iProt-Sub

swMATH27604MaRDI QIDQ39320

No author found.

Related Items (14)

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 ⋮ Predicting membrane protein types by incorporating a novel feature set into Chou's general PseAAC ⋮ Analysis and prediction of ion channel inhibitors by using feature selection and Chou's general pseudo amino acid composition ⋮ 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 ⋮ Prediction and functional analysis of prokaryote lysine acetylation site by incorporating six types of features into Chou's general 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 ⋮ Analysis and prediction of animal toxins by various Chou's pseudo components and reduced amino acid compositions ⋮ 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

This page was built for software: iProt-Sub