Extracting chemical reactions from text using Snorkel.

ABSTRACT:

Background

Enzymatic and chemical reactions are key for understanding biological processes in cells. Curated databases of chemical reactions exist but these databases struggle to keep up with the exponential growth of the biomedical literature. Conventional text mining pipelines provide tools to automatically extract entities and relationships from the scientific literature, and partially replace expert curation, but such machine learning frameworks often require a large amount of labeled training data and thus lack scalability for both larger document corpora and new relationship types.

Results

We developed an application of Snorkel, a weakly supervised learning framework, for extracting chemical reaction relationships from biomedical literature abstracts. For this work, we

SUBMITTER: Mallory EK 

PROVIDER: S-EPMC7251675 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature