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Cited by in F6Publishing
For: Jiang S, Xiao G, Koh AY, Chen Y, Yao B, Li Q, Zhan X. HARMONIES: A Hybrid Approach for Microbiome Networks Inference via Exploiting Sparsity. Front Genet 2020;11:445. [PMID: 32582274 DOI: 10.3389/fgene.2020.00445] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
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1 Matchado MS, Lauber M, Reitmeier S, Kacprowski T, Baumbach J, Haller D, List M. Network analysis methods for studying microbial communities: A mini review. Comput Struct Biotechnol J 2021;19:2687-98. [PMID: 34093985 DOI: 10.1016/j.csbj.2021.05.001] [Cited by in F6Publishing: 2] [Reference Citation Analysis]
2 Chen L, Wan H, He Q, He S, Deng M. Statistical Methods for Microbiome Compositional Data Network Inference: A Survey. J Comput Biol 2022. [PMID: 35404093 DOI: 10.1089/cmb.2021.0406] [Reference Citation Analysis]
3 Zeng Y, Li J, Wei C, Zhao H, Tao W. mbDenoise: microbiome data denoising using zero-inflated probabilistic principal components analysis. Genome Biol 2022;23. [DOI: 10.1186/s13059-022-02657-3] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]