TY - JOUR
T1 - BioCreative V BioC track overview
T2 - collaborative biocurator assistant task for BioGRID
AU - Kim, Sun
AU - Islamaj Doğan, Rezarta
AU - Chatr-Aryamontri, Andrew
AU - Chang, Christie S
AU - Oughtred, Rose
AU - Rust, Jennifer
AU - Batista-Navarro, Riza
AU - Carter, Jacob
AU - Ananiadou, Sophia
AU - Matos, Sérgio
AU - Santos, André
AU - Campos, David
AU - Oliveira, José Luís
AU - Singh, Onkar
AU - Jonnagaddala, Jitendra
AU - Dai, Hong-Jie
AU - Su, Emily Chia-Yu
AU - Chang, Yung-Chun
AU - Su, Yu-Chen
AU - Chu, Chun-Han
AU - Chen, Chien Chin
AU - Hsu, Wen-Lian
AU - Peng, Yifan
AU - Arighi, Cecilia
AU - Wu, Cathy H
AU - Vijay-Shanker, K
AU - Aydın, Ferhat
AU - Hüsünbeyi, Zehra Melce
AU - Özgür, Arzucan
AU - Shin, Soo-Yong
AU - Kwon, Dongseop
AU - Dolinski, Kara
AU - Tyers, Mike
AU - Wilbur, W John
AU - Comeau, Donald C
N1 - Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.
PY - 2016/9/1
Y1 - 2016/9/1
N2 - BioC is a simple XML format for text, annotations and relations, and was developed to achieve interoperability for biomedical text processing. Following the success of BioC in BioCreative IV, the BioCreative V BioC track addressed a collaborative task to build an assistant system for BioGRID curation. In this paper, we describe the framework of the collaborative BioC task and discuss our findings based on the user survey. This track consisted of eight subtasks including gene/protein/organism named entity recognition, protein-protein/genetic interaction passage identification and annotation visualization. Using BioC as their data-sharing and communication medium, nine teams, world-wide, participated and contributed either new methods or improvements of existing tools to address different subtasks of the BioC track. Results from different teams were shared in BioC and made available to other teams as they addressed different subtasks of the track. In the end, all submitted runs were merged using a machine learning classifier to produce an optimized output. The biocurator assistant system was evaluated by four BioGRID curators in terms of practical usability. The curators' feedback was overall positive and highlighted the user-friendly design and the convenient gene/protein curation tool based on text mining.Database URL: http://www.biocreative.org/tasks/biocreative-v/track-1-bioc/.
AB - BioC is a simple XML format for text, annotations and relations, and was developed to achieve interoperability for biomedical text processing. Following the success of BioC in BioCreative IV, the BioCreative V BioC track addressed a collaborative task to build an assistant system for BioGRID curation. In this paper, we describe the framework of the collaborative BioC task and discuss our findings based on the user survey. This track consisted of eight subtasks including gene/protein/organism named entity recognition, protein-protein/genetic interaction passage identification and annotation visualization. Using BioC as their data-sharing and communication medium, nine teams, world-wide, participated and contributed either new methods or improvements of existing tools to address different subtasks of the BioC track. Results from different teams were shared in BioC and made available to other teams as they addressed different subtasks of the track. In the end, all submitted runs were merged using a machine learning classifier to produce an optimized output. The biocurator assistant system was evaluated by four BioGRID curators in terms of practical usability. The curators' feedback was overall positive and highlighted the user-friendly design and the convenient gene/protein curation tool based on text mining.Database URL: http://www.biocreative.org/tasks/biocreative-v/track-1-bioc/.
KW - Journal Article
KW - Research Support, N.I.H., Extramural
KW - Research Support, Non-U.S. Gov't
KW - Research Support, N.I.H., Intramural
KW - Research Support, U.S. Gov't, Non-P.H.S.
UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-85037580282&origin=resultslist&sort=plf-f&src=s&sid=2cf3fc6ad797b7bd2d82bd0ec0fd4bec&sot=a&sdt=a&sl=31&s=AU-ID%28%22Su%2c+Chiayu%22+22939281200%29&relpos=7&citeCnt=1&searchTerm=
UR - https://www.scopus.com/results/citedbyresults.uri?sort=plf-f&cite=2-s2.0-85037580282&src=s&imp=t&sid=ac348583fdf48692a1efccbb0f9008e0&sot=cite&sdt=a&sl=0&origin=recordpage&editSaveSearch=&txGid=3039ab3f2fb1efb365560880f4cc6ee0
U2 - 10.1093/database/baw121
DO - 10.1093/database/baw121
M3 - Article
C2 - 27589962
SN - 1758-0463
VL - 2016
JO - Database : the journal of biological databases and curation
JF - Database : the journal of biological databases and curation
ER -