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Descripción
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| Since the discovery of the regulatory function of microRNA miRNA, increased attention has focused on identifying the relationship between miRNA and disease. It has been suggested that computational method is an efficient way to identify potential disease-related miRNAs for further confirmation using biological experiments. In this paper, we first highlighted three limitations commonly associated with previous computational methods. To resolve these limitations, we established disease similarity subnetwork and miRNA similarity subnetwork by integrating multiple data sources, where the disease similarity is composed of disease semantic similarity and disease functional similarity, and the miRNA similarity is calculated using the miRNA-target gene and miRNA-lncRNA long non-coding RNA associations. Then, a heterogeneous network was constructed by connecting the disease | |
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Internacional
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Si |
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JCR del ISI
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Si |
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Título de la revista
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Ieee-Acm Transactions on Computational Biology And Bioinformatics |
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ISSN
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1545-5963 |
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Factor de impacto JCR
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1,955 |
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Información de impacto
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Volumen
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DOI
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Número de revista
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Desde la página
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905 |
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Hasta la página
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915 |
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Mes
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SIN MES |
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Ranking
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