Overview of BioCreative II gene mention recognition

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 F(1 )...

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Detalles Bibliográficos
Autores principales: Smith, Larry, Tanabe, Lorraine K, Ando, Rie Johnson nee, 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, Wilbur, W John
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2559986/
https://www.ncbi.nlm.nih.gov/pubmed/18834493
http://dx.doi.org/10.1186/gb-2008-9-s2-s2
Descripción
Sumario: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 F(1 )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.

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