Biology Reference
In-Depth Information
et al
.
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), is not applicable to humans, and can be more challenging to
treat automatically than other transcriptome data types.
86,88
Briefly, the basic approach chosen in Bgee is to recode expression
data for a gene in an organ and developmental stage as “not detected”,
“expressed with high confidence”, or “expressed with low confidence”.
For experiments based on tag counting, such as ESTs, SAGE, or MPSS,
we have considered a gene as expressed with a high confidence if the
95% confidence interval does not include zero.
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For microarray data, a
gene is considered expressed if the normalized signal is significantly
above the background signal.
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In the future, we plan to add informa-
tion on whether a gene is significantly more expressed in one condition
than another (e.g. more expressed in muscle than brain), and integrate
other types of data.
The database is developed with MySQL, and currently includes four
vertebrate species. The website allows users to retrieve information on
gene expression by querying the database for keywords or gene identi-
fiers, or browsing anatomical or developmental ontologies. In addition
to species-specific or gene-specific views, users may view all gene fami-
lies expressed in homologous organs between chosen species, and the
complete expression information of a gene family across species. All
queries may be constrained by data type, data quality, and keywords or
identifiers.
Bgee is a promising tool to enable evo-devo studies on a larger scale.
We hope that it will also be useful to put functional genomics studies in
a comparative context, and provide a platform for integration of anatom-
ical homology information into bioinformatics.
4. Conclusion
The intersection of bioinformatics and evo-devo is still relatively small,
but holds a large potential for bringing the tools of high-throughput
biology to illuminate our understanding of some of the most fundamen-
tal questions in biology: the origin of novelty, the role of constraints, the
importance of loss vs. gain, and the extent of conservation between
distant taxa. In this chapter, we have discussed briefly two aspects of the
integration of bioinformatics and evo-devo: sequence-based analysis,
