Large-scale prediction and analysis of protein sub-mitochondrial localization with DeepMito.

ABSTRACT:

Background

The prediction of protein subcellular localization is a key step of the big effort towards protein functional annotation. Many computational methods exist to identify high-level protein subcellular compartments such as nucleus, cytoplasm or organelles. However, many organelles, like mitochondria, have their own internal compartmentalization. Knowing the precise location of a protein inside mitochondria is crucial for its accurate functional characterization. We recently developed DeepMito, a new method based on a 1-Dimensional Convolutional Neural Network (1D-CNN) architecture outperforming other similar approaches available in literature.

Results

Here, we explore the adoption of DeepMito for the large-scale annotation of four sub-mitochondrial localizations on mi

SUBMITTER: Savojardo C 

PROVIDER: S-EPMC7493403 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature