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Workshop: 2nd Generative AI for Biology Workshop
Connecting Gene Expression and Tissue Morphology with Conditional Generative Models
Frederieke Lohmann · Alberto Valdeolivas · Jelica Vasiljević
Keywords: [ diffusion models ] [ contrastive learning ] [ gans ] [ digital pathology ] [ spatial transcriptomics ]
Inferring tissue morphology from gene expression remains widely unexplored. We present a two-stage conditional generative framework that leverages for the first time spatial transcriptomics data from the Visium HD platform to demonstrate this inference is feasible. Starting from near-whole-transcriptome profiles, the model synthesizes histology-like images that are plausible, as validated by FID scores and expert review. Model interpretation further reveals biologically meaningful links between specific genes and morphological patterns.