DeepISO: deep learning-powered prediction of protein–protein interaction rewiring generated by alternative splicing
Abstract
Isoforms from the same gene can significantly rewire protein interaction networks, but proteome-wide computational evaluation of these effects remains challenging. In this work, we present DeepISO, a deep learning framework for predicting isoform-specific interactions. DeepISO integrates two graph convolutional neural networks and a random forest model via a logistic regression model. To the best of our knowledge, this is the first approach to jointly leverage AlphaFold-predicted structures and ESM2 language model embeddings for this task. Compared with state-of-the-art PPI prediction tools, DeepISO demonstrates superior performance.
Fields of Study & Subjects
Bioinformatics and Genomic Networks
Protein Structure and Dynamics
Machine Learning in Bioinformatics
Publication details
- Journal / source
- Genome biology
- Publisher
- Springer Science and Business Media LLC
- Volume
- 27
- Issue
- 1
- Publication date
- 27 March 2026
- Language
- EN