AtSubP-2.0: An integrated web server for the annotation of Arabidopsis proteome subcellular localization using deep learning.

ABSTRACT: The organization of subcellular components in a cell is critical for its function and studying cellular processes, protein-protein interactions, identifying potential drug targets, network analysis, and other systems biology mechanisms. Determining protein localization experimentally is time-consuming and expensive. Due to the need for meticulous experimentation, validation, and data analysis, computational methods provide a quick and accurate alternative. Arabidopsis thaliana, a beneficial model organism in plant biology, facilitates experimentation and applies to other plants. Predicting its proteins' subcellular localization can improve our understanding of cellular processes and have applications in crop improvement and biotechnology. We propose AtSubP-2.0, an extension of our previous

SUBMITTER: Duhan N 

PROVIDER: S-EPMC11807733 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature