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The authors address the issue of providing highly representative descriptions in automated functional annotations. For an uncharacterized sequence, a common strategy is to infer such annotations from those of well-characterized sequences that contain its homologues. However, under many circumstances, this strategy fails to produce meaningful annotations.(More)
We address the issue of providing highly informative and comprehensive annotations using information revealed by the structured vocabularies of gene ontology (GO). For a target, a set of candidate terms for inferring target properties is collected and form a unique distribution on the GO directed acyclic graph (DAG). We propose a novel ontology-based(More)
We address the issue of providing highly informative annotations using information revealed by the structured vocabularies of Gene Ontology (GO). For a target, a set of candidate terms used to infer the target’s property is collected and forms a unique distribution on the GO directed acyclic graph (DAG). We propose a generic and adaptive algorithm— GOMIT,(More)
Laboratories worldwide are working on EST cDNA library and microarray projects, each project involving hundreds to hundreds of thousands of clones. To support the needs of individual laboratories, an efficient EST sequence management system is needed. Here, we describe BIO101, a centralized approach to laboratory EST sequence management and functional(More)
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