"Frontmatter". In: Plant Genomics and Proteomics

W
EB
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ESOURCES
http://www.maizemap.org/iMapDB/iMap.html
http://hbz7.tamu.edu/homelinks/phymap/soybean/soytool_4.htm
http://wheat.pw.usda.gov/NSF/
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CHAPTER
9
B
I O I N F O R M AT I C S
O
VERVIEW
Bioinformatics covers the whole range of activities from the documentation
of the genomics and associated data, to its storage and analysis, and its final
dissemination. The importance of bioinformatics is a consequence of the gen-
eration of very large amounts of data being produced by the genomics rev-
olution. Coping with these data has turned into one of the major activities
for all genomic projects. In general, the advances in data gathering, storage,
and distribution technologies have far outpaced computational advances in
techniques for analyzing and understanding data.
Experimental approaches are designed to discover genes and their func-
tions by combining genomic sequences, ESTs, proteomics, genetics, and
reverse genetics. Biological functions also must be assayed to understand
genotype/phenotype correlations, and these observations must be con-
nected to all the genomics data. A frequent additional consideration is that
many genomics projects involve more than a single institution and therefore
require the frequent interchange of the raw data between the various
members involved in the project. The volume and complexity of all of these
data generally require an organized information management system to
enter, maintain, and analyze this data, so that the cycle from experiment, to
analysis, to prediction, to the experimental testing of any new insights is effi-
ciently managed. 
The components that are involved in the assembly and analysis of all of
these data include:
∑ A database (now necessarily a relational database) to store and cross-
query all the project-generated data at an appropriate level of detail 
Plant Genomics and Proteomics, by Christopher A. Cullis
ISBN 0-471-37314-1 Copyright © 2004 John Wiley & Sons, Inc.
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∑ The software to conduct the data type-specific analyses 
∑ General-purpose multivariate statistics to test the significance of any
tentative conclusions 
Although these components are considered separately here, they are fre-
quently present together, especially in the large public databases where the
data and the analysis tools are available from the same site.