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Seq2Ref: a web server to facilitate functional interpretation

Wenlin Li2, Qian Cong2, Lisa N Kinch1 and Nick V Grishin12*

Author Affiliations

1 Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9050, USA

2 Department of Biochemistry and Department of Biophysics, University of Texas Southwestern Medical Center, Dallas, Texas 75390-9050, USA

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BMC Bioinformatics 2013, 14:30  doi:10.1186/1471-2105-14-30

Published: 28 January 2013



The size of the protein sequence database has been exponentially increasing due to advances in genome sequencing. However, experimentally characterized proteins only constitute a small portion of the database, such that the majority of sequences have been annotated by computational approaches. Current automatic annotation pipelines inevitably introduce errors, making the annotations unreliable. Instead of such error-prone automatic annotations, functional interpretation should rely on annotations of ‘reference proteins’ that have been experimentally characterized or manually curated.


The Seq2Ref server uses BLAST to detect proteins homologous to a query sequence and identifies the reference proteins among them. Seq2Ref then reports publications with experimental characterizations of the identified reference proteins that might be relevant to the query. Furthermore, a plurality-based rating system is developed to evaluate the homologous relationships and rank the reference proteins by their relevance to the query.


The reference proteins detected by our server will lend insight into proteins of unknown function and provide extensive information to develop in-depth understanding of uncharacterized proteins. Seq2Ref is available at: webcite.

Web server; Functional interpretation; Sequence homology; Reference protein; PubMed literature