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ZENODO
Dataset . 2021
License: CC BY NC
Data sources: Datacite
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Dataset . 2021
License: CC BY NC
Data sources: ZENODO
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ZENODO
Dataset . 2021
License: CC BY NC
Data sources: ZENODO
ZENODO
Dataset . 2021
License: CC BY NC
Data sources: Datacite
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3Cnet: pathogenicity prediction of human variants using multitask learning with evolutionary constraints

Research datakeyboard_double_arrow_right Dataset 01 Jan 2021 English Publisher:Zenodo
Authors: Won, Dhong-gun; Kim, Dong-wook; Woo, Junwoo Isaac; Lee, Kyoungyeul;

doi: 10.5281/zenodo.6016720 , 10.5281/zenodo.6016719

3Cnet: pathogenicity prediction of human variants using multitask learning with evolutionary constraints

Abstract

Dataset needed to train and evaluate 3Cnet. See github repository for source code. https://github.com/KyoungYeulLee/3Cnet

Keywords

pathogenicity prediction, protein sequence variants, recurrent neural networks, knowledge transfer

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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