BioC: a minimalist approach to interoperability for biomedical text processing

DSpace/Manakin Repository

BioC: a minimalist approach to interoperability for biomedical text processing

Citable link to this page

 

 
Title: BioC: a minimalist approach to interoperability for biomedical text processing
Author: Comeau, Donald C.; Islamaj Doğan, Rezarta; Ciccarese, Paolo; Cohen, Kevin Bretonnel; Krallinger, Martin; Leitner, Florian; Lu, Zhiyong; Peng, Yifan; Rinaldi, Fabio; Torii, Manabu; Valencia, Alfonso; Verspoor, Karin; Wiegers, Thomas C.; Wu, Cathy H.; Wilbur, W. John

Note: Order does not necessarily reflect citation order of authors.

Citation: Comeau, D. C., R. Islamaj Doğan, P. Ciccarese, K. B. Cohen, M. Krallinger, F. Leitner, Z. Lu, et al. 2013. “BioC: a minimalist approach to interoperability for biomedical text processing.” Database: The Journal of Biological Databases and Curation 2013 (1): bat064. doi:10.1093/database/bat064. http://dx.doi.org/10.1093/database/bat064.
Full Text & Related Files:
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/
Published Version: doi:10.1093/database/bat064
Other Sources: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3889917/pdf/
Terms of Use: This article is made available under the terms and conditions applicable to Other Posted Material, as set forth at http://nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of-use#LAA
Citable link to this page: http://nrs.harvard.edu/urn-3:HUL.InstRepos:11879601
Downloads of this work:

Show full Dublin Core record

This item appears in the following Collection(s)

 
 

Search DASH


Advanced Search
 
 

Submitters