Context Is Part of the Signal: Two Studies in Computational Pathology and Functional Genomics
Published:
Modern biological machine learning increasingly relies on pretrained representations. A pathology foundation model can transform an image into rich embeddings, while a perturbation model can learn recurring transcriptional programs from large single-cell datasets. But representations alone do not always contain enough information to generalize reliably.