Algorithms on strings, trees, and sequences: computer science and computational biology
Algorithms on strings, trees, and sequences: computer science and computational biology
Motif discovery without alignment or enumeration (extended abstract)
RECOMB '98 Proceedings of the second annual international conference on Computational molecular biology
Sequence homology detection through large scale pattern discovery
RECOMB '99 Proceedings of the third annual international conference on Computational molecular biology
Protein remote homology detection based on auto-cross covariance transformation
Computers in Biology and Medicine
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We describe DELPHI, a new computational tool for identifying sequence similarity between a query sequence and a database of proteins. Use is made of a set of patterns obtained from the underlying database through a one-time computation. The patterns are subsequently matched against every query sequence presented to the system. A pattern matched by a region of the query pinpoints a potential local similarity between that region and all of the database sequences also matching that pattern. In a final step, all such local similarities are examined more closely by aligning and scoring the corresponding query and database regions. By prudently choosing a set of patterns, the method can be used to discover weak but biologically important similarities. We provide a number of examples using both classified and unclassified proteins that corroborate this claim.