biostudies-literatureVerplaetse NNHGRI NIH HHSFonds Wetenschappelijk Onderzoek223https://www.ebi.ac.uk/biostudies/studies/S-EPMC12291258biostudies-literatureUnknown26(1)Moving from a one-size-fits-all to an individual approach in precision medicine requires a deeper understanding of disease molecular mechanisms. Especially in heterogeneous complex diseases such as inflammatory bowel disease (IBD), better molecular stratification will help select the correct therapy. For this, we build end-to-end biologically sparsified neural network architectures for IBD subtyping based on whole exome sequence representations with gene-level and variant-level resolution. By moving beyond univariate methods, we capitalize on the model's ability to extract complex molecular patterns to improve prediction. Model interpretation identifies the most predictive pathways, genes, and variants, uncovering important intestinal barrier, immunological, and microbiome factors.Genome biologyExplainable deep learning for stratified medicine in inflammatory bowel disease.PMC1229125812Y5623NU54 HG003067Moreau YRaimondi DFariselli PVerplaetse NfalseExplainable deep learning for stratified medicine in inflammatory bowel disease.Moving from a one-size-fits-all to an individual approach in precision medicine requires a deeper understanding of disease molecular mechanisms. Especially in heterogeneous complex diseases such as inflammatory bowel disease (IBD), better molecular stratification will help select the correct therapy. For this, we build end-to-end biologically sparsified neural network architectures for IBD subtyping based on whole exome sequence representations with gene-level and variant-level resolution. By moving beyond univariate methods, we capitalize on the model's ability to extract complex molecular patterns to improve prediction. Model interpretation identifies the most predictive pathways, genes, and variants, uncovering important intestinal barrier, immunological, and microbiome factors.2025-01-01T00:00:00Z2025 Jul2026-07-15T12:31:25.691Z2025-08-13T03:04:49.041ZS-EPMC122912584070801410.1186/s13059-025-03692-6