Updated review of advances in microRNAs and complex diseases: taxonomy, trends and challenges of computational models
Since the problem proposed in late 2000s, microRNA–disease association (MDA)
predictions have been implemented based on the data fusion paradigm. Integrating diverse …
predictions have been implemented based on the data fusion paradigm. Integrating diverse …
Updated review of advances in microRNAs and complex diseases: towards systematic evaluation of computational models
Currently, there exist no generally accepted strategies of evaluating computational models
for microRNA-disease associations (MDAs). Though K-fold cross validations and case …
for microRNA-disease associations (MDAs). Though K-fold cross validations and case …
HINGRL: predicting drug–disease associations with graph representation learning on heterogeneous information networks
Identifying new indications for drugs plays an essential role at many phases of drug
research and development. Computational methods are regarded as an effective way to …
research and development. Computational methods are regarded as an effective way to …
Updated review of advances in microRNAs and complex diseases: experimental results, databases, webservers and data fusion
MicroRNAs (miRNAs) are gene regulators involved in the pathogenesis of complex
diseases such as cancers, and thus serve as potential diagnostic markers and therapeutic …
diseases such as cancers, and thus serve as potential diagnostic markers and therapeutic …
Predicting miRNA–disease associations via learning multimodal networks and fusing mixed neighborhood information
Z Lou, Z Cheng, H Li, Z Teng, Y Liu… - Briefings in …, 2022 - academic.oup.com
Motivation In recent years, a large number of biological experiments have strongly shown
that miRNAs play an important role in understanding disease pathogenesis. The discovery …
that miRNAs play an important role in understanding disease pathogenesis. The discovery …
Predicting miRNA-disease associations using an ensemble learning framework with resampling method
Q Dai, Z Wang, Z Liu, X Duan, J Song… - Briefings in …, 2022 - academic.oup.com
Motivation: Accumulating evidences have indicated that microRNA (miRNA) plays a crucial
role in the pathogenesis and progression of various complex diseases. Inferring disease …
role in the pathogenesis and progression of various complex diseases. Inferring disease …
Predicting miRNA-disease associations via node-level attention graph auto-encoder
H Zhang, J Fang, Y Sun, G Xie, Z Lin… - IEEE/ACM Transactions …, 2022 - ieeexplore.ieee.org
Previous studies have confirmed microRNA (miRNA), small single-stranded non-coding
RNA, participates in various biological processes and plays vital roles in many complex …
RNA, participates in various biological processes and plays vital roles in many complex …
PDMDA: predicting deep-level miRNA–disease associations with graph neural networks and sequence features
Motivation Many studies have shown that microRNAs (miRNAs) play a key role in human
diseases. Meanwhile, traditional experimental methods for miRNA–disease association …
diseases. Meanwhile, traditional experimental methods for miRNA–disease association …
Explainable and programmable hypergraph convolutional network for imaging genetics data fusion
X Bi, S Luo, S Jiang, Y Wang, Z Xing, L Xu - Information Fusion, 2023 - Elsevier
Integrating multi-view information to gain a new understanding of complex disease like
Alzheimer's disease (AD) has great clinical value. Hypergraphs have unique advantages in …
Alzheimer's disease (AD) has great clinical value. Hypergraphs have unique advantages in …
GADRP: graph convolutional networks and autoencoders for cancer drug response prediction
H Wang, C Dai, Y Wen, X Wang, W Liu… - Briefings in …, 2023 - academic.oup.com
Drug response prediction in cancer cell lines is of great significance in personalized
medicine. In this study, we propose GADRP, a cancer drug response prediction model …
medicine. In this study, we propose GADRP, a cancer drug response prediction model …