<p>Assessing CNN and RNN models to classify scientific literature into UniProt entry categories</p>

Julien Knafou; Douglas Teodoro; Cecilia Arighi; Patrick Ruch

doi:10.7490/f1000research.1117043.1

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Knafou J, Teodoro D, Arighi C and Ruch P. Assessing CNN and RNN models to classify scientific literature into UniProt entry categories [version 1; not peer reviewed]. F1000Research 2019, 8(ELIXIR):1092 (poster) (https://doi.org/10.7490/f1000research.1117043.1)

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Assessing CNN and RNN models to classify scientific literature into UniProt entry categories

Julien Knafou¹, Douglas Teodoro, Cecilia Arighi, Patrick Ruch

Published 15 Jul 2019 (https://doi.org/10.7490/f1000research.1117043.1)

Author Affiliations

¹ SIB Text Mining, Swiss Institute of Bioinformatics, Switzerland

Copyright © 2019 Knafou J et al. This is an open access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Published 15 Jul 2019

Assessing CNN and RNN models to classify scientific literature into UniProt entry categories
[version 1; not peer reviewed]

Julien Knafou¹, Douglas Teodoro, Cecilia Arighi, Patrick Ruch

Author Affiliations

¹ SIB Text Mining, Swiss Institute of Bioinformatics, Switzerland

Presented at

ELIXIR All Hands 2019

Abstract

Competing Interests

No competing interests were disclosed

Keywords

uniprot, uniprotKB, CNN, RNN, text mining

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