Statistical principle-based approach for gene and protein related object recognition

Author:

Lai Po-TingORCID,Huang Ming-Siang,Yang Ting-Hao,Hsu Wen-Lian,Tsai Richard Tzong-Han

Funder

Ministry of Science and Technology, Taiwan

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Computer Graphics and Computer-Aided Design,Physical and Theoretical Chemistry,Computer Science Applications

Reference22 articles.

1. Rabal O, Pérez-Pérez M, Pérez-Rodríguez G, Vazquez M, Fdez-Riverola F, Oyarzabal J, Valencia A, Lourenço A, Krallinger M (2018) Comparative assessment of named entity recognition strategies on medicinal chemistry patents for systems pharmacology. J Cheminformatics 2018:11–18

2. Kim J-D, Ohta T, Tsuruoka Y, Tateisi Y, Collier N (2004) Introduction to the bio-entity recognition task at JNLPBA. In Proceedings of the international joint workshop on natural language processing in biomedicine and its applications. Association for Computational Linguistics, Geneva, Switzerland, pp 70–75

3. Smith L, Tanabe LK, Ando R, Kuo C-J, Chung I-F, Hsu C-N, Lin Y-S, Klinger R, Friedrich CM, Ganchev K et al (2008) Overview of BioCreative II gene mention recognition. Genome Biol 9:S2

4. Krallinger M, Leitner F, Rabal O, Vazquez M, Oyarzabal J, Valencia A (2015) CHEMDNER: the drugs and chemical names extraction challenge. J Cheminform 7(1):S1

5. Leaman R, Wei C-H, Zou C, Lu Z (2016) Mining chemical patents with an ensemble of open systems. Database. https://doi.org/10.1093/database/baw065

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