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eBLOCKS


NAR Molecular Biology Database Collection entry number 666
Su Q., Lu L., Saxonov S. and Brutlag D.L.
Department of Biochemistry, Stanford University, Stanford, CA 94305-5307

Database Description

Classifying proteins into families and super-families allows identification of functionally mportant conserved domains. The motifs and scoring matrices derived from such conserved regions provide computational tools to recognize similar patterns in novel sequences, and thus enable protein function prediction for genomes. The eBLOCKs database enumerates a cascade of protein blocks with varied conservation levels for each functional domain. A biologically important region is most stringently conserved among a smaller family of highly similar proteins. The same region is often found in a larger group of more remotely related proteins with a reduced stringency. Through enumeration, highly specific signatures can be generated from blocks with more columns and fewer family members, while highly sensitive signatures can be derived from blocks with fewer columns and more members as in a super-family. By applying PSI-BLAST and a modified K-means clustering algorithm, eBLOCKs automatically groups protein sequences according to different levels of similarity. Multiple sequence alignments are made and trimmed into a series of ungapped blocks. Motifs and position specific scoring matrices were derived from eBLOCKs and made available for sequence search and annotation. The eBLOCKs database provides a tool for high throughput genome annotation with maximal specificity and sensitivity.

The eBLOCKs database is freely available on the World Wide Web at http://motif.stanford.edu/eblocks/ to all users for on-line usage. Academic and not for profit institutions wishing copies of the program should contact Douglas L. Brutlag (brutlag@stanford.edu) or Jacqueline Tay (jacqueline.tay@stanford.edu; http://otl.stanford.edu/)


Go to the abstract in the NAR 2005 Database Issue.
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