Literature DB >> 30715220

PMC text mining subset in BioC: about three million full-text articles and growing.

Donald C Comeau1, Chih-Hsuan Wei1, Rezarta Islamaj Doğan1, Zhiyong Lu1.   

Abstract

MOTIVATION: Interest in text mining full-text biomedical research articles is growing. To facilitate automated processing of nearly 3 million full-text articles (in PubMed Central® Open Access and Author Manuscript subsets) and to improve interoperability, we convert these articles to BioC, a community-driven simple data structure in either XML or JavaScript Object Notation format for conveniently sharing text and annotations.
RESULTS: The resultant articles can be downloaded via both File Transfer Protocol for bulk access and a Web API for updates or a more focused collection. Since the availability of the Web API in 2017, our BioC collection has been widely used by the research community.
AVAILABILITY AND IMPLEMENTATION: https://www.ncbi.nlm.nih.gov/research/bionlp/APIs/BioC-PMC/. © Published by Oxford University Press 2019. This work is written by a US Government employee and is in the public domain in the US.

Mesh：

Year:  2019        PMID： 30715220      PMCID： PMC6748740          DOI： 10.1093/bioinformatics/btz070

Source DB:  PubMed          Journal:  Bioinformatics        ISSN： 1367-4803            Impact factor:   6.937


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