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Cited by in F6Publishing
For: Li J, Peng D, Xie Y, Dai Z, Zou X, Li Z. Novel Potential Small Molecule-MiRNA-Cancer Associations Prediction Model Based on Fingerprint, Sequence, and Clinical Symptoms. J Chem Inf Model 2021;61:2208-19. [PMID: 33899462 DOI: 10.1021/acs.jcim.0c01458] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 0.5] [Reference Citation Analysis]
Number Citing Articles
1 Luo Y, Peng L, Shan W, Sun M, Luo L, Liang W. Machine learning in the development of targeting microRNAs in human disease. Front Genet 2022;13:1088189. [PMID: 36685965 DOI: 10.3389/fgene.2022.1088189] [Reference Citation Analysis]
2 Ni J, Cheng X, Ni T, Liang J. Identifying SM-miRNA associations based on layer attention graph convolutional network and matrix decomposition. Front Mol Biosci 2022;9:1009099. [PMID: 36504714 DOI: 10.3389/fmolb.2022.1009099] [Reference Citation Analysis]
3 Xu H, Li B. MicroRNA-582-3p targeting ribonucleotide reductase regulatory subunit M2 inhibits the tumorigenesis of hepatocellular carcinoma by regulating the Wnt/β-catenin signaling pathway. Bioengineered 2022;13:12876-87. [PMID: 35609318 DOI: 10.1080/21655979.2022.2078026] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]