Predicting the subcellular location of prokaryotic proteins with DeepLocPro

• DOI: 10.1093/bioinformatics/btae677
• Publication Date: 2024-11-14T13:56:11Z
• Authors: Jaime Moreno; Henrik Nielsen; Ole Winther; Felix Teufel

Abstract

Motivation Protein subcellular location prediction is a widely explored task in bioinformatics because of its importance in proteomics research. We propose DeepLocPro, an extension to the popular method DeepLoc, tailored specifically to archaeal and bacterial organisms.

Results DeepLocPro is a multiclass subcellular location prediction tool for prokaryotic proteins, trained on experimentally verified data curated from UniProt and PSORTdb. DeepLocPro compares favorably to the PSORTb 3.0 ensemble method, surpassing its performance across multiple metrics in our benchmark experiment.

Availability and implementation The DeepLocPro prediction tool is available online at https://ku.biolib.com/deeplocpro and https://services.healthtech.dtu.dk/services/DeepLocPro-1.0/.