Fig. 1: AI-aided analysis for screening chemical candidates. | Experimental & Molecular Medicine

Fig. 1: AI-aided analysis for screening chemical candidates.

From: Transcriptome-based deep learning analysis identifies drug candidates targeting protein synthesis and autophagy for the treatment of muscle wasting disorder

Fig. 1

a Scheme of RNA sequencing and preprocessing. Transcript expression information from muscle tissues isolated from healthy individuals and patients afflicted with sarcopenia was processed and analyzed. The objective of this study was to identify potential drug candidates capable of rebalancing patients’ aberrant gene expression profiles toward a normal state. b Differentially expressed gene (DEG) selection: RNA expression data were collected from the muscle tissues of healthy hosts and cancer patients suffering from sarcopenia. c Scheme showing the drug-disease comparison. Comprehensive analysis of disease-associated DEGs in two different cachexia cohorts. Drug-induced DEGs were used to evaluate the efficacy of each drug against the target disease. d Schematic of the score ensemble: three distinct scores, derived from the enrichment test (ET), similarity test (ST), and contingency test (CT), were combined for further analysis.

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