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Evaluation of human-readable annotation in biomolecular sequence databases with biological rule libraries



Evaluation of human-readable annotation in biomolecular sequence databases with biological rule libraries



Bioinformatics 15(7-8): 528-535



Motivation: Computer-based selection of entries from sequence databases with respect to a related functional description, e.g. with respect to a common cellular localization or contributing to the same phenotypic function, is a difficult task. Automatic semantic analysis of annotations is not only hampered by incomplete functional assignments. A major problem is that annotations are written in a rich, non-formalized language and are meant for reading by a human expert. This person can extract from the text considerably more information than is immediately apparent due to his extended biological background knowledge and logical reasoning. Approach: A technique of automated annotation evaluation based on a combination of lexical analysis and the usage of biological rule libraries has been developed. The proposed algorithm generates new functional descriptors from the annotation of a given entry using the semantic units of the annotation as prepositions for implications executed in accordance with the rule library. Results: The prototype of a software system, the MetaA(nnotator) program, is described and the results of its application to sequence attribute assignment and sequence selection problems, such as cellular localization and sequence domain annotation of SWISS-PROT entries, are presented. The current software version assigns useful subcellular localization qualifiers to apprx88% of all SWISS-PROT entries. As shown by demonstrative examples, the combination of sequence and annotation analysis is a powerful approach for the detection of mutual annotation/sequence inconsistencies. Availability: The software is available on request from Frank.Eisenhaber@embl-heidelberg.de. Results for the cellular localization assignment can be viewed at the URL http://www.bork.embl-heidelberg.de/CELLLOC/CELLLOC.html. Contact: Frank.Eisenhaber@EMBL-Heidelberg.DE.

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Accession: 010616236

Download citation: RISBibTeXText

PMID: 10487860

DOI: 10.1093/bioinformatics/15.7.528



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