<p>Applying Natural Language Processing (NLP) techniques on the scientific literature to accelerate drug discovery for COVID-19</p>

Carlos Soto; Gilchan Park; Yen-Chi Chen; Ada Sedova; Line Pouchard; Shinjae Yoo

doi:10.7490/f1000research.1118140.1

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Soto C, Park G, Chen YC et al. Applying Natural Language Processing (NLP) techniques on the scientific literature to accelerate drug discovery for COVID-19 [version 1; not peer reviewed]. F1000Research 2020, 9(ISCB Comm J):853 (poster) (https://doi.org/10.7490/f1000research.1118140.1)

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Applying Natural Language Processing (NLP) techniques on the scientific literature to accelerate drug discovery for COVID-19

Carlos Soto¹, Gilchan Park, Yen-Chi Chen, Ada Sedova, Line Pouchard, Shinjae Yoo

Published 31 Jul 2020 (https://doi.org/10.7490/f1000research.1118140.1)

Author Affiliations

¹ Brookhaven National Laboratory, USA

Copyright © 2020 Soto C 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 31 Jul 2020

Applying Natural Language Processing (NLP) techniques on the scientific literature to accelerate drug discovery for COVID-19
[version 1; not peer reviewed]

Carlos Soto¹, Gilchan Park, Yen-Chi Chen, Ada Sedova, Line Pouchard, Shinjae Yoo

Author Affiliations

¹ Brookhaven National Laboratory, USA

Presented at

28th International Conference on Intelligent Systems for Molecular Biology (ISMB) 2020

Abstract

Competing Interests

No competing interests were disclosed

Keywords

Natural Language Processing, NLP, scientific literature mining, COVID-19, drug discovery

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