A deep learning method that identifies cellular heterogeneity using nanoscale nuclear features.

ABSTRACT: Cellular phenotypic heterogeneity is an important hallmark of many biological processes and understanding its origins remains a substantial challenge. This heterogeneity often reflects variations in the chromatin structure, influenced by factors such as viral infections and cancer, which dramatically reshape the cellular landscape. To address the challenge of identifying distinct cell states, we developed artificial intelligence of the nucleus (AINU), a deep learning method that can identify specific nuclear signatures at the nanoscale resolution. AINU can distinguish different cell states based on the spatial arrangement of core histone H3, RNA polymerase II or DNA from super-resolution microscopy images. With only a small number of images as the training data, AINU correctly identifies h

SUBMITTER: Carnevali D 

PROVIDER: S-EPMC11415298 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature