Results 11 to 20 of about 1,906,656 (324)
Drug–disease association prediction with literature based multi-feature fusion
Frontiers in Pharmacology, 2023 Introduction: Exploring the potential efficacy of a drug is a valid approach for drug development with shorter development times and lower costs. Recently, several computational drug repositioning methods have been introduced to learn multi-features for ...
Hongyu Kang +6 more
doaj +2 more sources
Human Microbe-Disease Association Prediction Based on Adaptive Boosting
Frontiers in Microbiology, 2018 There are countless microbes in the human body, and they play various roles in the physiological process. There is growing evidence that microbes are closely associated with human diseases.
Li-Hong Peng +4 more
doaj +2 more sources
lncRNA-disease association prediction based on latent factor model and projection [PDF]
Scientific Reports, 2021 Computer aided research of lncRNA-disease association is an important way to study the development of lncRNA-disease. The correlation analysis of existing data, the establishment of prediction model, prediction of unknown lncRNA-disease association, can ...
Bo Wang +3 more
openalex +2 more sources
MHCLMDA: multihypergraph contrastive learning for miRNA-disease association prediction. [PDF]
Brief Bioinform, 2023 The correct prediction of disease-associated miRNAs plays an essential role in disease prevention and treatment. Current computational methods to predict disease-associated miRNAs construct different miRNA views and disease views based on various miRNA ...
Peng W, He Z, Dai W, Lan W.
europepmc +2 more sources
Similarity measures-based graph co-contrastive learning for drug–disease association prediction
Bioinformatics, 2023 Motivation An imperative step in drug discovery is the prediction of drug–disease associations (DDAs), which tries to uncover potential therapeutic possibilities for already validated drugs.
Zihao Gao +4 more
semanticscholar +1 more source
GCSENet: A GCN, CNN and SENet ensemble model for microRNA-disease association prediction
PLoS Comput. Biol., 2021 Recently, an increasing number of studies have demonstrated that miRNAs are involved in human diseases, indicating that miRNAs might be a potential pathogenic factor for various diseases.
Zhong Li +4 more
openalex +3 more sources
International Journal of Molecular Sciences, 2022 Genome-wide association studies (GWAS) can be used to infer genome intervals that are involved in genetic diseases. However, investigating a large number of putative mutations for GWAS is resource- and time-intensive.
Yoonbee Kim +2 more
semanticscholar +1 more source
Heterogeneous graph neural network for lncRNA-disease association prediction
Scientific Reports, 2022 Identifying lncRNA-disease associations is conducive to the diagnosis, treatment and prevention of diseases. Due to the expensive and time-consuming methods verified by biological experiments, prediction methods based on computational models have ...
Hong Shi +3 more
semanticscholar +1 more source
Frontiers in Pharmacology, 2022 MiRNAs can regulate genes encoding specific proteins which are related to the efficacy of drugs, and predicting miRNA-drug resistance associations is of great importance.
Y. Niu +3 more
semanticscholar +1 more source
Genomic prediction and quantitative trait locus discovery in a cassava training population constructed from multiple breeding stages [PDF]
, 2020 Open Access Article; Published online: 11 Dec 2019Assembly of a training population (TP) is an important component of effective genomic selection‐based breeding programs.
Egesi, C. +11 more
core +1 more source