The EMOTIF database

Highly specific protein sequence motifs for genome analysis.

We present a method for discovering conserved sequence motifs from families of aligned protein sequences. The method has been implemented as a computer program called EMOTIF (http://motif. stanford.edu/emotif). Given an aligned set of protein sequences, EMOTIF generates a set of motifs with a wide range of specificities and sensitivities. EMOTIF also can generate motifs that describe possible s...

CONSTRUCTION OF A DATABASE OF CO -OCCURRING eMOTIFS BASED ON CONDITIONAL PROBABILITIES

Classification of a newly discovered protein into a family of proteins enables the determination of its function. The eMOTIF system identifies conserved modular domains that confer functionality or structure to proteins and allows classification of proteins into families based on the conserved domains a protein contains. A program called multeeMOTIF has been developed which analyzes eMOTIFS and...

eMOTIF Maker: Nodally Awesome: Comparing Results of eMOTIF Maker with Neighbor-Joining Trees

Saccharomyces Genome Database (SGD) provides biochemical and structural information for budding yeast proteins

The Saccharomyces Genome Database (SGD: http://genome-www.stanford.edu/Saccharomyces/) has recently developed new resources to provide more complete information about proteins from the budding yeast Saccharomyces cerevisiae. The PDB Homologs page provides structural information from the Protein Data Bank (PDB) about yeast proteins and/or their homologs. SGD has also created a resource that util...

Sequence-Structure Patterns: Discovery and Applications

Protein sequence data is being generated at a tremendous rate; however, functional annotation of these proteins is proceeding at a much slower pace. Biologists rely on computational biology and pattern recognition to predict the functionality of proteins. This is based on the fact that proteins that share a similar function often exhibit conserved sequence patterns. Such sequence patterns, or m...