Document Type
Article
Language
eng
Publication Date
2008
Publisher
BioMed Central
Source Publication
Genome Biology
Source ISSN
1465-6906
Original Item ID
doi: 10.1186/gb-2008-9-s2-s2; PubMed Central: PMCID 2559986
Abstract
Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop. In this task participants designed systems to identify substrings in sentences corresponding to gene name mentions. A variety of different methods were used and the results varied with a highest achieved F1 score of 0.8721. Here we present brief descriptions of all the methods used and a statistical analysis of the results. We also demonstrate that, by combining the results from all submissions, an F score of 0.9066 is feasible, and furthermore that the best result makes use of the lowest scoring submissions.
Recommended Citation
Smith, Larry; Tanabe, Lorraine K.; nee Ando, Rie Johnson; Kuo, Cheng-Ju; Chung, I-Fang; Hsu, Chun-Nan; Lin, Yu-Shi; Klinger, Roman; Friedrich, Christoph M.; Ganchev, Kuzman; Torii, Manabu; Liu, Hongfang; Haddow, Barry; Struble, Craig A.; Povinelli, Richard J.; Vlachos, Andreas; Baumgartner, William A.; Hunter, Lawrence; Carpenter, Bob; Tsai, Richard Tzong-Han; Dai, Hong-Jie; Liu, Feng; Chen, Yifei; Sun, Chengjie; Katrenko, Sophia; Adriaans, Pieter; Blaschke, Christian; Torres, Rafael; Neves, Mariana; Nakov, Preslav; Divoli, Anna; Maña-López, Manuel; Mata, Jacinto; and Wilbur, W John, "Overview of BioCreative II Gene Mention Recognition" (2008). Electrical and Computer Engineering Faculty Research and Publications. 91.
https://epublications.marquette.edu/electric_fac/91
Comments
Published version. Genome Biology, Vol. 9, Suppl. 2 (2008). DOI. © 2008 Smith et al; licensee BioMed Central Ltd.
This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.