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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.
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."
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.
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.
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