ArticleJournal of personalized medicine2022
MDMF: Predicting miRNA-Disease Association Based on Matrix Factorization with Disease Similarity Constraint.
Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.
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38 citing papers in PubMed.
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- Breast cancer homologous recombination deficiency prediction from pathological images with a sufficient and representative Transformer.NPJ precision oncology · 2025Article
- Deep learning-based computational approach for predicting ncRNAs-disease associations in metaplastic breast cancer diagnosis.BMC cancer · 2025Article
- Neighborhood-Regularized Matrix Factorization for lncRNA-Disease Association Identification.International journal of molecular sciences · 2025Article
- DGCLCMI: a deep graph collaboration learning method to predict circRNA-miRNA interactions.BMC biology · 2025Article
- DeepMethyGene: a deep-learning model to predict gene expression using DNA methylations.BMC bioinformatics · 2025Article
- Identification of UBE2N as a biomarker of Alzheimer's disease by combining WGCNA with machine learning algorithms.Scientific reports · 2025Article
- DeepWalk-Based Graph Embeddings for miRNA-Disease Association Prediction Using Deep Neural Network.Biomedicines · 2025Article
- MGATAF: multi-channel graph attention network with adaptive fusion for cancer-drug response prediction.BMC bioinformatics · 2025Article
- Establishing a GRU-GCN coordination-based prediction model for miRNA-disease associations.BMC genomic data · 2025Article
- Graph Convolutional Network with Neural Collaborative Filtering for Predicting miRNA-Disease Association.Biomedicines · 2025Article
- Mogroside V Promotes Osteogenic Differentiation of Bone Marrow Mesenchymal Stem Cells from Diabetic Mice by Altering MicroRNA Profiles.Combinatorial chemistry & high throughput screening · 2025Article
- A Novel KIF4A-related Model for Predicting Immunotherapy Response and Prognosis in Kidney Renal Clear Cell Carcinoma.Combinatorial chemistry & high throughput screening · 2025Article
- Network Pharmacology, Molecular Docking, and Experimental Validation of the Mechanism of Jeduxiaoliu Formula against Diffuse Large B-Cell Lymphoma.Combinatorial chemistry & high throughput screening · 2025Article
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Abstract
MicroRNAs (miRNAs) have drawn enormous attention owing to their significant roles in various biological processes, as well as in the pathogenesis of human diseases. Therefore, predicting miRNA-disease associations is a pivotal task for the early diagnosis and better understanding of disease pathogenesis. To date, numerous computational frameworks have been proposed to identify potential miRNA-disease associations without escalating the costs and time required for clinical experiments. In this regard, I propose a novel computational framework (MDMF) for identifying potential miRNA-disease associations using matrix factorization with a disease similarity constraint. To evaluate the performance of MDMF, I calculated the area under the ROC curve (AUCs) in the framework of global and local leave-one-out cross-validation (LOOCV). In conclusion, MDMF achieved reliable AUC values of 0.9147 and 0.8905 for global and local LOOCV, respectively, which was a significant improvement upon the previous methods. Additionally, case studies were conducted on two major human cancers (breast cancer and lung cancer) to validate the effectiveness of MDMF. Comprehensive experimental results demonstrate that MDMF not only discovers miRNA-disease associations efficiently but also deciphers the underlying roles of miRNAs in the pathogenesis of diseases at a system level.
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Registered trials
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