BioC: a minimalist approach to interoperability for biomedical text processing

TitleBioC: a minimalist approach to interoperability for biomedical text processing
Publication TypeJournal Article
Year of Publication2013
AuthorsComeau DC, Doğan RIslamaj, Ciccarese P, Cohen KBretonnel, Krallinger M, Leitner F, Lu Z, Peng Y, Rinaldi F, Torii M, Valencia A, Verspoor K, Wiegers TC, Wu CH, W Wilbur J
JournalDatabase (Oxford)
Volume2013
Paginationbat064
Date Published2013
ISSN1758-0463
KeywordsBiomedical Research, Data Mining, Humans, Natural Language Processing, Software
Abstract

A vast amount of scientific information is encoded in natural language text, and the quantity of such text has become so great that it is no longer economically feasible to have a human as the first step in the search process. Natural language processing and text mining tools have become essential to facilitate the search for and extraction of information from text. This has led to vigorous research efforts to create useful tools and to create humanly labeled text corpora, which can be used to improve such tools. To encourage combining these efforts into larger, more powerful and more capable systems, a common interchange format to represent, store and exchange the data in a simple manner between different language processing systems and text mining tools is highly desirable. Here we propose a simple extensible mark-up language format to share text documents and annotations. The proposed annotation approach allows a large number of different annotations to be represented including sentences, tokens, parts of speech, named entities such as genes or diseases and relationships between named entities. In addition, we provide simple code to hold this data, read it from and write it back to extensible mark-up language files and perform some sample processing. We also describe completed as well as ongoing work to apply the approach in several directions. Code and data are available at http://bioc.sourceforge.net/. Database URL: http://bioc.sourceforge.net/

DOI10.1093/database/bat064
Alternate JournalDatabase (Oxford)
PubMed ID24048470
PubMed Central IDPMC3889917
Grant List5R01 LM008111-08 / LM / NLM NIH HHS / United States
5R01 LM009254-07 / LM / NLM NIH HHS / United States
G08LM010720 / LM / NLM NIH HHS / United States
/ / Intramural NIH HHS / United States