Recent Advances in the Prediction of Subcellular Localization of Proteins and Related Topics

Overview

Journal Front Bioinform

Specialty Biology

Date 2022 Oct 28

PMID 36304291

Authors

Kenta Nakai

Leyi Wei

Affiliations

Soon will be listed here.

Abstract

Prediction of subcellular localization of proteins from their amino acid sequences has a long history in bioinformatics and is still actively developing, incorporating the latest advances in machine learning and proteomics. Notably, deep learning-based methods for natural language processing have made great contributions. Here, we review recent advances in the field as well as its related fields, such as subcellular proteomics and the prediction/recognition of subcellular localization from image data.

Citing Articles

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SCLpred-ECL: Subcellular Localization Prediction by Deep N-to-1 Convolutional Neural Networks.

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