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For: Qu J, Zhao Y, Yin J. Identification and Analysis of Human Microbe-Disease Associations by Matrix Decomposition and Label Propagation. Front Microbiol 2019;10:291. [PMID: 30863376 DOI: 10.3389/fmicb.2019.00291] [Cited by in Crossref: 9] [Cited by in F6Publishing: 12] [Article Influence: 3.0] [Reference Citation Analysis]
Number Citing Articles
1 Yang X, Kuang L, Chen Z, Wang L. Multi-Similarities Bilinear Matrix Factorization-Based Method for Predicting Human Microbe-Disease Associations. Front Genet 2021;12:754425. [PMID: 34721543 DOI: 10.3389/fgene.2021.754425] [Reference Citation Analysis]
2 Yin M, Gao Y, Shang J, Zheng C, Liu J. Multi-similarity fusion-based label propagation for predicting microbes potentially associated with diseases. Future Generation Computer Systems 2022;134:247-55. [DOI: 10.1016/j.future.2022.04.012] [Reference Citation Analysis]
3 Peng L, Shen L, Liao L, Liu G, Zhou L. RNMFMDA: A Microbe-Disease Association Identification Method Based on Reliable Negative Sample Selection and Logistic Matrix Factorization With Neighborhood Regularization. Front Microbiol 2020;11:592430. [PMID: 33193260 DOI: 10.3389/fmicb.2020.592430] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
4 Lei X, Wang Y. Predicting Microbe-Disease Association by Learning Graph Representations and Rule-Based Inference on the Heterogeneous Network. Front Microbiol 2020;11:579. [PMID: 32351464 DOI: 10.3389/fmicb.2020.00579] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
5 Zhao Y, Wang CC, Chen X. Microbes and complex diseases: from experimental results to computational models. Brief Bioinform 2021;22:bbaa158. [PMID: 32766753 DOI: 10.1093/bib/bbaa158] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
6 Niu YW, Qu CQ, Wang GH, Yan GY. RWHMDA: Random Walk on Hypergraph for Microbe-Disease Association Prediction. Front Microbiol 2019;10:1578. [PMID: 31354672 DOI: 10.3389/fmicb.2019.01578] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 1.7] [Reference Citation Analysis]
7 Ma Y, Jiang H. NinimHMDA: Neural integration of neighborhood information on a multiplex heterogeneous network for multiple types of human Microbe-Disease association. Bioinformatics 2021:btaa1080. [PMID: 33416850 DOI: 10.1093/bioinformatics/btaa1080] [Reference Citation Analysis]
8 Grenni P. Antimicrobial Resistance in Rivers: A Review of the Genes Detected and New Challenges. Environ Toxicol Chem 2022;41:687-714. [PMID: 35191071 DOI: 10.1002/etc.5289] [Reference Citation Analysis]
9 Xu D, Xu H, Zhang Y, Gao R. Novel Collaborative Weighted Non-negative Matrix Factorization Improves Prediction of Disease-Associated Human Microbes. Front Microbiol 2022;13:834982. [DOI: 10.3389/fmicb.2022.834982] [Reference Citation Analysis]
10 Alaidarous MA. The emergence of new trends in clinical laboratory diagnosis. Saudi Med J 2020;41:1175-80. [PMID: 33130836 DOI: 10.15537/smj.2020.11.25455] [Reference Citation Analysis]
11 Srivastava D, Baksi KD, Kuntal BK, Mande SS. "EviMass": A Literature Evidence-Based Miner for Human Microbial Associations. Front Genet 2019;10:849. [PMID: 31616466 DOI: 10.3389/fgene.2019.00849] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 0.7] [Reference Citation Analysis]
12 Xu D, Xu H, Zhang Y, Wang M, Chen W, Gao R. MDAKRLS: Predicting human microbe-disease association based on Kronecker regularized least squares and similarities. J Transl Med 2021;19:66. [PMID: 33579301 DOI: 10.1186/s12967-021-02732-6] [Reference Citation Analysis]
13 Chen Y, Sun H, Sun M, Shi C, Sun H, Shi X, Ji B, Cui J. Finding Colon Cancer- and Colorectal Cancer-Related Microbes Based on Microbe-Disease Association Prediction. Front Microbiol 2021;12:650056. [PMID: 33796094 DOI: 10.3389/fmicb.2021.650056] [Reference Citation Analysis]
14 Wen Z, Yan C, Duan G, Li S, Wu FX, Wang J. A survey on predicting microbe-disease associations: biological data and computational methods. Brief Bioinform 2021;22:bbaa157. [PMID: 34020541 DOI: 10.1093/bib/bbaa157] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
15 Wang L, Tan Y, Yang X, Kuang L, Ping P. Review on predicting pairwise relationships between human microbes, drugs and diseases: from biological data to computational models. Brief Bioinform 2022:bbac080. [PMID: 35325024 DOI: 10.1093/bib/bbac080] [Reference Citation Analysis]
16 Wu C, Xiao X, Yang C, Chen J, Yi J, Qiu Y. Mining microbe-disease interactions from literature via a transfer learning model. BMC Bioinformatics 2021;22:432. [PMID: 34507528 DOI: 10.1186/s12859-021-04346-7] [Reference Citation Analysis]