Prediction of protein structural classes by recurrence quantification analysis based on chaos game representation

DOI10.1016/j.jtbi.2008.12.027zbMath1400.92417OpenAlexW2113784134WikidataQ51853395 ScholiaQ51853395MaRDI QIDQ1617743

Jian-Yi Yang, Desheng Wang, Rui-Jie Zhang, Zhen-Ling Peng, V. V. Anh, Zu-Guo Yu

Publication date: 8 November 2018

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jtbi.2008.12.027

zbMATH Keywords

recurrence plotsjackknife testsequence homologyone-against-others

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bootstrap, jackknife and other resampling methods (62F40) Learning and adaptive systems in artificial intelligence (68T05) Applications of game theory (91A80) Protein sequences, DNA sequences (92D20)

Related Items (14)

Fractal approximation of chaos game representations using recurrent iterated function systems ⋮ Improving the prediction accuracy of protein structural class: approached with alternating word frequency and normalized Lempel-Ziv complexity ⋮ Predicting DNA binding proteins using support vector machine with hybrid fractal features ⋮ Prediction of protein structure classes using hybrid space of multi-profile Bayes and bi-gram probability feature spaces ⋮ Some remarks on protein attribute prediction and pseudo amino acid composition ⋮ Communities in the iron superoxide dismutase amino acid network ⋮ Spatial functional normal mixed effect approach for curve classification ⋮ Using the concept of Chou's pseudo amino acid composition for risk type prediction of human papillomaviruses ⋮ Similarity analysis for DNA sequences based on chaos game representation. Case study: the albumin ⋮ Identifying anticancer peptides by using a generalized chaos game representation ⋮ Wavelet-RKHS-based functional statistical classification ⋮ A new hybrid fractal algorithm for predicting thermophilic nucleotide sequences ⋮ Protein sequence complexity revisited. relationship with fractal 3D structure, topological and kinetic parameters ⋮ Fractal and complex network analyses of protein molecular dynamics

Uses Software

• Cell-PLoc
• Memtype-2L
• ProtIdent
• K2
• Signal-CF
• Signal-3L
• EzyPred
• Euk-mPLoc
• Hum-PLoc

Cites Work

• Unnamed Item
• Prediction of structural classes for protein sequences and domains--impact of prediction algorithms, sequence representation and homology, and test procedures on accuracy
• Prediction protein structural classes with pseudo-amino acid composition: approximate entropy and hydrophobicity pattern
• The modified Mahalanobis discriminant for predicting outer membrane proteins by using Chou's pseudo amino acid composition
• Predicting protein structural class based on multi-features fusion
• Enzymes/non-enzymes classification model complexity based on composition, sequence, 3D and topological indices
• Chaos game representation of protein sequences based on the detailed HP model and their multifractal and correlation analyses
• Using pseudo-amino acid composition and support vector machine to predict protein structural class
• Prediction of the subcellular location of apoptosis proteins
• 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

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