Dual Convolutional Neural Network Based Method for Predicting Disease-Related miRNAs.

ABSTRACT: Identification of disease-related microRNAs (disease miRNAs) is helpful for understanding and exploring the etiology and pathogenesis of diseases. Most of recent methods predict disease miRNAs by integrating the similarities and associations of miRNAs and diseases. However, these methods fail to learn the deep features of the miRNA similarities, the disease similarities, and the miRNA⁻disease associations. We propose a dual convolutional neural network-based method for predicting candidate disease miRNAs and refer to it as CNNDMP. CNNDMP not only exploits the similarities and associations of miRNAs and diseases, but also captures the topology structures of the miRNA and disease networks. An embedding layer is constructed by combining the biological premises about the miRNA⁻disease associat

SUBMITTER: Xuan P 

PROVIDER: S-EPMC6321160 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature