Automated extraction and semantic analysis of mutation impacts from the biomedical literature.

ABSTRACT:

Background

Mutations as sources of evolution have long been the focus of attention in the biomedical literature. Accessing the mutational information and their impacts on protein properties facilitates research in various domains, such as enzymology and pharmacology. However, manually curating the rich and fast growing repository of biomedical literature is expensive and time-consuming. As a solution, text mining approaches have increasingly been deployed in the biomedical domain. While the detection of single-point mutations is well covered by existing systems, challenges still exist in grounding impacts to their respective mutations and recognizing the affected protein properties, in particular kinetic and stability properties together with physical quantities.

Results

We

SUBMITTER: Naderi N 

PROVIDER: S-EPMC3395893 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature