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NLProt: extracting protein names and sequences from papers.

Sven Mika·Burkhard Rost
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Abstract

Automatically extracting protein names from the literature and linking these names to the associated entries in sequence databases is becoming increasingly important for annotating biological databases. NLProt is a novel system that combines dictionary- and rule-based filtering with several support vector machines (SVMs) to tag protein names in PubMed abstracts. When considering partially tagged names as errors, NLProt still reached a precision of 75% at a recall of 76%. By many criteria our system outperformed other tagging methods significantly; in particular, it proved very reliable even for novel names. Names encountered particularly frequently in Drosophila, such as white, wing and bizarre, constitute an obvious limitation of NLProt. Our method is available both as an Internet server and as a program for download (http://cubic.bioc.columbia.edu/services/NLProt/). Input can be PubMed/MEDLINE identifiers, authors, titles and journals, as well as collections of abstracts, or entire papers.

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AlgorithmsAmino Acid SequenceArtificial IntelligenceDatabases, ProteinInternetPubMedPublicationsSoftwareTerminology as TopicUser-Computer InterfaceJournal Article

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BibTeXRIS

Sven Mika, Burkhard Rost. 2004-07-01. NLProt: extracting protein names and sequences from papers.. https://doi.org/10.1093/nar%2Fgkh427

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