzyme Molecular Oncology and Silico Insights
32 Geospiza Inc.
33 Glycominds Inc.

34 Hitachi

35 Hybrigenics

36 University of Idaho
37 Immusol Inc.

38 IBM
39 Incyte Genomics Inc.

40 Inpharmatica Ltd

41 Institute for Systems Biology
42 Integrated Genomics Inc.
43 Interleukin Genetics Inc. and Genome Therapeutics Inc.
44 Interoperable Informatics Infrastructure Consortium (I3C)

45 Kenna Technologies
46 LifeSpan BioSciences Inc.

47 Lion Bioscience

48 Massachusettes Institute of Technology

49 McGill University Launches Centre for Bioinformatics
50 MDL Information Systems Inc.

51 MDS Proteomics
52 Microarray Gene Expression Data Group (MGED)
53 Molecular Mining Corp.
54 Myriad Genetics Inc.
B. Key Companies and Research Groups; N through Z
1 National Resource for Cell Analysis and Modeling (NRCAM); University of Connecticut
2 National Center for Genome Resources (US)
3 National Cancer Institute (US)
4 National Institute of General Medical Sciences (US)
5 NIH's National Center for Biotechnology Information (NCBI)

6 Norwegian Radium Hospital

7 Oak Ridge National Laboratory
8 Oracle Corp.
9 O'Reilly and Electric Genetics: Bioinformatics Technology Conference and Bio-hackathon

10 Pacific Northwest National Laboratory
11 Parabon Computation Inc.

12 Paracel

13 Paradigm Genetics

14 Pharsight Corporation

15 Physiome Sciences
16 Proteome Systems Ltd.

17 Purdue University

18 Rosetta Biosoftware
19 Shanghai Genecore Biotechnologies Co. Ltd.

20 Space Telescope Science Institute
21 Spotfire Inc.
22 Stanford University and Intel Corp.

23 State University of Groningen
24 Structural Bioinformatics Inc.

25 Structural GenomiX
26 TIGR (The Institute for Genomic Research)
27 Tripos Inc.

28 TurboGenomics
29 University of Illinois; Urbana-Champaign

30 University of Pennsylvania

31 University of Washington

32 University of Chicago and Sun Microsystems
33 Uppsala University; Sweden
34 US Dept. of Agriculture (USDA)

35 US Department of Energy
36 National Institutes of Health (NIH)

37 Virginia Bioinformatics Institute and Virginia Tech

38 Visualize Life Sciences Group
39 XTL Biopharmaceuticals Ltd. and Hybrigenics
40 Zygogen LLC and Nutec Sciences Inc.
7 Technical Insights' 2002 Science and Technology Awards
A. Technology Innovation

1 Introduction
2 ZymoGenetics Inc.
B. Technology Leadership

1 Introduction
2 Accelrys Inc.

8 Appendices
A. Patents; Websites; Contacts; Books
1 Appendix A: Recent Patents with Applications in Bioinformatics
2 Appendix B: Useful Websites
3 Appendix C: Contact Information
4 Appendix D: Introductory Books on Bioinformatics






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