Journal ArticleDOI
Prediction of miRNA-disease associations based on Weighted K-Nearest known neighbors and network consistency projection
Ahmet Toprak,Esma Eryilmaz +1 more
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TLDR
Experimental results have shown that the proposed method can be used as a reliable computational model to reveal potential relationships between miRNAs and diseases.Abstract:
MicroRNAs (miRNA) are a type of non-coding RNA molecules that are effective on the formation and the progression of many different diseases. Various researches have reported that miRNAs play a majo...read more
Citations
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Journal ArticleDOI
Prediction of Potential MicroRNA–Disease Association Using Kernelized Bayesian Matrix Factorization
Ahmet Toprak,Esma Eryilmaz Dogan +1 more
TL;DR: KBMF technique can be used as a reliable computational model to infer possible miRNA-disease associations and the predictive reliability of this method was confirmed by the results.
Journal ArticleDOI
Identification and Analysis of microRNA-Disease Associations with Kernelized Bayesian Matrix Factorization
Ahmet Toprak,Esma Eryilmaz Doğan +1 more
TL;DR: KBMF can be used as a reliable computational model to reveal possible miRNA-disease relationships and was applied to case studies based on breast, lung, and colon neoplasms to prove the performance of KBMF technique.
Journal ArticleDOI
WVMDA: Predicting miRNA-Disease Association Based on Weighted Voting.
TL;DR: Wang et al. as discussed by the authors presented a weighted vote-based model to predict miRNA-disease association (WVMDA), which established credibility similarity based on the reliability of known associations and used it to improve the incomplete of original similarity.
Journal ArticleDOI
A Novel Method for miRNA-Disease Association Prediction based on Space Projection and Label Propagation (SPLPMDA)
TL;DR: Wang et al. as discussed by the authors proposed a new method for the identification of miRNA-disease associations based on space projection and label propagation (SPLPMDA), which was demonstrated using 5-fold cross-validation and LOOCV techniques.
References
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Prospective identification of tumorigenic breast cancer cells
Muhammad Al-Hajj,Max S. Wicha,Adalberto Benito-Hernandez,Sean J. Morrison,Sean J. Morrison,Michael F. Clarke +5 more
TL;DR: The ability to prospectively identify tumorigenic cancer cells will facilitate the elucidation of pathways that regulate their growth and survival and strategies designed to target this population may lead to more effective therapies.
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A microRNA expression signature of human solid tumors defines cancer gene targets
Stefano Volinia,George A. Calin,Chang Gong Liu,Stefan Ambs,Amelia Cimmino,Fabio Petrocca,Rosa Visone,Marilena V. Iorio,Claudia Roldo,Manuela Ferracin,Robyn L. Prueitt,Nozumu Yanaihara,Giovanni Lanza,Aldo Scarpa,Andrea Vecchione,Massimo Negrini,Curtis C. Harris,Carlo M. Croce +17 more
TL;DR: The results indicate that miRNAs are extensively involved in cancer pathogenesis of solid tumors and support their function as either dominant or recessive cancer genes.
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miRBase: annotating high confidence microRNAs using deep sequencing data.
Ana Kozomara,Sam Griffiths-Jones +1 more
TL;DR: An update of the miRBase database is described, including the collation and use of deep sequencing data sets to assign levels of confidence to miR base entries, and a high confidence subset of miR Base entries are provided, based on the pattern of mapped reads.
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