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Fast Neural Network Engine for Natural Science Language Processing: A Drug-Search Case.

26 August 2020, Version 2
Working Paper
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

The main advantage of modern natural language processing methods is a possibility to turn an amorphous human-readable task into a strict mathematic form. That allows to extract chemical data and insights from articles and to find new semantic relations. We propose a universal engine for processing chemical and biological texts. We successfully tested it on various use-cases and applied to a case of searching a therapeutic agent for a COVID-19 disease by analyzing PubMed archive.

Keywords

nataral language processing
drug design
covid-19

Supplementary materials

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Version History

Aug 26, 2020 Version 2

Version Notes

Fixed typos, added Supporting Information

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The content is available under CC BY NC ND 4.0 [opens in a new tab]

DOI

10.26434/chemrxiv.12800348.v2
D O I: 10.26434/chemrxiv.12800348.v2 [opens in a new tab]

Author’s competing interest statement

No conflict of interest

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