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swMATH22413MaRDI QIDQ34205

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Related Items (27)

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 ⋮ Predicting protein submitochondrial locations by incorporating the pseudo-position specific scoring matrix into the general Chou's pseudo-amino acid composition ⋮ Identifying 5-methylcytosine sites in RNA sequence using composite encoding feature into Chou's PseKNC ⋮ 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 ⋮ Characterization of BioPlex network by topological properties ⋮ Prediction of metastasis in advanced colorectal carcinomas using CGH data ⋮ BlaPred: predicting and classifying \(\beta\)-lactamase using a 3-tier prediction system via Chou's general PseAAC ⋮ pLoc\_bal-mGneg: predict subcellular localization of Gram-negative bacterial proteins by quasi-balancing training dataset and general PseAAC ⋮ Identify Gram-negative bacterial secreted protein types by incorporating different modes of PSSM into Chou's general PseAAC via Kullback-Leibler divergence ⋮ Predicting structural classes of proteins by incorporating their global and local physicochemical and conformational properties into general Chou's PseAAC ⋮ iMethyl-STTNC: identification of N\(^6\)-methyladenosine sites by extending the idea of SAAC into Chou's PseAAC to formulate RNA sequences ⋮ Analysis and prediction of ion channel inhibitors by using feature selection and Chou's general pseudo amino acid composition ⋮ Effective DNA binding protein prediction by using key features via Chou's general PseAAC ⋮ iPPI-PseAAC(CGR): identify protein-protein interactions by incorporating chaos game representation into PseAAC ⋮ Fu-SulfPred: identification of protein S-sulfenylation sites by fusing forests via Chou's general PseAAC ⋮ MFSC: multi-voting based feature selection for classification of Golgi proteins by adopting the general form of Chou's PseAAC components ⋮ Predicting protein-protein interactions by fusing various Chou's pseudo components and using wavelet denoising approach ⋮ Prediction of interface residue based on the features of residue interaction network ⋮ Highly accurate prediction of protein self-interactions by incorporating the average block and PSSM information into the general PseAAC ⋮ Discriminate protein decoys from native by using a scoring function based on ubiquitous phi and psi angles computed for all atom ⋮ 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 ⋮ 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 ⋮ Massive datasets and machine learning for computational biomedicine: trends and challenges ⋮ iEnhancer-MFGBDT: Identifying enhancers and their strength by fusing multiple features and gradient boosting decision tree

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