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swMATH22402MaRDI QIDQ34194

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Related Items (26)

Predicting Golgi-resident protein types using pseudo amino acid compositions: approaches with positional specific physicochemical properties ⋮ pSuc-Lys: predict lysine succinylation sites in proteins with PseAAC and ensemble random forest approach ⋮ iCDI-PseFpt: identify the channel-drug interaction in cellular networking with PseAAC and molecular fingerprints ⋮ Predicting anticancer peptides with Chou's pseudo amino acid composition and investigating their mutagenicity via ames test ⋮ IMem-2LSAAC: a two-level model for discrimination of membrane proteins and their types by extending the notion of SAAC into Chou's pseudo amino acid composition ⋮ Naïve Bayes classifier with feature selection to identify phage virion proteins ⋮ Protein fold recognition by alignment of amino acid residues using kernelized dynamic time warping ⋮ Chou's pseudo amino acid composition improves sequence-based antifreeze protein prediction ⋮ Neural network and SVM classifiers accurately predict lipid binding proteins, irrespective of sequence homology ⋮ A set of descriptors for identifying the protein-drug interaction in cellular networking ⋮ pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC ⋮ iPPI-PseAAC(CGR): identify protein-protein interactions by incorporating chaos game representation into PseAAC ⋮ pSSbond-PseAAC: prediction of disulfide bonding sites by integration of PseAAC and statistical moments ⋮ MFSC: multi-voting based feature selection for classification of Golgi proteins by adopting the general form of Chou's PseAAC components ⋮ iRNA-PseKNC(2methyl): identify RNA 2'-O-methylation sites by convolution neural network and Chou's pseudo components ⋮ SPrenylC-PseAAC: a sequence-based model developed via Chou's 5-steps rule and general PseAAC for identifying S-prenylation sites in proteins ⋮ Dforml(KNN)-PseAAC: detecting formylation sites from protein sequences using K-nearest neighbor algorithm via Chou's 5-step rule and pseudo components ⋮ Predicting protein subchloroplast locations with both single and multiple sites via three different modes of Chou's pseudo amino acid compositions ⋮ Discriminating bioluminescent proteins by incorporating average chemical shift and evolutionary information into the general form of Chou's pseudo amino acid composition ⋮ Prediction of Golgi-resident protein types using general form of Chou's pseudo-amino acid compositions: approaches with minimal redundancy maximal relevance feature selection ⋮ Machine learning approaches for discrimination of extracellular matrix proteins using hybrid feature space ⋮ Prediction of protein structure classes by incorporating different protein descriptors into general Chou's pseudo amino acid composition ⋮ Classification of membrane protein types using voting feature interval in combination with Chou's pseudo amino acid composition ⋮ iLM-2L: a two-level predictor for identifying protein lysine methylation sites and their methylation degrees by incorporating K-gap amino acid pairs into Chou's general PseAAC ⋮ Prediction of \(\beta\)-lactamase and its class by Chou's pseudo-amino acid composition and support vector machine ⋮ Discrimination of acidic and alkaline enzyme using Chou's pseudo amino acid composition in conjunction with probabilistic neural network model

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