Background: The size of the protein sequence database has been exponentially increasing due to advances in\r\ngenome sequencing. However, experimentally characterized proteins only constitute a small portion of the\r\ndatabase, such that the majority of sequences have been annotated by computational approaches. Current\r\nautomatic annotation pipelines inevitably introduce errors, making the annotations unreliable. Instead of such\r\nerror-prone automatic annotations, functional interpretation should rely on annotations of ââ?¬Ë?reference proteinsââ?¬â?¢ that\r\nhave been experimentally characterized or manually curated.\r\nResults: The Seq2Ref server uses BLAST to detect proteins homologous to a query sequence and identifies the\r\nreference proteins among them. Seq2Ref then reports publications with experimental characterizations of the\r\nidentified reference proteins that might be relevant to the query. Furthermore, a plurality-based rating system is\r\ndeveloped to evaluate the homologous relationships and rank the reference proteins by their relevance to the query.\r\nConclusions: The reference proteins detected by our server will lend insight into proteins of unknown function and\r\nprovide extensive information to develop in-depth understanding of uncharacterized proteins. Seq2Ref is available at:\r\nhttp://prodata.swmed.edu/seq2ref.
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