Using artificially generated spectral data to improve protein secondary structure prediction from Fourier transform infrared spectra of proteins

Analytical Biochemistry

Volumn 332, Issue 2, 2004, Pages 238-244

  Severcan, Mete ^a   Haris, Parvez I ^b   Severcan, Feride ^a  

^a MIDDLE EAST TECHNICAL UNIVERSITY   (Turkey)

^b DE MONTFORT UNIVERSITY   (United Kingdom)

Author keywords

FTIR; Neural networks; Protein; Secondary structure prediction; Spectroscopy

Indexed keywords

BAYESIAN NETWORKS; FORECASTING; MAXIMUM LIKELIHOOD ESTIMATION; NEURAL NETWORKS; PROTEINS; SPECTROSCOPY;

BAYESIAN REGULARIZATION; FOURIER TRANSFORM INFRARED SPECTRA; FTIR; GENERALIZATION ABILITY; MAXIMUM LIKELIHOOD ESTIMATION METHOD; PROTEIN SECONDARY-STRUCTURE PREDICTION; SECONDARY STRUCTURE PREDICTION; STANDARD ERROR OF PREDICTION;

FOURIER TRANSFORM INFRARED SPECTROSCOPY;

ALPHA HELIX; ANALYTIC METHOD; ARTICLE; ARTIFICIAL NEURAL NETWORK; BAYES THEOREM; BETA SHEET; INFRARED SPECTROSCOPY; PREDICTION; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN STRUCTURE;

EID: 8444246271     PISSN: 00032697     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ab.2004.06.030     Document Type: Article

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