Non-linear models based on simple topological indices to identify RNase III protein members

Journal of Theoretical Biology

Volumn 273, Issue 1, 2011, Pages 167-178

  Agüero Chapin, Guillermin ^a,b   de la Riva, Gustavo A ^c   Molina Ruiz, Reinaldo ^b   Sánchez Rodríguez, Aminael ^d   Pérez Machado, Gisselle ^b   Vasconcelos, Vítor ^a,e   Antunes, Agostinho ^a  

^a UNIVERSITY OF PORTO   (Portugal)

^b CENTRAL UNIVERSITY OF LAS VILLAS   (Cuba)

^c Instituto Superior Tecnológico de Irapuato ITESI   (Mexico)

^d UNIVERSITY OF LEUVEN   (Belgium)

^e UNIVERSITY OF PORTO   (Portugal)

Author keywords

Alignment free models; Artificial neural networks; Clustering; Decision tree models; Spectral moments

Indexed keywords

RIBONUCLEASE III;

AMINO ACID; ARTIFICIAL NEURAL NETWORK; HOMOLOGY; NONLINEARITY; NUMERICAL MODEL; PROTEIN; RNA; TOPOLOGY;

ACCURACY; AMINO ACID COMPOSITION; AMINO ACID SEQUENCE; ARTICLE; ARTIFICIAL NEURAL NETWORK; CLASSIFICATION; CLASSIFIER; CLUSTER ANALYSIS; CONTROLLED STUDY; DECISION TREE; ESCHERICHIA COLI; HIDDEN MARKOV MODEL; HYDROPHOBICITY; INTERMETHOD COMPARISON; NONHUMAN; NONLINEAR SYSTEM; NUCLEOTIDE SEQUENCE; PREDICTION; PRIORITY JOURNAL; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS; SEQUENCE HOMOLOGY;

AMINO ACID SEQUENCE; DECISION TREES; ENZYME ASSAYS; ESCHERICHIA COLI; MARKOV CHAINS; MOLECULAR SEQUENCE DATA; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; PROTEIN CONFORMATION; RECOMBINANT PROTEINS; REPRODUCIBILITY OF RESULTS; RIBONUCLEASE III; ROC CURVE; SEQUENCE ALIGNMENT;

BACTERIA (MICROORGANISMS);

EID: 78651360965     PISSN: 00225193     EISSN: 10958541     Source Type: Journal    
DOI: 10.1016/j.jtbi.2010.12.019     Document Type: Article

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