Prediction of protein subcellular localization in single cells.

ABSTRACT: The subcellular localization of a protein is important for its function and interaction with other molecules, and its mislocalization is linked to numerous diseases. While atlas-scale efforts have been made to profile protein localization across various cell lines, existing datasets only contain limited pairs of proteins and cell lines which do not cover all human proteins. We present a method that uses both protein sequences and cellular landmark images to perform Predictions of Unseen Proteins' Subcellular localization (PUPS), which can generalize to both proteins and cell lines not used for model training. PUPS combines a protein language model and an image inpainting model to utilize both protein sequence and cellular images for protein localization p

SUBMITTER: Zhang X 

PROVIDER: S-EPMC11291118 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature