Results 301 to 310 of about 1,906,656 (324)

Multi-view Multichannel Attention Graph Convolutional Network for miRNA-disease association prediction

Briefings Bioinform., 2021
MOTIVATION In recent years, a growing number of studies have proved that microRNAs (miRNAs) play significant roles in the development of human complex diseases.
Xinru Tang, Jiawei Luo, Cong Shen, Zihan Lai   +3 more
semanticscholar   +1 more source

A novel circRNA-miRNA association prediction model based on structural deep neural network embedding

Briefings Bioinform., 2022
A large amount of clinical evidence began to mount, showing that circular ribonucleic acids (RNAs; circRNAs) perform a very important function in complex diseases by participating in transcription and translation regulation of microRNA (miRNA) target ...
Lu-Xiang Guo, Zhuhong You, Lei Wang, Changqing Yu, Bowei Zhao, Zhong-Hao Ren, Jie Pan   +6 more
semanticscholar   +1 more source

NSECDA: Natural Semantic Enhancement for CircRNA-Disease Association Prediction

IEEE journal of biomedical and health informatics, 2022
Increasing evidence suggest that circRNA, as one of the most promising emerging biomarkers, has a very close relationship with diseases. Exploring the relationship between circRNA and diseases can provide novel perspective for diseases diagnosis and ...
Lei Wang, Leon Wong, Zhuhong You, Desheng Huang, Xiao-Rui Su, Bowei Zhao   +5 more
semanticscholar   +1 more source

Graph Neural Network with Self-Supervised Learning for Noncoding RNA-Drug Resistance Association Prediction

Journal of Chemical Information and Modeling, 2022
Noncoding RNA(ncRNA) is closely related to drug resistance. Identifying the association between ncRNA and drug resistance is of great significance for drug development.
Jingjing Zheng, Yurong Qian, Jie He, Zerui Kang, L. Deng   +4 more
semanticscholar   +1 more source

DeepMNE: Deep Multi-Network Embedding for lncRNA-Disease Association Prediction

IEEE journal of biomedical and health informatics, 2022
Long non-coding RNA (lncRNA) participates in various biological processes, hence its mutations and disorders play an important role in the pathogenesis of multiple human diseases.
Yingjun Ma
semanticscholar   +1 more source

Heterogeneous graph attention network based on meta-paths for lncRNA-disease association prediction

Briefings Bioinform., 2021
MOTIVATION Discovering long noncoding RNA (lncRNA)-disease associations is a fundamental and critical part in understanding disease etiology and pathogenesis.
Xiaosa Zhao, Xiaowei Zhao, Minghao Yin
semanticscholar   +1 more source

NMCMDA: neural multicategory MiRNA-disease association prediction

Briefings Bioinform., 2021
MOTIVATION There is growing evidence showing that the dysregulations of miRNAs cause diseases through various kinds of the underlying mechanism. Thus, predicting the multiple-category associations between microRNAs (miRNAs) and diseases plays an ...
Jingru Wang, Jin Li, Kun Yue, Li Wang, Yu-Hang Ma, Qing Li   +5 more
semanticscholar   +1 more source

A Semi-Supervised Learning Method for MiRNA-Disease Association Prediction Based on Variational Autoencoder

IEEE/ACM Transactions on Computational Biology & Bioinformatics, 2021
MicroRNAs (miRNAs) are a class of non-coding RNAs that play critical role in many biological processes, such as cell growth, development, differentiation and aging. Increasing studies have revealed that miRNAs are closely involved in many human diseases.
Cunmei Ji, Yutian Wang, Zhen Gao, Lei Li, Jiancheng Ni, C. Zheng   +5 more
semanticscholar   +1 more source

NCMCMDA: miRNA-disease association prediction through neighborhood constraint matrix completion

Briefings Bioinform., 2020
Emerging evidence shows that microRNAs (miRNAs) play a critical role in diverse fundamental and important biological processes associated with human diseases. Inferring potential disease related miRNAs and employing them as the biomarkers or drug targets
Xing Chen, Lian-Gang Sun, Yan Zhao
semanticscholar   +1 more source

BGMSDDA: a bipartite graph diffusion algorithm with multiple similarity integration for drug-disease association prediction.

Molecular Omics, 2021
Drug repositioning, a method that relies on the information from the original drug-disease association matrix, aims to identify new indications for existing drugs and is expected to greatly reduce the cost and time of drug development.
Guobo Xie, Jianming Li, Guosheng Gu, Yuping Sun, Zhiyi Lin, Yinting Zhu, Weiming Wang   +6 more
semanticscholar   +1 more source