CNN-based Chemical-Protein Interactions Classification. Yüksel, A., Öztürk, H., Ozkirimli, E., & Özgür, A. Technical Report
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Paper Website abstract bibtex In this study, we present a Convolutional Neural Network (CNN) based model for the extraction and classification of different groups of interactions between chemical and protein pairs for the Text Mining Chemical-Protein Interactions (CHEMPROT) task of BioCreative VI. We used word-embeddings and distance embeddings to represent a potential relation. Our system obtained 0.68 F-measure on the CHEMPROT development set.
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abstract = {In this study, we present a Convolutional Neural Network (CNN) based model for the extraction and classification of different groups of interactions between chemical and protein pairs for the Text Mining Chemical-Protein Interactions (CHEMPROT) task of BioCreative VI. We used word-embeddings and distance embeddings to represent a potential relation. Our system obtained 0.68 F-measure on the CHEMPROT development set.},
bibtype = {techreport},
author = {Yüksel, Atakan and Öztürk, Hakime and Ozkirimli, Elif and Özgür, Arzucan}
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