5.8 Gene Expression Databases 119
ing, an XML-encoded file is then built that is entered into the database via an
HTML submission form. The ORDB can be downloaded as an HTML file.
RiboWebsmi-web.stanford.edu/projects/helix/riboweb.html
RiboWeb is a relational database containing a representation of the primary
3D data relevant to the structure of the ribosome of the prokaryotic 30S ribo-
somal subunit, which initiates the translation of messenger RNA (mRNA)
into protein and is the site of action of numerous antibiotics (Chen et al.
1997). The project has since been expanded to include structural data per-
taining to the entire ribosome of prokaryotes (but primarilyEscherichia coli).
The project includes computational modules for constructing and studying
structural models,
5.8 Gene Expression Databases
Gene expression profiling includes both transcriptomics and proteomics. The
former monitors gene transcription, while the latter monitors gene trans-
lation. Proteomics has more restrictive expressions and post-translational
modifications. In contrast to transcriptomics, which is an “indirect” measure
of gene expression, proteomics provides a more direct measurement of gene
expression and is increasingly important in functional genomics. Thus, gene
expression databases contain both transcriptomics databases and proteomics
databases.
5.8.1 Transcriptomics Databases
It is useful to study the temporal and spatial patterns of gene expression.
Transcriptomicsis defined as the use of quantitative mRNA measurements
of gene expression to characterize biological processes and elucidate gene
transcription mechanisms. Thus, the goal of gene expression experiments
is to quantify mRNA expression, particularly under certain conditions (e.g.,
drug intervention) or in a disease state. Differential gene expression mea-
surements are performed using a number of high-throughput techniques
such as (1) expression sequence tags (ESTs), (2) DNA microarrays (includ-
ing oligonucleotide microarrays and spotted microarrays), (3) subtractive
cloning, (4) differential display, and (5) serial analysis of gene expression
(SAGE). Gene expression experiments have as their goal the identification of
novel disease genes, drug targets, and coregulated gene groups. Transcrip-
tomics databases provide integrated data management and analysis systems
