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Recent Advances in the Prediction of Subcellular Localization of Proteins and Related Topics
2022
Frontiers in Bioinformatics
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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 ...
Notably, deep learning-based methods for natural language processing have made great contributions. ...
DEEP LEARNING AND LANGUAGE MODEL-BASED METHODS As noted above, the prediction of protein subcellular localization has always been a playground where the latest machine learning algorithms are introduced ...
doi:10.3389/fbinf.2022.910531
fatcat:54hro2t225hutf7wstpik3w7ca
SAWRPI: A Stacking Ensemble Framework With Adaptive Weight for Predicting ncRNA-Protein Interactions Using Sequence Information
2022
Frontiers in Genetics
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
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More specifically, the raw features of protein and ncRNA are firstly extracted through the k-mer sparse matrix with SVD reduction and learning nucleic acid symbols by natural language processing with local ...
However, these methods may be not available to all RNAs and proteins, particularly processing new RNAs and proteins. Additionally, most of them cannot process well with long sequence. ...
C., and Li, X. (2021). iDeepSubMito: Identification of Protein Submitochondrial Localization with Deep Learning. ...
doi:10.3389/fgene.2022.839540
pmid:35360836
pmcid:PMC8963817
fatcat:j6xzjby7dvglrls5jetjyfha4a