LCASPMDA: a computational model for predicting potential microbe-drug associations based on learnable graph convolutional attention networks and self-paced iterative sampling ensemble
Zinuo Yang,
Lei Wang,
Xiangrui Zhang
et al.
Abstract:IntroductionNumerous studies show that microbes in the human body are very closely linked to the human host and can affect the human host by modulating the efficacy and toxicity of drugs. However, discovering potential microbe-drug associations through traditional wet labs is expensive and time-consuming, hence, it is important and necessary to develop effective computational models to detect possible microbe-drug associations.MethodsIn this manuscript, we proposed a new prediction model named LCASPMDA by comb… Show more
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