Discovering patterns to extract protein–protein interactions from full texts | Zendy

Minlie Huang | Zendy; Xiaoyan Zhu | Zendy; Yu Hao | Zendy; Donald G. Payan | Zendy; Kunbin Qu | Zendy; Ming Li | Zendy

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Discovering patterns to extract protein–protein interactions from full texts

Author(s) -

Minlie Huang,

Xiaoyan Zhu,

Yu Hao,

Donald G. Payan,

Kunbin Qu,

Ming Li

Publication year - 2004

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/bth451

Subject(s) - computer science , recall rate , scientific literature , matching (statistics) , information retrieval , natural language processing , artificial intelligence , data mining , biology , statistics , mathematics , paleontology

Although there are several databases storing protein-protein interactions, most such data still exist only in the scientific literature. They are scattered in scientific literature written in natural languages, defying data mining efforts. Much time and labor have to be spent on extracting protein pathways from literature. Our aim is to develop a robust and powerful methodology to mine protein-protein interactions from biomedical texts.

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