iRNA-AI
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Software:36195
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Related Items (26)
RBSURFpred: modeling protein accessible surface area in real and binary space using regularized and optimized regression ⋮ NucPosPred: predicting species-specific genomic nucleosome positioning via four different modes of general PseKNC ⋮ 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 ⋮ Sequence-based discrimination of protein-RNA interacting residues using a probabilistic approach ⋮ The preliminary efficacy evaluation of the CTLA-4-ig treatment against lupus nephritis through \textit{in-silico} analyses ⋮ Prediction of metastasis in advanced colorectal carcinomas using CGH data ⋮ Predicting apoptosis protein subcellular localization by integrating auto-cross correlation and PSSM into Chou's 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 ⋮ Large-scale frequent stem pattern mining in RNA families ⋮ 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 ⋮ \textit{In silico} analysis of \textit{plasmodium falciparum} CDPK5 protein through molecular modeling, docking and dynamics ⋮ 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 ⋮ Identifying N\(^6\)-methyladenosine sites using extreme gradient boosting system optimized by particle swarm optimizer ⋮ 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 ⋮ 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 ⋮ Bi-PSSM: position specific scoring matrix based intelligent computational model for identification of mycobacterial membrane proteins ⋮ Prediction of protein subcellular localization with oversampling approach and Chou's general PseAAC
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