Can Computational Science Keep Up with Evolving Technology for Genome Mapping and Sequencing? (C.R. Cantor). Informatics and Experiments for the Human Genome Project (H. Lehrach et al.). Date Management Tools for Scientific Applications (V.M. Markowitz). The ACEDB Genome Database (R. Durbin, UJ. ThierryMieg). The Integrated Genomic Database (O. Ritter). Genetic Mapping (J. Beckmann). Representing Genomic Maps in a Relational Database (R.J. Robbins). Livermore's Pragmatic Approach to Integrated Mapping for Chromosome 19 (T. Slezak et al.). Searching Protein Sequence Databases (W.R. Pearson). Algorithmic Advances for Searching Biosequence Databases (E.W. Myers). Pattern Recognition in Genomic and Protein Sequences (J.G. Reich). New Algorithms for the Computation of Evolutionary Phylogenetic Trees (G.H. Gonnet). Modelling Protein Structure from Remote Sequence Similarity (W.R. Taylor). Genetic Algorithms in Protein Structure Prediction (F. Herrmann, S. Suhai). Statistical Models of Chromosome Evolution (M.J. Bishop). Deciphering the Genetic Message (C. Frontali). Index.

Evaluating the Statistical Significance of Multiple Distinct Local Alignments; S.F. Altscul. Hidden Markov Models for Human Genes: Periodic Patterns in Exon Sequence; S. Brunak. Identification of Muscle-Specific Transcriptional Regulatory Regions; J.W. Fickett. A Systematic Analysis of Gene Functions by the Metabolic Pathway Database; M. Kanehisa. Polymer Dynamics of DNA, Chromatin and Chromosomes; J. Langowski. Is Whole Human Genome Sequencing Feasible?; E.W. Myers. Sequence patterns Diagnostic of Structure and Function; T.F. Smith. Recognizing Functional Domains in Biological Sequences; G.D. Stormo. Stochastic Modelling in Molecular Genetics; P. Tautu. The Integrated Genomic Database (IGD): Enhancing the Productivity of Gene Mapping Projects; S.P. Bryant. Error Analysis of Genetic Linkage Data; R. Cottingham. Managing Accelerating Data Growth in the Genome Database; K.H. Fasman. Advances in Statistical Methods for Linkage Analysis; D.E. Weeks. Exploring Heterogeneous Molecular Biology Databases in the Context of the Object-Protocol Model; V.M. Markowitz. Comprehensive Genome Information Systems; O. Ritter. Visualizing the Genome; D.B. Searls. Data Management for Ligand-Based Drug Design; K. Aberer. 7 Additional Articles. Index.

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."

Genome research will certainly be one of the most important and exciting sci- tific disciplines of the 21st century. Deciphering the structure of the human genome, as well as that of several model organisms, is the key to our understanding how genes fu- tion in health and disease. With the combined development of innovativetools, resources, scientific know-how, and an overall functional genomic strategy, the origins of human and other organisms'geneticdiseases can be traced. Scientificresearch groups and dev- opmental departments of several major pharmaceutical and biotechnological companies are using new, innovative strategies to unravel how genes function, elucidating the gene protein product, understanding how genes interact with others-both in health and in the disease state. Presently, the impact of the applications of genome research on our society in medicine, agriculture and nutrition will be comparable only to that of communication technologies. In fact, computational methods, including networking, have been playing a substantial role even in genomics and proteomics from the beginning. We can observe, however, a fundamental change of the paradigm in life sciences these days: research focused until now mostly on the study of single processes related to a few genes or gene products, but due to technical developments of the last years we can now potentially identify and analyze all genes and gene products of an organism and clarify their role in the network of lifeprocesses.

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.