Theoretical and Computational Methods in Genome Research

1. Front Matter

   Pages i-ix

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2. Evaluating the Statistical Significance of Multiple Distinct Local Alignments

   • Stephen F. Altschul

   Pages 1-14

3. Hidden Markov Models for Human Genes

   • Pierre Baldi, Søren Brunak, Yves Chauvin, Anders Krogh

   Pages 15-32

4. Identification of Muscle-Specific Transcriptional Regulatory Regions

   • James W. Fickett

   Pages 33-39

5. A Systematic Analysis of Gene Functions by the Metabolic Pathway Database

   • Minoru Kanehisa, Susumu Goto

   Pages 41-55

6. Polymer Dynamics of DNA, Chromatin, and Chromosomes

   • Jörg Langowski, Lutz Ehrlich, Markus Hammermann, Christian Münkel, Gero Wedemann

   Pages 57-72

7. Is Whole Human Genome Sequencing Feasible?

   • Eugene W. Myers, James L. Weber

   Pages 73-89

8. Sequence Patterns Diagnostic of Structure and Function

   • Temple F. Smith, R. Mark Adams, Sudeshna Das, Lihua Yu, Loredana Lo Conte, James White

   Pages 91-104

9. Recognizing Functional Domains in Biological Sequences

   • Gary D. Stormo

   Pages 105-116

10. The Integrated Genomic Database (IGD)s

    • Stephen P. Bryant, Anastassia Spiridou, Nigel K. Spurr

    Pages 117-134

11. Error Analysis of Genetic Linkage Data

    • Robert W. Cottingham Jr., Margaret Gelder Ehm, Marek Kimmel

    Pages 135-143

12. Managing Accelerating Data Growth in the Genome Database

    • Kenneth H. Fasman

    Pages 145-151

13. Advances in Statistical Methods for Linkage Analysis

    • Jeffrey R. O’Connell, Daniel E. Weeks

    Pages 153-160

14. Exploring Heterogeneous Molecular Biology Databases in the Context of the Object-Protocol Model

    • Victor M. Markowitz, I-Min A. Chen, Anthony S. Kosky

    Pages 161-176

15. Comprehensive Genome Information Systems

    • Otto Ritter

    Pages 177-184

16. Visualizing the Genome

    • David B. Searls

    Pages 185-204

17. Data Management for Ligand-Based Drug Design

    • Karl Aberer, Klemens Hemm, Manfred Hendlich

    Pages 205-230

18. Picturing the Working Protein

    • Hans Frauenfelder, Peter G. Wolynes

    Pages 231-236

19. HIV-1 Protease and its Inhibitors

    • Maciej Geller, Joanna Trylska, Jan Antosiewicz

    Pages 237-254

20. Density Functional and Neural Network Analysis

    • K. J. Jalkanen, S. Suhai, H. Bohr

    Pages 255-277

The application ofcomputational methods to solve scientific and practical problems in genome research created a new interdisciplinary area that transcends boundaries tradi­ tionally separating genetics, biology, mathematics, physics, and computer science. Com­ puters have, of course, been intensively used in the field of life sciences for many years, even before genome research started, to store and analyze DNA or protein sequences; to explore and model the three-dimensional structure, the dynamics, and the function of biopolymers; to compute genetic linkage or evolutionary processes; and more. The rapid development of new molecular and genetic technologies, combined with ambitious goals to explore the structure and function ofgenomes ofhigher organisms, has generated, how­ ever, not only a huge and exponentially increasing body of data but also a new class of scientific questions. The nature and complexity of these questions will also require, be­ yond establishing a new kind ofalliance between experimental and theoretical disciplines, the development of new generations both in computer software and hardware technolo­ gies. New theoretical procedures, combined with powerful computational facilities, will substantially extend the horizon of problems that genome research can attack with suc­ cess. Many of us still feel that computational models rationalizing experimental findings in genome research fulfill their promises more slowly than desired. There is also an uncer­ tainty concerning the real position of a "theoretical genome research" in the network of established disciplines integrating their efforts in this field.

• DNA
• computational models
• development
• genes
• molecular biology
• protein sequence
• transcription

• German Cancer Research Center, Heidelberg, Germany

  Sándor Suhai

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