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

Kenta Nakai, Leyi Wei
2022 Frontiers in Bioinformatics  
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

Zhong-Hao Ren, Chang-Qing Yu, Li-Ping Li, Zhu-Hong You, Yong-Jian Guan, Yue-Chao Li, Jie Pan
2022 Frontiers in Genetics  
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