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Mini-review: Recent advances in post-translational modification site prediction based on deep learning.

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第一作者: Lingkuan,Meng
第一单位: Department of Computer Science, City University of Hong Kong, Hong Kong Special Administrative Region.;Department of Chemistry, City University of Hong Kong, Hong Kong Special Administrative Region.
作者: Lingkuan,Meng [1] ; Wai-Sum,Chan [2] ; Lei,Huang [2] ; Linjing,Liu [2] ; Xingjian,Chen [2] ; Weitong,Zhang [2] ; Fuzhou,Wang [2] ; Ke,Cheng [3] ; Hongyan,Sun [3] ; Ka-Chun,Wong [2]
作者单位: Department of Computer Science, City University of Hong Kong, Hong Kong Special Administrative Region.;Department of Chemistry, City University of Hong Kong, Hong Kong Special Administrative Region. [1] Department of Computer Science, City University of Hong Kong, Hong Kong Special Administrative Region. [2] Department of Chemistry, City University of Hong Kong, Hong Kong Special Administrative Region. [3]
关键词 AAindex, Amino acid indexATP, Adenosine triphosphateAUC, Area under curveAc, AcetylationBE, Binary encodingBLOSUM, Blocks substitution matrixBi-LSTM, Bidirectional LSTMCKSAAP, Composition of k-spaced amino acid PairsCNN, Convolutional neural networkCNNOH, CNN with the one-hot encodingCNNWE, CNN with the word-embedding encodingCNNrgb, CNN red green blueCV, Cross-validationDC-CNN, Densely connected convolutional neural networkDL, Deep learningDNNs, Deep neural networksDeep learningE. coli, Escherichia coliEBGW, Encoding based on grouped weightEGAAC, Enhanced grouped amino acids contentIG, Information gainK, LysineKNN, k nearest neighborLASSO, Least absolute shrinkage and selection operatorLSTM, Long short-term memoryLSTMWE, LSTM with the word-embedding encodingM.musculus, Mus musculusMDC, Modular densely connected convolutional networksMDCAN, Multilane dense convolutional attention networkML, Machine learningMLP, Multilayer perceptronMMI, Multivariate mutual informationMachine learningMass spectrometryNMBroto, Normalized Moreau-Broto autocorrelationP, ProlinePSP, PhosphoSitePlusPSSM, Position-specific scoring matrixPTM, Post-translational modificationsPh, PhosphorylationPost-translational modificationPredictionPseAAC, Pseudo-amino acid compositionR, ArginineRF, Random forestRNN, Recurrent neural networkROC, Receiver operating characteristicS, SerineS. typhimurium, Salmonella typhimuriumS.cerevisiae, Saccharomyces cerevisiaeSE, Squeeze and excitationSEV, Split to Equal ValidationST, Source and targetSUMO, Small ubiquitin-like modifierSVM, Support vector machinesT, ThreonineUb, UbiquitinationY, TyrosineZSL, Zero-shot learning
DOI 10.1016/j.csbj.2022.06.045
PMID 35860402
发布时间 2022-07-22
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Computational and structural biotechnology journal

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