RelEx—Relation extraction using dependency parse trees | Zendy

Katrin Fundel | Zendy; Robert Küffner | Zendy; Ralf Zimmer | Zendy

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RelEx—Relation extraction using dependency parse trees

Author(s) -

Katrin Fundel,

Robert Küffner,

Ralf Zimmer

Publication year - 2006

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btl616

Subject(s) - preprocessor , relationship extraction , relation (database) , computer science , dependency (uml) , parsing , biomedical text mining , set (abstract data type) , information extraction , information retrieval , artificial intelligence , natural language processing , data mining , text mining , programming language

The discovery of regulatory pathways, signal cascades, metabolic processes or disease models requires knowledge on individual relations like e.g. physical or regulatory interactions between genes and proteins. Most interactions mentioned in the free text of biomedical publications are not yet contained in structured databases.

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