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

Mete Severcan; Parvez I. Haris; Feride Severcan

doi:10.1016/j.ab.2004.06.030

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

Analytical Biochemistry ◽

10.1016/j.ab.2004.06.030 ◽

2004 ◽

Vol 332 (2) ◽

pp. 238-244 ◽

Cited By ~ 34

Author(s):

Mete Severcan ◽

Parvez I. Haris ◽

Feride Severcan

Keyword(s):

Fourier Transform ◽

Secondary Structure ◽

Spectral Data ◽

Infrared Spectra ◽

Structure Prediction ◽

Secondary Structure Prediction ◽

Protein Secondary Structure ◽

Fourier Transform Infrared ◽

Protein Secondary Structure Prediction ◽

Fourier Transform Infrared Spectra

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Automatic amide I frequency selection for rapid quantification of protein secondary structure from Fourier transform infrared spectra of proteins

PROTEOMICS ◽

10.1002/1615-9861(200207)2:7<839::aid-prot839>3.0.co;2-l ◽

2002 ◽

Vol 2 (7) ◽

pp. 839 ◽

Cited By ~ 22

Author(s):

Joachim A. Hering ◽

Peter R. Innocent ◽

Parvez I. Haris

Keyword(s):

Fourier Transform ◽

Secondary Structure ◽

Infrared Spectra ◽

Protein Secondary Structure ◽

Fourier Transform Infrared ◽

Frequency Selection ◽

Fourier Transform Infrared Spectra ◽

Selection For ◽

Rapid Quantification

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Faculty Opinions recommendation of Protein secondary structure prediction using deep convolutional neural fields.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.726067888.793548469 ◽

2018 ◽

Author(s):

Patrice Koehl

Keyword(s):

Secondary Structure ◽

Structure Prediction ◽

Secondary Structure Prediction ◽

Protein Secondary Structure ◽

Neural Fields ◽

Protein Secondary Structure Prediction

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Identification and application of the concepts important for accurate and reliable protein secondary structure prediction

Protein Science ◽

10.1002/pro.5560051116 ◽

1996 ◽

Vol 5 (11) ◽

pp. 2298-2310 ◽

Cited By ~ 299

Author(s):

Ross D. King ◽

Michael J.E. Sternberg

Keyword(s):

Secondary Structure ◽

Structure Prediction ◽

Secondary Structure Prediction ◽

Protein Secondary Structure ◽

Protein Secondary Structure Prediction

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Protein Secondary Structure Prediction Using Support Vector Machines (SVMs)

2013 International Conference on Machine Intelligence and Research Advancement ◽

10.1109/icmira.2013.124 ◽

2013 ◽

Author(s):

Hitesh Shah

Keyword(s):

Support Vector Machines ◽

Secondary Structure ◽

Structure Prediction ◽

Secondary Structure Prediction ◽

Protein Secondary Structure ◽

Support Vector ◽

Protein Secondary Structure Prediction ◽

Vector Machines

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Protein Secondary Structure Prediction using Bayesian Inference method on Decision fusion algorithms

2007 IEEE International Parallel and Distributed Processing Symposium ◽

10.1109/ipdps.2007.370430 ◽

2007 ◽

Cited By ~ 1

Author(s):

Somasheker Akkaladevi ◽

Ajay K Katangur

Keyword(s):

Bayesian Inference ◽

Secondary Structure ◽

Structure Prediction ◽

Secondary Structure Prediction ◽

Protein Secondary Structure ◽

Decision Fusion ◽

Inference Method ◽

Protein Secondary Structure Prediction ◽

Bayesian Inference Method

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Capturing hydrophobic moment using spectral coherence for protein secondary structure prediction

2013 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) ◽

10.1109/cibcb.2013.6595403 ◽

2013 ◽

Author(s):

Pradeep Chowriappa ◽

Sumeet Dua

Keyword(s):

Secondary Structure ◽

Structure Prediction ◽

Secondary Structure Prediction ◽

Protein Secondary Structure ◽

Spectral Coherence ◽

Protein Secondary Structure Prediction ◽

Hydrophobic Moment

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A protein secondary structure prediction framework based on the Extreme Learning Machine

Neurocomputing ◽

10.1016/j.neucom.2008.01.016 ◽

2008 ◽

Vol 72 (1-3) ◽

pp. 262-268 ◽

Cited By ~ 95

Author(s):

Guoren Wang ◽

Yi Zhao ◽

Di Wang

Keyword(s):

Secondary Structure ◽

Extreme Learning Machine ◽

Structure Prediction ◽

Secondary Structure Prediction ◽

Protein Secondary Structure ◽

Protein Secondary Structure Prediction ◽

Learning Machine

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Improving protein secondary structure prediction with aligned homologous sequences

Protein Science ◽

10.1002/pro.5560050113 ◽

1996 ◽

Vol 5 (1) ◽

pp. 106-113 ◽

Cited By ~ 41

Author(s):

V. Di Francesco ◽

J. Garnier ◽

P.J. Munson

Keyword(s):

Secondary Structure ◽

Structure Prediction ◽

Secondary Structure Prediction ◽

Protein Secondary Structure ◽

Protein Secondary Structure Prediction ◽

Homologous Sequences

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Protein secondary structure prediction using rule induction from coverings

2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology ◽

10.1109/cibcb.2009.4925711 ◽

2009 ◽

Author(s):

Leong Lee ◽

Jennifer L. Leopold ◽

Ronald L. Frank ◽

Anne M. Maglia

Keyword(s):

Secondary Structure ◽

Structure Prediction ◽

Secondary Structure Prediction ◽

Protein Secondary Structure ◽

Rule Induction ◽

Protein Secondary Structure Prediction

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A new hybrid coding for protein secondary structure prediction based on primary structure similarity

Gene ◽

10.1016/j.gene.2017.03.011 ◽

2017 ◽

Vol 618 ◽

pp. 8-13 ◽

Cited By ~ 11

Author(s):

Zhong Li ◽

Jing Wang ◽

Shunpu Zhang ◽

Qifeng Zhang ◽

Wuming Wu

Keyword(s):

Secondary Structure ◽

Primary Structure ◽

Structure Prediction ◽

Secondary Structure Prediction ◽

Protein Secondary Structure ◽

Protein Secondary Structure Prediction ◽

Hybrid Coding ◽

Structure Similarity

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