<p>Improving target-disease association prediction through a graph neural network with credibility information</p>

Chang Liu; Cuinan Yu; Yipin Lei; Kangbo Lyu; Tingzhong Tian; Qianhao Li; Dan Zhao; Fengfeng Zhou; Jianyang Zeng

doi:10.7490/f1000research.1119131.1

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Liu C, Yu C, Lei Y et al. Improving target-disease association prediction through a graph neural network with credibility information [version 1; not peer reviewed]. F1000Research 2022, 11:1110 (poster) (https://doi.org/10.7490/f1000research.1119131.1)

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Improving target-disease association prediction through a graph neural network with credibility information

Chang Liu, Cuinan Yu, Yipin Lei, Kangbo Lyu, Tingzhong Tian, Qianhao Li, Dan Zhao¹, Fengfeng Zhou², Jianyang Zeng¹

Published 28 Sep 2022 (https://doi.org/10.7490/f1000research.1119131.1)

Author Affiliations

¹ Institute for Interdisciplinary Information Sciences, Tsinghua University, China
² Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, College of Computer Science and Technology, Jilin University, China

Copyright © 2022 Liu 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 28 Sep 2022

Improving target-disease association prediction through a graph neural network with credibility information
[version 1; not peer reviewed]

Chang Liu, Cuinan Yu, Yipin Lei, Kangbo Lyu, Tingzhong Tian, Qianhao Li, Dan Zhao¹, Fengfeng Zhou², Jianyang Zeng¹

Author Affiliations

Abstract

Competing Interests

No competing interests were disclosed

Keywords

target-disease association, graph neural network, credibility information, drug discovery

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