Additional file 1 of Machine learning based identification potential feature genes for prediction of drug efficacy in nonalcoholic steatohepatitis animal model

Supplementary Material 1. Fig. A.1. Showing the pathogenic pathways and processes involved in NAFLD/NASH genesis through the KEGG pathway database, Fig. A.2. showing the involvement of the biochemical-RNA signatures in pathogenic mechanisms (Hippo signaling, TGF-β signaling, TNF signaling pathway, apoptosis, oxidative stress, and inflammatory response) through the KEGG pathway database, and GeneCards database; Fig. A.3. Validation that our selected mRNAs are key regulatory genes in gut microbiota, Fig. A.4. Validation of the interaction between the selected mRNAs and the retrieved miRNAs from mirwalk3; Fig. A.5. Validation of the relation of the candidate miRNAs to pathogenic mechanisms such as Hippo signaling, and TGF-β signaling through DIANA tools mirPath 3; Fig. A.6. Validation of the interaction between the selected miRNAs and the retrieved lncRNAs from mirwalk3 and DIANA-LncBase; Table A.1. The detailed differentially expressed genes in NASH were retrieved from the gene chip datasets GSE164760, GSE24807, and GSE126848, Table A.2. List of primer assays; Table A.3. Histopathological scoring grid for NAFLD/NASH liver sections.