Computational Methods in Genome Research

1. Front Matter

   Pages i-viii

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2. Can Computational Science Keep up with Evolving Technology for Genome Mapping and Sequencing?

   • Charles R. Cantor

   Pages 1-18

3. Informatics and Experiments for the Human Genome Project

   • Hans Lehrach, Richard Mott, Günther Zehetner

   Pages 19-24

4. Data Management Tools for Scientific Applications: Framework, Status, and Genomic Applications

   • Victor M. Markowitz

   Pages 25-44

5. The ACEDB Genome Database

   • Richard Durbin, Jean Thierry-Mieg

   Pages 45-55

6. The Integrated Genomic Database (IGD)

   • Otto Ritter

   Pages 57-73

7. Genetic Mapping, an Overview

   • Jacques S. Beckmann

   Pages 75-84

8. Representing Genomic Maps in a Relational Database

   • Robert J. Robbins

   Pages 85-96

9. Livermore’s Pragmatic Approach to Integrated Mapping for Chromosome 19

   • Tom Slezak, Mark Wagner, Mimi Yeh, Roy Cantu III, Elbert Branscomb

   Pages 97-110

10. Searching Protein Sequence Databases — Is Optimal Best?

    • William R. Pearson

    Pages 111-120

11. Algorithmic Advances for Searching Biosequence Databases

    • Eugene W. Myers

    Pages 121-135

12. Pattern Recognition in Genomic and Protein Sequences: A Survey of Statistical Validation Problems

    • Jens G. Reich

    Pages 137-152

13. New Algorithms for the Computation of Evolutionary Phylogenetic Trees

    • Gaston H. Gonnet

    Pages 153-161

14. Modelling Protein Structure from Remote Sequence Similarity: An Approach to Tertiary Structure Prediction

    • William R. Taylor

    Pages 163-171

15. Genetic Algorithms in Protein Structure Prediction

    • Frank Herrmann, Sándor Suhai

    Pages 173-190

16. Applications of Artificial Neural Networks in Genome Research

    • M. Reczko, S. Suhai

    Pages 191-208

17. Statistical Models of Chromosome Evolution

    • M. J. Bishop, J. H. Edwards, J. L. Dicks

    Pages 209-216

18. Deciphering the Genetic Message: Some Thoughts on Present Limits

    • C. Frontali

    Pages 217-218

19. Back Matter

    Pages 219-227

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The application of computational methods to solve scientific and pratical problems in genome research created a new interdisciplinary area that transcends boundaries traditionally separating genetics, biology, mathematics, physics, and computer science. Computers have been, of course, intensively used for many year~ in the field of life sciences, even before genome research started, to store and analyze DNA or proteins sequences, to explore and model the three-dimensional structure, the dynamics and the function of biopolymers, to compute genetic linkage or evolutionary processes etc. The rapid development of new molecular and genetic technologies, combined with ambitious goals to explore the structure and function of genomes of higher organisms, has generated, however, not only a huge and burgeoning body of data but also a new class of scientific questions. The nature and complexity of these questions will require, beyond establishing a new kind of alliance between experimental and theoretical disciplines, also the development of new generations both in computer software and hardware technologies, respectively. New theoretical procedures, combined with powerful computational facilities, will substantially extend the horizon of problems that genome research can ·attack with success. Many of us still feel that computational models rationalizing experimental findings in genome research fulfil their promises more slowly than desired. There also is an uncertainity concerning the real position of a 'theoretical genome research' in the network of established disciplines integrating their efforts in this field.

• Chromosom
• DNA
• chromosome
• databases
• development
• evolution
• genetics
• genome mapping
• polymer
• protein
• proteins

• German Cancer Research Centre, Heidelberg, Germany

  Sándor Suhai

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