MULocDeep web service for protein localization prediction and visualization at subcellular and suborganellar levels

Author:

Jiang Yuexu1,Jiang Lei1,Akhil Chopparapu Sai1,Wang Duolin1,Zhang Ziyang1,Zhang Weinan1,Xu Dong1ORCID

Affiliation:

1. Department of Electrical Engineer and Computer Science, Christopher S. Bond Life Sciences Center, University of Missouri , Columbia , USA

Abstract

Abstract Predicting protein localization and understanding its mechanisms are critical in biology and pathology. In this context, we propose a new web application of MULocDeep with improved performance, result interpretation, and visualization. By transferring the original model into species-specific models, MULocDeep achieved competitive prediction performance at the subcellular level against other state-of-the-art methods. It uniquely provides a comprehensive localization prediction at the suborganellar level. Besides prediction, our web service quantifies the contribution of single amino acids to localization for individual proteins; for a group of proteins, common motifs or potential targeting-related regions can be derived. Furthermore, the visualizations of targeting mechanism analyses can be downloaded for publication-ready figures. The MULocDeep web service is available at https://www.mu-loc.org/.

Funder

National Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Genetics

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