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FMSM: a novel computational model for predicting potential miRNA biomarkers for various human diseases.
Sun, Yiwen; Zhu, Zexuan; You, Zhu-Hong; Zeng, Zijie; Huang, Zhi-An; Huang, Yu-An.
Afiliação
  • Sun Y; School of Medicine, Shenzhen University, Shenzhen, 518060, China.
  • Zhu Z; College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, China.
  • You ZH; Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Science, ürümqi, 830011, China.
  • Zeng Z; College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, 518060, China.
  • Huang ZA; Department of Computer Science, City University of Hong Kong, Hong Kong, 999077, China. huang_za@outlook.com.
  • Huang YA; Department of Computing, Hong Kong Polytechnic University, Hong Kong, 999077, China. yahaung1991@gmail.com.
BMC Syst Biol ; 12(Suppl 9): 121, 2018 12 31.
Article em En | MEDLINE | ID: mdl-30598090
BACKGROUND: MicroRNA (miRNA) plays a key role in regulation mechanism of human biological processes, including the development of disease and disorder. It is necessary to identify potential miRNA biomarkers for various human diseases. Computational prediction model is expected to accelerate the process of identification. RESULTS: Considering the limitations of previously proposed models, we present a novel computational model called FMSM. It infers latent miRNA biomarkers involved in the mechanism of various diseases based on the known miRNA-disease association network, miRNA expression similarity, disease semantic similarity and Gaussian interaction profile kernel similarity. FMSM achieves reliable prediction performance in 5-fold and leave-one-out cross validations with area under ROC curve (AUC) values of 0.9629+/- 0.0127 and 0.9433, respectively, which outperforms the state-of-the-art competitors and classical algorithms. In addition, 19 of top 25 predicted miRNAs have been validated to have associations with Colonic Neoplasms in case study. CONCLUSIONS: A factored miRNA similarity based model and miRNA expression similarity substantially contribute to the well-performing prediction. The list of the predicted most latent miRNA biomarkers of various human diseases is publicized. It is anticipated that FMSM could serve as a useful tool guiding the future experimental validation for those promising miRNA biomarker candidates.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Simulação por Computador / Marcadores Genéticos / Doença / Biologia Computacional / MicroRNAs Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Simulação por Computador / Marcadores Genéticos / Doença / Biologia Computacional / MicroRNAs Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2018 Tipo de documento: Article