Hum-PLoc
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Software:38586
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Related Items (22)
Alignment-free prediction of mycobacterial DNA promoters based on pseudo-folding lattice network or star-graph topological indices ⋮ Prediction of protein structural classes by recurrence quantification analysis based on chaos game representation ⋮ A novel representation for apoptosis protein subcellular localization prediction using support vector machine ⋮ Multiclass cancer classification by support vector machines with class-wise optimized genes and probability estimates ⋮ Predicting plant protein subcellular multi-localization by Chou's PseAAC formulation based multi-label homolog knowledge transfer learning ⋮ Comprehensive comparative analysis and identification of RNA-binding protein domains: multi-class classification and feature selection ⋮ SubChlo: predicting protein subchloroplast locations with pseudo-amino acid composition and the evidence-theoretic \(K\)-nearest neighbor (ET-KNN) algorithm ⋮ Some remarks on protein attribute prediction and pseudo amino acid composition ⋮ Prediction of the subcellular location of apoptosis proteins ⋮ Novel scales based on hydrophobicity indices for secondary protein structure ⋮ Prediction of apoptosis protein subcellular location using improved hybrid approach and pseudo-amino acid composition ⋮ Using Chou's amphiphilic pseudo-amino acid composition and support vector machine for prediction of enzyme subfamily classes ⋮ CE-PLoc: An ensemble classifier for predicting protein subcellular locations by fusing different modes of pseudo amino acid composition ⋮ Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses ⋮ MFSC: multi-voting based feature selection for classification of Golgi proteins by adopting the general form of Chou's PseAAC components ⋮ \(\gamma\)-Turn types prediction in proteins using the support vector machines ⋮ Bi-PSSM: position specific scoring matrix based intelligent computational model for identification of mycobacterial membrane proteins ⋮ MemHyb: predicting membrane protein types by hybridizing SAAC and PSSM ⋮ Multi-kernel transfer learning based on Chou's PseAAC formulation for protein submitochondria localization ⋮ Adaptive compressive learning for prediction of protein-protein interactions from primary sequence ⋮ The modified Mahalanobis discriminant for predicting outer membrane proteins by using Chou's pseudo amino acid composition ⋮ Discrimination of acidic and alkaline enzyme using Chou's pseudo amino acid composition in conjunction with probabilistic neural network model
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