SEQUENCE MOTIF DISCOVERY & SEARCH

University Of California, San Diego, La Jolla CA

Investigators

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Abstract

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. The MEME/MAST project allows biomedical scientists to model molecular sequences and identify relationships and patterns among them. This aids in understanding the structure and function of genes and proteins in the cell. MEME is a pattern discovery tool, based on statistical learning algorithms, that finds sequence patterns in groups of proteins or genes. These patterns are useful for understanding the important biological features of the sequences. Furthermore, they can be used by the MAST algorithm to identify genes and proteins that share the patterns found by MEME, and are therefore likely to be functionally or evolutionarily related to the original group of sequences. MEME and MAST comprise an extremely powerful method for identifying distant but important relationships among biological molecules.