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For: Alshawaqfeh M, Bashaireh A, Serpedin E, Suchodolski J. Consistent metagenomic biomarker detection via robust PCA. Biol Direct 2017;12:4. [PMID: 28143486 DOI: 10.1186/s13062-017-0175-4] [Cited by in Crossref: 11] [Cited by in F6Publishing: 7] [Article Influence: 2.2] [Reference Citation Analysis]
Number Citing Articles
1 Nguyen TH, Nguyen T. Disease Prediction Using Metagenomic Data Visualizations Based on Manifold Learning and Convolutional Neural Network. In: Dang TK, Küng J, Takizawa M, Bui SH, editors. Future Data and Security Engineering. Cham: Springer International Publishing; 2019. pp. 117-31. [DOI: 10.1007/978-3-030-35653-8_9] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Feng X, Li J, Li H, Chen H, Li F, Liu Q, You ZH, Zhou F. Age Is Important for the Early-Stage Detection of Breast Cancer on Both Transcriptomic and Methylomic Biomarkers. Front Genet 2019;10:212. [PMID: 30984234 DOI: 10.3389/fgene.2019.00212] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]
3 AlShawaqfeh MK, Wajid B, Minamoto Y, Markel M, Lidbury JA, Steiner JM, Serpedin E, Suchodolski JS. A dysbiosis index to assess microbial changes in fecal samples of dogs with chronic inflammatory enteropathy. FEMS Microbiol Ecol 2017;93. [PMID: 29040443 DOI: 10.1093/femsec/fix136] [Cited by in Crossref: 66] [Cited by in F6Publishing: 62] [Article Influence: 16.5] [Reference Citation Analysis]
4 Tang J, Wang Y, Fu J, Zhou Y, Luo Y, Zhang Y, Li B, Yang Q, Xue W, Lou Y, Qiu Y, Zhu F. A critical assessment of the feature selection methods used for biomarker discovery in current metaproteomics studies. Briefings in Bioinformatics 2020;21:1378-90. [DOI: 10.1093/bib/bbz061] [Cited by in Crossref: 19] [Cited by in F6Publishing: 15] [Article Influence: 6.3] [Reference Citation Analysis]
5 Nagpal S, Singh R, Taneja B, Mande SS. MarkerML – Marker feature identification in metagenomic datasets using interpretable machine learning. Journal of Molecular Biology 2022. [DOI: 10.1016/j.jmb.2022.167589] [Reference Citation Analysis]
6 Li C, Xu J. Feature selection with the Fisher score followed by the Maximal Clique Centrality algorithm can accurately identify the hub genes of hepatocellular carcinoma. Sci Rep 2019;9:17283. [PMID: 31754223 DOI: 10.1038/s41598-019-53471-0] [Cited by in Crossref: 9] [Cited by in F6Publishing: 8] [Article Influence: 3.0] [Reference Citation Analysis]
7 Huang L, Xu C, Yang W, Yu R. A machine learning framework to determine geolocations from metagenomic profiling. Biol Direct 2020;15:27. [PMID: 33225966 DOI: 10.1186/s13062-020-00278-z] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 1.0] [Reference Citation Analysis]
8 Alshawaqfeh M, Bashaireh A, Serpedin E, Suchodolski J. Reliable Biomarker discovery from Metagenomic data via RegLRSD algorithm. BMC Bioinformatics 2017;18:328. [PMID: 28693478 DOI: 10.1186/s12859-017-1738-1] [Cited by in Crossref: 2] [Cited by in F6Publishing: 3] [Article Influence: 0.4] [Reference Citation Analysis]