Chemical–protein interaction extraction via Gaussian probability distribution and external biomedical knowledge | Zendy

Cong Sun | Zendy; Zhihao Yang | Zendy; Leilei Su | Zendy; Lei Wang | Zendy; Yin Zhang | Zendy; Hongfei Lin | Zendy; Jian Wang | Zendy

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Chemical–protein interaction extraction via Gaussian probability distribution and external biomedical knowledge

Author(s) -

Cong Sun,

Zhihao Yang,

Leilei Su,

Lei Wang,

Yin Zhang,

Hongfei Lin,

Jian Wang

Publication year - 2020

Publication title -

bioinformatics

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btaa491

Subject(s) - computer science , softmax function , sequence (biology) , gaussian , artificial intelligence , information extraction , source code , relationship extraction , data mining , sentence , knowledge extraction , machine learning , artificial neural network , physics , quantum mechanics , biology , genetics , operating system

The biomedical literature contains a wealth of chemical-protein interactions (CPIs). Automatically extracting CPIs described in biomedical literature is essential for drug discovery, precision medicine, as well as basic biomedical research. Most existing methods focus only on the sentence sequence to identify these CPIs. However, the local structure of sentences and external biomedical knowledge also contain valuable information. Effective use of such information may improve the performance of CPI extraction.

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