Self-supervised learning of cell type specificity from immunohistochemical images.

ABSTRACT:

Motivation

Advances in bioimaging now permit in situ proteomic characterization of cell-cell interactions in complex tissues, with important applications across a spectrum of biological problems from development to disease. These methods depend on selection of antibodies targeting proteins that are expressed specifically in particular cell types. Candidate marker proteins are often identified from single-cell transcriptomic data, with variable rates of success, in part due to divergence between expression levels of proteins and the genes that encode them. In principle, marker identification could be improved by using existing databases of immunohistochemistry for thousands of antibodies in human tissue, such as the Human Protein Atlas. However, these data lack detailed annotations

SUBMITTER: Murphy M 

PROVIDER: S-EPMC9235491 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature