Mitochondrial proteins are physiologically active in different compartments and their aberrant localization contributes to the pathogenesis of human mitochondrial pathologies.

Here we present DeepMito, a novel method for predicting sub-mitochondrial localization and based on a convolutional neural network architecture to extract relevant patterns from primary features. Given an input protein, DeepMito is able to discriminate four different sub-mitochondrial compartments: outer membrane, inner membrane, intermembrane space and mitochondrial matrix.

More details on DeepMito can be found in the following paper:

Savojardo C, Bruciaferri N, Tartari G, Martelli PL, Casadio R. DeepMito: accurate prediction of protein submitochondrial localization using convolutional neural networks. Bioinformatics. 2019 Jun 20.

Submit your sequence(s)

Please, paste input FASTA sequences (max 200 sequences, max 100000 residues) in the area below:

Alternatively, select and upload a FASTA file: