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Cited by in F6Publishing
For: Zhang Y, Lei X, Pan Y, Pedrycz W. Prediction of disease-associated circRNAs via circRNA–disease pair graph and weighted nuclear norm minimization. Knowledge-Based Systems 2021;214:106694. [DOI: 10.1016/j.knosys.2020.106694] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Xu H, Pan H, Zheng J, Liu Q, Tong J. Dynamic penalty adaptive matrix machine for the intelligent detection of unbalanced faults in roller bearing. Knowledge-Based Systems 2022;247:108779. [DOI: 10.1016/j.knosys.2022.108779] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 2.0] [Reference Citation Analysis]
2 Bamunu Mudiyanselage T, Lei X, Senanayake N, Zhang Y, Pan Y. Predicting CircRNA disease associations using novel node classification and link prediction models on Graph Convolutional Networks. Methods 2021:S1046-2023(21)00248-6. [PMID: 34748953 DOI: 10.1016/j.ymeth.2021.10.008] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Pan Y, Lei X, Zhang Y. Association predictions of genomics, proteinomics, transcriptomics, microbiome, metabolomics, pathomics, radiomics, drug, symptoms, environment factor, and disease networks: A comprehensive approach. Med Res Rev 2021. [PMID: 34346083 DOI: 10.1002/med.21847] [Reference Citation Analysis]
4 Wu B, Li L, Cui Y, Zheng K. Cross-Adversarial Learning for Molecular Generation in Drug Design. Front Pharmacol 2022;12:827606. [DOI: 10.3389/fphar.2021.827606] [Reference Citation Analysis]