Computational methods for transcriptional regulation.
How is the information from a thousand gene-expression arrays, the location of more than two hundred regulatory factors, and nine sequenced genomes to be integrated into a global view of the regulatory network in budding yeast? Computational methods that fit incomplete noisy data provide the outlines of regulatory pathways, but the errors are not quantified. In the fly, embryonic patterning has proved amenable to computational prediction, but only when the DNA-binding preferences of the relevant factors are taken into account. In both these model organisms, simply restricting attention to regulatory sequences that align with related species (i.e. "conserved") discards much information regarding what is functional.
Siggia
Eric D
ED
Center for Studies in Physics and Biology, The Rockefeller University, 1230 York Avenue, New York, NY 10021, USA. siggiae@rockefeller.edu
D000818:Animals; D001665:Binding Sites; D019295:Computational Biology; D004247:DNA / Q000378:metabolism; D004175:Diptera / Q000235:genetics*; D005786:Gene Expression Regulation; D020411:Oligonucleotide Array Sequence Analysis; D014158:Transcription, Genetic; D015003:Yeasts / Q000235:genetics*
D004247:DNA