The algorithm interrogates a motif search space (composed of combinations of small stem-loop structures and specific sequence information) for how well their occurrences in mRNA sequences predict corresponding measurements of mRNA levels from functional genomics experiments. StructRED then builds a linear model of several stem-loop motifs that significantly explain mRNA levels in the input data set. Inputs to StructRED are a fasta sequence file and one or more columns of numerical mRNA level data in tab-delimited text files.
Some advantages of this method are that it:
Detects cis-regulatory elements that are defined by both nucleotide sequence and RNA secondary structure
Requires no thresholding of microarray data
Does not require a "positive" or "negative" sequence set
PDF reprint of the paper:
"Discovering structural cis-regulatory elements by modeling the behaviors of mRNAs"
and "Supplementary Material".
Barrett Foat and Gary D. Stormo
Discovering structural cis-regulatory elements by modeling the behaviors of mRNAs
Mol. Syst. Biol. 2009. 5:268.
Please send bug reports, questions, and comments to Barrett Foat (barrett AT wustl.edu) and Gary Stormo (stormo AT genetics.wustl.edu).
Source code for the latest version: StructRED
Last updated June
2, 2009. Thanks to Xing Xu for the website template.