Prediction of microbe–drug associations based on a modified graph attention variational autoencoder and random forest

The identification of microbe-drug associations can greatly facilitate drug research and development. Traditional methods for screening microbe-drug associations are time-consuming, manpower-intensive, and costly to conduct, so computational methods are a good alternative. However, most of them igno...

Celý popis

Podrobná bibliografie

Vydáno v:	Frontiers in microbiology Ročník 15; s. 1394302
Hlavní autoři:	Wang, Bo, Ma, Fangjian, Du, Xiaoxin, Zhang, Guangda, Li, Jingyou
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Switzerland Frontiers Media S.A 31.05.2024
Témata:	computational prediction model graph attention network microbe–drug association prediction Microbiology modified graph convolutional neural network random forest classifier variational autoencoder graph attention network computational prediction model microbe–drug association prediction random forest classifier variational autoencoder modified graph convolutional neural network
ISSN:	1664-302X, 1664-302X
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!