Microbe Disease Associations | List of Frontiers open access articles

Original Research

Published on 13 Dec 2024

Predicting microbe-disease associations via graph neural network and contrastive learning

in Systems Microbiology

Cong Jiang
Junxuan Feng
Bingshen Shan
Qiyue Chen
Jian Yang
Gang Wang
Xiaogang Peng
Xiaozheng Li

Frontiers in Microbiology

doi 10.3389/fmicb.2024.1483983

3,018 views
4 citations

Original Research

Published on 31 May 2022

Metapath Aggregated Graph Neural Network and Tripartite Heterogeneous Networks for Microbe-Disease Prediction

in Systems Microbiology

Yali Chen
Xiujuan Lei

Frontiers in Microbiology

doi 10.3389/fmicb.2022.919380

5,360 views
24 citations

Original Research

Published on 26 Feb 2019

Identification and Analysis of Human Microbe-Disease Associations by Matrix Decomposition and Label Propagation

in Systems Microbiology

Jia Qu
Yan Zhao
Jun Yin

Frontiers in Microbiology

doi 10.3389/fmicb.2019.00291

5,920 views
42 citations

Original Research

Published on 22 Feb 2017

PBHMDA: Path-Based Human Microbe-Disease Association Prediction

in Systems Microbiology

Zhi-An Huang
Xing Chen
Zexuan Zhu
Hongsheng Liu
Gui-Ying Yan
Zhu-Hong You
Zhenkun Wen

Frontiers in Microbiology

doi 10.3389/fmicb.2017.00233

8,287 views
89 citations

Original Research

Published on 11 Feb 2025

Dual graph-embedded fusion network for predicting potential microbe-disease associations with sequence learning

in Computational Genomics

Junlong Wu
Liqi Xiao
Liu Fan
Lei Wang
Xianyou Zhu

Frontiers in Genetics

doi 10.3389/fgene.2025.1511521

1,725 views
1 citation

Editorial

Published on 26 Oct 2023

Editorial: Omics-based novel computational methods revealing microbe-disease associations

in Extra-intestinal Microbiome

Stephen S.-T. Yau
Qi Wu

Frontiers in Cellular and Infection Microbiology

doi 10.3389/fcimb.2023.1305902

1,267 views

Original Research

Published on 23 Mar 2023

MADGAN:A microbe-disease association prediction model based on generative adversarial networks

in Systems Microbiology

Weixin Hu
Xiaoyu Yang
Lei Wang
Xianyou Zhu

Frontiers in Microbiology

doi 10.3389/fmicb.2023.1159076

3,302 views
6 citations

Methods

Published on 19 Jan 2023

Identifying microbe-disease association based on graph convolutional attention network: Case study of liver cirrhosis and epilepsy

in Gut-Brain Axis

Kai Shi
Lin Li
Zhengfeng Wang
Huazhou Chen
Zilin Chen
Shuanfeng Fang

Frontiers in Neuroscience

doi 10.3389/fnins.2022.1124315

4,074 views
12 citations

Original Research

Published on 10 Jul 2019

RWHMDA: Random Walk on Hypergraph for Microbe-Disease Association Prediction

in Systems Microbiology

Ya-Wei Niu
Cun-Quan Qu
Guang-Hui Wang
Gui-Ying Yan

Frontiers in Microbiology

doi 10.3389/fmicb.2019.01578

6,348 views
24 citations

Methods

Published on 04 Aug 2020

Inferring Disease-Associated Microbes Based on Multi-Data Integration and Network Consistency Projection

in Computational Genomics

Yongxian Fan
Meijun Chen
Qingqi Zhu
Wanru Wang

Frontiers in Bioengineering and Biotechnology

doi 10.3389/fbioe.2020.00831

3,471 views
19 citations

Methods

Published on 08 Aug 2025

BANSMDA: a computational model for predicting potential microbe-disease associations based on bilinear attention networks and sparse autoencoders

in Computational Genomics

Xianzhi Liu
Mingmin Liang
Ge Yu
Shichang Tang
Ouxiang Wu
Bin Zeng
Lei Wang

Frontiers in Genetics

doi 10.3389/fgene.2025.1618472

1,521 views
1 citation

Original Research

Published on 02 Feb 2024

MLFLHMDA: predicting human microbe-disease association based on multi-view latent feature learning

in Systems Microbiology

Ziwei Chen
Liangzhe Zhang
Jingyi Li
Mingyang Fu

Frontiers in Microbiology

doi 10.3389/fmicb.2024.1353278

2,439 views
6 citations

Original Research

Published on 10 Mar 2022

Novel Collaborative Weighted Non-negative Matrix Factorization Improves Prediction of Disease-Associated Human Microbes

in Systems Microbiology

Da Xu
Hanxiao Xu
Yusen Zhang
Rui Gao

Frontiers in Microbiology

doi 10.3389/fmicb.2022.834982

2,394 views
7 citations

Original Research

Published on 14 Oct 2021

Multi-Similarities Bilinear Matrix Factorization-Based Method for Predicting Human Microbe–Disease Associations

in Computational Genomics

Xiaoyu Yang
Linai Kuang
Zhiping Chen
Lei Wang

Frontiers in Genetics

doi 10.3389/fgene.2021.754425

2,693 views
9 citations

Original Research

Published on 18 Sep 2023

Predicting potential microbe-disease associations with graph attention autoencoder, positive-unlabeled learning, and deep neural network

in Systems Microbiology

Lihong Peng
Liangliang Huang
Geng Tian
Yan Wu
Guang Li
Jianying Cao
Peng Wang
Zejun Li
Lian Duan

Frontiers in Microbiology

doi 10.3389/fmicb.2023.1244527

3,882 views
15 citations

Original Research

Published on 01 Nov 2018

Human Microbe-Disease Association Prediction With Graph Regularized Non-Negative Matrix Factorization

in Systems Microbiology

Bin-Sheng He
Li-Hong Peng
Zejun Li

Frontiers in Microbiology

doi 10.3389/fmicb.2018.02560

5,251 views
32 citations

Articles

Predicting microbe-disease associations via graph neural network and contrastive learning

Metapath Aggregated Graph Neural Network and Tripartite Heterogeneous Networks for Microbe-Disease Prediction

Identification and Analysis of Human Microbe-Disease Associations by Matrix Decomposition and Label Propagation

PBHMDA: Path-Based Human Microbe-Disease Association Prediction

Dual graph-embedded fusion network for predicting potential microbe-disease associations with sequence learning

Editorial: Omics-based novel computational methods revealing microbe-disease associations

MADGAN:A microbe-disease association prediction model based on generative adversarial networks

Identifying microbe-disease association based on graph convolutional attention network: Case study of liver cirrhosis and epilepsy

RWHMDA: Random Walk on Hypergraph for Microbe-Disease Association Prediction

Inferring Disease-Associated Microbes Based on Multi-Data Integration and Network Consistency Projection

BANSMDA: a computational model for predicting potential microbe-disease associations based on bilinear attention networks and sparse autoencoders

MLFLHMDA: predicting human microbe-disease association based on multi-view latent feature learning

Novel Collaborative Weighted Non-negative Matrix Factorization Improves Prediction of Disease-Associated Human Microbes

Multi-Similarities Bilinear Matrix Factorization-Based Method for Predicting Human Microbe–Disease Associations

Predicting potential microbe-disease associations with graph attention autoencoder, positive-unlabeled learning, and deep neural network

Human Microbe-Disease Association Prediction With Graph Regularized Non-Negative Matrix Factorization