MPCLCDA: predicting circRNA–disease associations by using automatically selected meta-path and contrastive learning
W Liu, T Tang, X Lu, X Fu, Y Yang… - Briefings in …, 2023 - academic.oup.com
Circular RNA (circRNA) is closely associated with human diseases. Accordingly, identifying
the associations between human diseases and circRNA can help in disease prevention …
the associations between human diseases and circRNA can help in disease prevention …
GCFMCL: predicting miRNA-drug sensitivity using graph collaborative filtering and multi-view contrastive learning
Studies have shown that the mechanism of action of many drugs is related to miRNA. In-
depth research on the relationship between miRNA and drugs can provide theoretical …
depth research on the relationship between miRNA and drugs can provide theoretical …
NSRGRN: a network structure refinement method for gene regulatory network inference
The elucidation of gene regulatory networks (GRNs) is one of the central challenges of
systems biology, which is crucial for understanding pathogenesis and curing diseases …
systems biology, which is crucial for understanding pathogenesis and curing diseases …
Dynamic network link prediction with node representation learning from graph convolutional networks
P Mei, YH Zhao - Scientific Reports, 2024 - nature.com
Dynamic network link prediction is extensively applicable in various scenarios, and it has
progressively emerged as a focal point in data mining research. The comprehensive and …
progressively emerged as a focal point in data mining research. The comprehensive and …
Headtailtransfer: an efficient sampling method to improve the performance of graph neural network method in predicting sparse ncrna–protein interactions
Noncoding RNA (ncRNA) is a functional RNA derived from DNA transcription, and most
transcribed genes are transcribed into ncRNA. ncRNA is not directly involved in the …
transcribed genes are transcribed into ncRNA. ncRNA is not directly involved in the …
Identification of key candidate genes for IgA nephropathy using machine learning and statistics based bioinformatics models
Abstract Immunoglobulin-A-nephropathy (IgAN) is a kidney disease caused by the
accumulation of IgAN deposits in the kidneys, which causes inflammation and damage to …
accumulation of IgAN deposits in the kidneys, which causes inflammation and damage to …
An efficient model for predicting human diseases through miRNA based on multiple-types of contrastive learning
Q Liao, X Fu, L Zhuo, H Chen - Frontiers in Microbiology, 2023 - frontiersin.org
Multiple studies have demonstrated that microRNA (miRNA) can be deeply involved in the
regulatory mechanism of human microbiota, thereby inducing disease. Developing effective …
regulatory mechanism of human microbiota, thereby inducing disease. Developing effective …
Prediction of miRNA-disease associations in microbes based on graph convolutional networks and autoencoders
Q Liao, Y Ye, Z Li, H Chen, L Zhuo - Frontiers in Microbiology, 2023 - frontiersin.org
MicroRNAs (miRNAs) are short RNA molecular fragments that regulate gene expression by
targeting and inhibiting the expression of specific RNAs. Due to the fact that microRNAs …
targeting and inhibiting the expression of specific RNAs. Due to the fact that microRNAs …
Identification and validation of prognostic signature genes of bladder cancer by integrating methylation and transcriptomic analysis
Being a frequent malignant tumor of the genitourinary system, Bladder Urothelial Carcinoma
(BLCA) has a poor prognosis. This study focused on identifying and validating prognostic …
(BLCA) has a poor prognosis. This study focused on identifying and validating prognostic …
A method to improve the prediction performance of cancer-gene association by screening negative training samples through gene network data
M Xu, NA Abdullah, AQM Sabri - Computational Biology and Chemistry, 2024 - Elsevier
This work focuses on data sampling in cancer-gene association prediction. Currently,
researchers are using machine learning methods to predict genes that are more likely to …
researchers are using machine learning methods to predict genes that are more likely to …