Access the full text.
Sign up today, get DeepDyve free for 14 days.
Qing-Bin Gao, Zheng-Zhi Wang, C. Yan, Yao-Hua Du (2005)
Prediction of protein subcellular location using a combined feature of sequenceFEBS Letters, 579
B. Schh, K. Sung, C. Burges, F. Girosi, P. Ogi, T. Poggio, V. Vapnik (1997)
Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classi
Kuo-Chen Chou, Chun-Ting Zhang (1995)
Prediction of protein structural classes.Critical reviews in biochemistry and molecular biology, 30 4
B Scholkopf (1997)
2758IEEE Trans Sign Proc, 45
H. Delacour, A. Servonnet, A. Perrot, J. Vigezzi, J. Ramirez (2005)
La courbe ROC (receiver operating characteristic) : principes et principales applications en biologie cliniqueAnnales De Biologie Clinique, 63
K. Chou (2001)
Prediction of signal peptides using scaled windowPeptides, 22
K. Chou (2000)
Prediction of tight turns and their types in proteins.Analytical biochemistry, 286 1
KC Chou, CT Zhang (1995)
Review: prediction of protein structural classesCrit Rev Biochem Mol Biol, 30
H Delacour (2005)
145Ann Biol Clin (Paris), 63
Yuhai Wu (2021)
Statistical Learning TheoryTechnometrics, 41
PY Chou (1978)
45Adv Enzymol Rel Subjects Biochem, 47
K. Chou (2002)
Prediction of protein signal sequences.Current protein & peptide science, 3 6
Chun-Ting Zhang, K. Chou (1994)
An alternate-subsite-coupled model for predicting HIV protease cleavage sites in proteins.Protein engineering, 7 1
K. Chou, Hongbin Shen (2006)
Hum-PLoc: a novel ensemble classifier for predicting human protein subcellular localization.Biochemical and biophysical research communications, 347 1
A. Alix (1999)
Predictive estimation of protein linear epitopes by using the program PEOPLE.Vaccine, 18 3-4
Guo-Ping Zhou (1998)
An Intriguing Controversy over Protein Structural Class PredictionJournal of Protein Chemistry, 17
M. Odorico, J. Pellequer (2003)
BEPITOPE: predicting the location of continuous epitopes and patterns in proteinsJournal of Molecular Recognition, 16
K. Chou, Hongbin Shen (2006)
Predicting eukaryotic protein subcellular location by fusing optimized evidence-theoretic K-Nearest Neighbor classifiers.Journal of proteome research, 5 8
K. Chou (1996)
Prediction of human immunodeficiency virus protease cleavage sites in proteins.Analytical biochemistry, 233 1
KC Chou (1997b)
120J Peptide Res, 49
KC Chou (2000)
Review: prediction of tight turns and their types in proteinsAnal Biochem, 286
KC Chou, JR Blinn (1997)
Classification and prediction of beta-turn typesJ Protein Chem, 16
KC Chou (1997a)
Prediction and classification of alpha-turn typesBiopolymers, 42
S. Saha, M. Bhasin, G. Raghava (2005)
Bcipep: A database of B-cell epitopesBMC Genomics, 6
H Delacour, A Servonnet, A Perrot, JF Vigezzi, JM Ramirez (2005)
ROC (receiver operating characteristics) curve: principles and application in biologyAnn Biol Clin (Paris), 63
Zhi-Ping Feng (2001)
Prediction of the subcellular location of prokaryotic proteins based on a new representation of the amino acid composition.Biopolymers, 58 5
K. Chou (1997)
Prediction and classification of α‐turn typesBiopolymers, 42
X. Xiao, Shihuang Shao, Yongsheng Ding, Z. Huang, Z. Huang, Y. Huang, Kuo-Chen Chou (2005)
Using complexity measure factor to predict protein subcellular locationAmino Acids, 28
K. Chou, J. Blinn (1997)
Classification and Prediction of β-Turn TypesJournal of Protein Chemistry, 16
K. Chou (1993)
A vectorized sequence-coupling model for predicting HIV protease cleavage sites in proteins.The Journal of biological chemistry, 268 23
W Liu, KC Chou (1999)
Protein secondary structural content predictionProtein Eng, 12
KC Chou (2002)
Review: prediction of protein signal sequencesCurr Protein Peptide Sci, 3
Guo-Ping Zhou, K. Doctor (2002)
Subcellular location prediction of apoptosis proteinsProteins: Structure, 50
P. Karplus, G. Schulz (1985)
Prediction of chain flexibility in proteinsNaturwissenschaften, 72
Z. Wen, M. Li, Y. Li, Y. Guo, K. Wang (2007)
Delaunay triangulation with partial least squares projection to latent structures: a model for G-protein coupled receptors classification and fast structure recognitionAmino Acids, 32
K. Chou (2001)
Using subsite coupling to predict signal peptides.Protein engineering, 14 2
KC Chou (1997b)
Prediction of beta-turns in proteinsJ Peptide Res, 49
A. Kolaskar, P. Tongaonkar (1990)
A semi‐empirical method for prediction of antigenic determinants on protein antigensFEBS Letters, 276
J. Söllner, B. Mayer (2006)
Machine learning approaches for prediction of linear B‐cell epitopes on proteinsJournal of Molecular Recognition, 19
X.-D. Sun, R. Huang (2006)
Prediction of protein structural classes using support vector machinesAmino Acids, 30
Yan-Zhi Guo, Menglong Li, Menglong Li, Minchun Lu, Zhining Wen, Zhining Wen, Ke-long Wang, Gongbing Li, J. Wu (2006)
Classifying G protein-coupled receptors and nuclear receptors on the basis of protein power spectrum from fast Fourier transformAmino Acids, 30
J. Parker, D. Guo, R. Hodges (1986)
New hydrophilicity scale derived from high-performance liquid chromatography peptide retention data: correlation of predicted surface residues with antigenicity and X-ray-derived accessible sites.Biochemistry, 25 19
E. Emini, J. Hughes, D. Perlow, J. Boger (1985)
Induction of hepatitis A virus-neutralizing antibody by a virus-specific synthetic peptideJournal of Virology, 55
Y. Gao, Shihuang Shao, Xuan Xiao, Yongsheng Ding, Y. Huang, Zheng-De Huang, Kuo-Chen Chou (2005)
Using pseudo amino acid composition to predict protein subcellular location: Approached with Lyapunov index, Bessel function, and Chebyshev filterAmino Acids, 28
J. Söllner (2006)
Selection and combination of machine learning classifiers for prediction of linear B‐cell epitopes on proteinsJournal of Molecular Recognition, 19
K. Chou (1995)
A sequence‐coupled vector‐projection model for predicting the specificity of GalNAc‐transferaseProtein Science, 4
K. Chou (1999)
Using Pair-Coupled Amino Acid Composition to Predict Protein Secondary Structure ContentJournal of Protein Chemistry, 18
K. Chou, Chun-Ting Zhang (1993)
Studies on the specificity of HIV protease: An application of Markov chain theoryJournal of Protein Chemistry, 12
Wei‐Min Liu, K. Chou (1999)
Prediction of protein secondary structure content.Protein engineering, 12 12
Shao-Wu Zhang, Q. Pan, H. Zhang, Z.-C. Shao, Jian-Yu Shi (2006)
Prediction of protein homo-oligomer types by pseudo amino acid composition: Approached with an improved feature extraction and Naive Bayes Feature FusionAmino Acids, 30
Youfang Cao, Shi Liu, Lida Zhang, J. Qin, Jiang Wang, K. Tang (2006)
Prediction of protein structural class with Rough SetsBMC Bioinformatics, 7
KC Chou (1996)
Review: prediction of HIV protease cleavage sites in proteinsAnal Biochem, 233
PA Karplus, GE Schulz (1985)
Prediction of chain flexibility in proteins – a tool for the selection of peptide antigensNaturwissenschaften, 72
PY Chou, GD Fasman (1978)
Prediction of secondary structure of proteins from amino acid sequencesAdv Enzymol Rel Subjects Biochem, 47
M. Blythe, D. Flower (2005)
Benchmarking B cell epitope prediction: Underperformance of existing methodsProtein Science, 14
KC Chou (1993)
16938J Biol Chem, 268
Chao Chen, Xibin Zhou, Yuanxin Tian, Xiaoyong Zou, Pei-xiang Cai (2006)
Predicting protein structural class with pseudo-amino acid composition and support vector machine fusion network.Analytical biochemistry, 357 1
Hui Liu, Jie Yang, Jianghuai Ling, K. Chou (2005)
Prediction of protein signal sequences and their cleavage sites by statistical rulers.Biochemical and biophysical research communications, 338 2
Identification of antigenic sites on proteins is of vital importance for developing synthetic peptide vaccines, immunodiagnostic tests and antibody production. Currently, most of the prediction algorithms rely on amino acid propensity scales using a sliding window approach. These methods are oversimplified and yield poor predicted results in practice. In this paper, a novel scale, called the amino acid pair (AAP) antigenicity scale, is proposed that is based on the finding that B-cell epitopes favor particular AAPs. It is demonstrated that, using SVM (support vector machine) classifier, the AAP antigenicity scale approach has much better performance than the existing scales based on the single amino acid propensity. The AAP antigenicity scale can reflect some special sequence-coupled feature in the B-cell epitopes, which is the essence why the new approach is superior to the existing ones. It is anticipated that with the continuous increase of the known epitope data, the power of the AAP antigenicity scale approach will be further enhanced.
Amino Acids – Springer Journals
Published: Jan 26, 2007
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.