PubMedPortable: A Framework for Supporting the Development of Text Mining Applications.

ABSTRACT: Information extraction from biomedical literature is continuously growing in scope and importance. Many tools exist that perform named entity recognition, e.g. of proteins, chemical compounds, and diseases. Furthermore, several approaches deal with the extraction of relations between identified entities. The BioCreative community supports these developments with yearly open challenges, which led to a standardised XML text annotation format called BioC. PubMed provides access to the largest open biomedical literature repository, but there is no unified way of connecting its data to natural language processing tools. Therefore, an appropriate data environment is needed as a basis to combine different software solutions and to develop customised text mining applications. PubMedPortable builds

SUBMITTER: Doring K 

PROVIDER: S-EPMC5051953 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature