Overview of BioCreative II Gene Mention Recognition

Authors

• Larry Smith, National Center for Biotechnology Information
• Lorraine K. Tanabe, National Center for Biotechnology Information
• Rie Johnson nee Ando, IBM TJ Watson Research
• Cheng-Ju Kuo, National Yang-Ming University
• I-Fang Chung, National Yang Ming University
• Chun-Nan Hsu, Academia Sinica
• Yu-Shi Lin, Academia Sinica
• Roman Klinger, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI)
• Christoph M. Friedrich, Fraunhofer Institute for Algorithms and Scientific Computing (SCAI)
• Kuzman Ganchev, University of Pennsylvania
• Manabu Torii, Georgetown University Medical Center
• Hongfang Liu, Georgetown University Medical Center
• Barry Haddow, University of Edinburgh
• Craig A. Struble, Marquette University
• Richard J. Povinelli, Marquette UniversityFollow
• Andreas Vlachos, University of Cambridge
• William A. Baumgartner, University of Colorado School of Medicine
• Lawrence Hunter, University of Colorado School of Medicine
• Bob Carpenter, Alias-i, Inc.
• Richard Tzong-Han Tsai, Academia Sinica
• Hong-Jie Dai, Academia Sinica
• Feng Liu, Vrije Universiteit Brussels
• Yifei Chen, Vrije Universiteit Brussels
• Chengjie Sun, Harbin Institute of Technology
• Sophia Katrenko, University of Amsterdam
• Pieter Adriaans, University of Amsterdam
• Christian Blaschke, Tres Cantos (Madrid)
• Rafael Torres, Tres Cantos (Madrid)
• Mariana Neves, Universidad Complutense de Madrid
• Preslav Nakov, University of California - Berkeley
• Anna Divoli, University of California - Berkeley
• Manuel Maña-López, Universidad de Huelva
• Jacinto Mata, Universidad de Huelva
• W John Wilbur, National Center for Biotechnology Information

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

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.

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.

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