Predicting Protein Functions with Ensemble Deep Learning and Protein Language Models

Understanding protein functions enables deciphering cellular mechanisms and improving healthcare outcomes, from disease diagnosis to targeted therapy. We present GOMIX, an ensemble learning method for predicting the functions of newly discovered proteins, packaged within an easy-to-use web application. By combining seven complementary base predictors–including sequence homology and protein language models, GOMIX achieves competitive or state-of-the-art performance in the CAFA-3 challenge. Unlike existing solutions, GOMIX is entirely open-source, modular, and computationally low-resource. The code is publicly available at https://github.com/disi-unibo-nlp/gomix (MIT License).