Discovering context-specific relationships from biological literature by using multi-level context terms.

ABSTRACT:

Background

The Swanson's ABC model is powerful to infer hidden relationships buried in biological literature. However, the model is inadequate to infer relations with context information. In addition, the model generates a very large amount of candidates from biological text, and it is a semi-automatic, labor-intensive technique requiring human expert's manual input. To tackle these problems, we incorporate context terms to infer relations between AB interactions and BC interactions.

Methods

We propose 3 steps to discover meaningful hidden relationships between drugs and diseases: 1) multi-level (gene, drug, disease, symptom) entity recognition, 2) interaction extraction (drug-gene, gene-disease) from literature, 3) context vector based similarity score calculation. Subseque

SUBMITTER: Lee S 

PROVIDER: S-EPMC3339396 | biostudies-literature | 2012 Apr

REPOSITORIES: biostudies-literature