Baoshi Liu
Northwest A&F University
6 Papers
Baoshi Liu is an academic researcher from Northwest A&F University. The author has contributed to research in topics: Medicine & Similarity (geometry). The author has an hindex of 1, co-authored 2 publications.
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Papers
Systematic investigation of the Erigeron breviscapus mechanism for treating cerebrovascular disease.
J.G. Wang,Zhang Lulu,Baoshi Liu,Qian Wang,Yangyang Chen,Zhenzhong Wang,Jun Zhou,Wei Xiao,Chunli Zheng,Yonghua Wang +9 more
TL;DR: The Erigeron breviscapus exerts a protective effect on CBVDs via regulating multiple pathways and hitting on multiple targets, which will give an impulse to theCBVDs drug development.
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A new framework for drug-disease association prediction combing light-gated message passing neural network and gated fusion mechanism
TL;DR: A model integrating a new variant of message passing neural network and a novel-gated fusion mechanism called GLGMPNN is proposed for drug-disease association prediction, which achieves excellent performance compared with the current models.
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SLGCN: Structure-enhanced line graph convolutional network for predicting drug-disease associations
Baoshi Liu,Ying-Lian Gao,Feng Li,Chunhou Zheng,Jinping Liu +4 more
TL;DR: This paper proposes SLGCN, a structure-enhanced line graph convolutional network, to predict drug-disease associations by incorporating structural information and heterophily, outperforming other methods on two datasets in drug repositioning.
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Patent
Pharmaceutical composition and applications thereof, sterile container and kit
Xiao Wei,Wang Yonghua,Zheng Chunli,Baoshi Liu,Zhang Lulu,Wang Zhenzhong +5 more
- 03 Apr 2020
TL;DR: In this article, a pharmaceutical composition consisting of a therapeutically effective amount of sophora flavescens and an antibody to at least an immune checkpoint is described. And the composition provides an opportunity to produce addition or synergistic effect in treatment of cancer and reduces side effects.
MKGSAGE: A Computational Framework via Multiple Kernel Fusion on GraphSAGE for Inferring Potential Disease-Related Microbes
Shuang Wang,Jinping Liu,Baoshi Liu,Lingyun Dai,Feng Li,Ying-Lian Gao +5 more
- 05 Dec 2023
TL;DR: A computational framework based on the multiple kernel fusion of graph embedding with sampling and aggregation and dual Laplace regularized least squares called MKGSAGE is proposed for predicting potential links between microbe and disease and 5-fold cross-validations show that MKGSAGE performs best.