Computing Gene Regulation Researchers take a statistical
glimpse at how gene expression is controlled By David Secko
Eukaryotic gene regulation as a field has matured much
during decades of study, but understanding it on a genome-
wide basis has started in earnest only with the assembly of
genomic data. Identifying genome-wide regulatory motifs is
problematic due to their typically low consensus sequences;
grasping which transcription factors bind to such motifs is
even more difficult, as numerous factors can bind to any one
motif. Nonetheless, with many diseases linked to
malfunctions in transcription factors, and many cellular
processes relying on multitiered transcriptional regulation,
this information is invaluable.
Today, researchers combine powerful statistical techniques
with their belief that the information to regulate every
gene is somewhere in the sequence database; they seek to
flush out common regulatory motifs and examine their roles
in regulating genomes. And better assays provide more
information for such approaches. Beyond understanding
genomic regulation, common motifs may lead to better
modeling. It comes down to "predictive power" says Frank
Pugh, assistant professor at Pennsylvania State University;
soon, sequence alone could accurately predict how a newly
discovered gene is regulated
Read the rest at The Scientist the-the-Open ↗
scientist.com/yr2004/jun/research2_040621.html
Posted by Robert Karl Stonjek.