DeepmRNALoc: A Novel Predictor of Eukaryotic mRNA Subcellular Localization Based on Deep Learning

Autor: Shihang Wang, Zhehan Shen, Taigang Liu, Wei Long, Linhua Jiang, Sihua Peng
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Molecules
Volume 28
Issue 5
Pages: 2284
ISSN: 1420-3049
DOI: 10.3390/molecules28052284
Popis: The subcellular localization of messenger RNA (mRNA) precisely controls where protein products are synthesized and where they function. However, obtaining an mRNA’s subcellular localization through wet-lab experiments is time-consuming and expensive, and many existing mRNA subcellular localization prediction algorithms need to be improved. In this study, a deep neural network-based eukaryotic mRNA subcellular location prediction method, DeepmRNALoc, was proposed, utilizing a two-stage feature extraction strategy that featured bimodal information splitting and fusing for the first stage and a VGGNet-like CNN module for the second stage. The five-fold cross-validation accuracies of DeepmRNALoc in the cytoplasm, endoplasmic reticulum, extracellular region, mitochondria, and nucleus were 0.895, 0.594, 0.308, 0.944, and 0.865, respectively, demonstrating that it outperforms existing models and techniques.
Databáze: OpenAIRE
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