A New Approach For Identifying Regulatory Motifs in Groups of Co-regulated Genes

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Dartmouth College is given an award for further development of the BEAM software under the direction of Dr. Robert Gross. BEAM (Beam-search Enumerative Algorithm for Motif finding) is a new kind of motif finding program that is simple to use, accurate, and very robust to noisy data. It does not require the user to input any information other than a list of genes, yet BEAM outperforms other programs in finding non-degenerate candidate regulatory motifs. BEAM is a pattern-driven program that employs a pruned search strategy. This results in a reduction of the search space by several orders of magnitude compared to a complete enumeration of all possible motifs. A search tree that focuses only on the highest scoring submotifs at every motif length is likely to identify the biologically relevant motifs. The highly efficient approach allows BEAM to utilize computationally demanding objective functions in addition to the standard over-representation. The research in this award is aimed at expanding BEAM into a suite of programs that can find additional types of regulatory motifs - those containing ambiguous characters as well as bipartite motifs. In addition, we will develop an approach that allows us to look for combinations of motifs that might function together. The entire suite of programs will be made available through an integrated front end. An important part of the Dartmouth environment is the involvement of undergraduates in research. Three of the key people involved in developing our initial approach and in developing the BEAM algorithm are undergraduates. These students function in the lab as would graduate students, participating in journal clubs, seminars, and lab meetings. The BEAM source code will be shared freely over the web once we have papers accepted and have completed the documentation of the code. This will be done under the standard GNU license. As of now, the Java code runs on Mac, Windows, and Unix systems.