ProMiner: rule-based protein and gene entity recognition

2005346 citationsJournal Articlegold Open Access

Authors

Daniel Hanisch · Fraunhofer Institute for Algorithms and Scientific Computing

Katrin Fundel · Ludwig-Maximilians-Universität München

Heinz‐Theodor Mevissen · Fraunhofer Institute for Algorithms and Scientific Computing

Ralf Zimmer · Ludwig-Maximilians-Universität München

Juliane Fluck · Fraunhofer Institute for Algorithms and Scientific Computing

Abstract

The extended ProMiner system has been applied to the test cases of the BioCreAtIvE competition with highly encouraging results. In blind predictions, the system achieved an F-measure of approximately 0.8 for the organisms mouse and fly and about 0.9 for the organism yeast.

Topics & Keywords

Biomedical Text Mining and Ontologies Semantic Web and Ontologies Genomics and Phylogenetic Studies

Publication Details

Published in: BMC Bioinformatics

Volume 6, Issue S1, pp. S14-S14

DOI: 10.1186/1471-2105-6-s1-s14

Field-Weighted Citation Impact: 6.43

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ProMiner: rule-based protein and gene entity recognition

Authors

Abstract

Topics & Keywords

Publication Details