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A SUPPORT VECTOR MACHINE APPROACH FOR PREDICTION OF T CELL EPITOPES
2005
Proceedings of the 3rd Asia-Pacific Bioinformatics Conference
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A new peptide encoding scheme is proposed to use with support vector machines for the direct recognition of T cell epitopes. ...
A procedure of feature selection is also introduced. The computational results demonstrate superior performance over previous techniques. ...
They would also like to express their gratitude to anonymous referees for useful comments. ...
doi:10.1142/9781860947322_0032
fatcat:mwabfzj3i5brpkcu6xl2vlrlim
Computational Methods in Linear B-cell Epitope Prediction
2013
International Journal of Computer Applications
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This paper reviews various approaches like amino acid scale based methods and machine learning methods used for the prediction of linear B-cell epitopes. ...
Since experimental methods of identifying epitopes are costly and time consuming, computational methods for prediction are desirable. ...
BayesB [29] is a Support Vector Machines (SVM) prediction model employing Bayes Feature Extraction to predict linear B-cell epitopes of diverse lengths .The length varies from 12 to 20. ...
doi:10.5120/10520-5498
fatcat:v3ey3xyayzdtjlskzxmfsttpgu
Computational Prediction of B Cell Epitopes from Antigen Sequences
[chapter]
2014
Msphere
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We review a comprehensive set of thirteen recent approaches that predict linear and four methods that predict conformational B-cell epitopes from the antigen sequences. ...
Efforts towards the development of method for the prediction of linear epitopes span over the last three decades, while only recently several predictors of conformational epitopes were released. ...
JG was supported by the Fundamental Research Funds for the Central Universities grant 65011491. ...
doi:10.1007/978-1-4939-1115-8_11
pmid:25048126
fatcat:lxep5wuwanfgrktm7wjban7aeq
On Predicting Conformational B-cell Epitopes: a Comparative Study and a New Model
2012
American Journal of Bioinformatics Research
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As a result of this study, we developed a novel computational method "CBCPRED" to predict conformational B-cell epitope residues from the target antigen structure by combining support vector machine model ...
In this paper, we have carried out a comparative study and discussions for different methods based on the two major computational approaches for predicting conformational B-cell epitopes: sequence-based ...
ACKNOWLEDGEMENTS It is a pleasure to thank Dr: Yasser EL-Manzalawy for his great support and help. ...
doi:10.5923/j.bioinformatics.20110101.02
fatcat:kfsgqavovrggnipig7a6vcgltq
Prediction of Antigenic Epitope Patches on Protein Surface Using Antigen Structure Information and Support Vector Machine
2012
American Journal of Bioinformatics Research
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The proposed method is a support vector machine based model to predict the epitope patches in the antigen structures by combining the accessible surface area and B-factor structural features. ...
It p rovides a new approach for the scientists to only use the predicted antigenic epitope surface patch from the target antigen structure in vaccine development rather than using the predicted epitope ...
ACKNOWLEDGEMENTS It is a pleasure to thank Dr: Yasser EL-Manzalawy for his great support and help. ...
doi:10.5923/j.bioinformatics.20120204.03
fatcat:kslgkuawc5aidkeo5gu4aqjyrq
Application of Support Vector Machines in Viral Biology
[chapter]
2019
Global Virology III: Virology in the 21st Century
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Support Vector Machines (SVM) is one such robust tool, based rigorously on statistical learning theory. SVM provides very high quality and robust solutions to classification and regression problems. ...
Several studies in virology employ high performance tools including SVM for identification of potentially important gene and protein functions. ...
Application of support
vector machines for
T-cell epitopes
prediction [64]
Purpose: T-cell epitope prediction
with an MHC I restricted T-cell
clone. ...
doi:10.1007/978-3-030-29022-1_12
fatcat:leaxfnxiuze2jbuyenwps7qcve
PREDICTING FLEXIBLE LENGTH LINEAR B-CELL EPITOPES
2008
Computational Systems Bioinformatics
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Therefore, computational tools for reliably predicting B-cell epitopes are highly desirable. We explore two machine learning approaches for predicting flexible length linear B-cell epitopes. ...
The second approach utilizes four different methods of mapping a variable length sequence into a fixed length feature vector. ...
Acknowledgments This work was supported in part by a doctoral fellowship from the Egyptian Government to Yasser EL-Manzalawy and a grant from the National Institutes of Health (GM066387) to Vasant Honavar ...
doi:10.1142/9781848162648_0011
fatcat:fr7xdueuybh5vjozubkb2r3ewa
Predicting Immunogenicity Risk in Biopharmaceuticals
2021
Symmetry
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for major histocompatibility complex (MHC) binding motifs, predicting T and B cell epitopes based on machine learning algorithms, molecular docking, and molecular dynamics simulations. ...
The complexity of the immune system manifests through numerous different mechanisms, which allows the use of different approaches for predicting the immunogenicity of biopharmaceuticals. ...
for predicting the subcellular localization of Gram-negative bacterial proteins based on support vector machine modules [30] . ...
doi:10.3390/sym13030388
fatcat:yfgas5oagrgflik46woqv6as2u
Predicting flexible length linear B-cell epitopes
2008
Computational systems bioinformatics. Computational Systems Bioinformatics Conference
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Therefore, computational tools for reliably predicting B-cell epitopes are highly desirable. We explore two machine learning approaches for predicting flexible length linear B-cell epitopes. ...
The second approach utilizes four different methods of mapping a variable length sequence into a fixed length feature vector. ...
Acknowledgments This work was supported in part by a doctoral fellowship from the Egyptian Government to Yasser EL-Manzalawy and a grant from the National Institutes of Health (GM066387) to Vasant Honavar ...
pmid:19642274
pmcid:PMC3400678
fatcat:nb6jdbej5zbvlpy2dvtwzmxaxi
Prediction of CTL epitopes using QM, SVM and ANN techniques
2004
Vaccine
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In brief this method allows prediction of CTL epitopes using QM, SVM, ANN approaches. The method also facilitates prediction of MHC restriction in predicted T cell epitopes. The method is available at ...
Most of the existing T cell epitope prediction methods are indirect methods that predict MHC class I binders instead of CTL epitopes. ...
Manoj Bhasin is a recipient of a fellowship from CSIR. This report has IMTECH communication No. 016/2003. ...
doi:10.1016/j.vaccine.2004.02.005
pmid:15297074
fatcat:icsmstvsm5hcxcqhoe2yzli44u
Epitope Predictions Indicate the Presence of Two Distinct Types of Epitope-Antibody-Reactivities Determined by Epitope Profiling of Intravenous Immunoglobulins
2013
PLoS ONE
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A webserver for predicting EAR of peptide sequences is available at www. sysmed-immun.eu/EAR. ...
Computational prediction of linear B cell epitopes was conducted using machine learning with an ensemble of classifiers in combination with position weight matrix (PWM) analysis. ...
Elke Schade for technical assistance.
Author Contributions ...
doi:10.1371/journal.pone.0078605
pmid:24244326
pmcid:PMC3823795
fatcat:d7uj5452zvehbjjb7avpc6g56y
Benchmarking Datasets from Malaria Cytotoxic T-cell Epitopes Using Machine Learning Approach
2021
Avicenna journal of medical biotechnology
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Conclusion: The study is the first in-silico study on benchmarking Plasmodium cytotoxic T cell epitope datasets using machine learning approach. ...
Machine learning classifiers were trained on epitope data using sequence features and comparison of amino acid physicochemical properties was done to yield a valid prediction model. ...
Anirban Chakraborty, Director of Nitte University Centre for Science Education and Research (NUCSER), Prof. Dr. ...
doi:10.18502/ajmb.v13i2.5527
pmid:34012524
pmcid:PMC8112139
fatcat:iwnyy5pvczcibaewadvedrff7e
Application of support vector machines for T-cell epitopes prediction
2003
Bioinformatics
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Results: For the first time we develop a support vector machine (SVM) for T-cell epitope prediction with an MHC type I restricted T-cell clone. ...
Deciphering the patterns of peptides that elicit a MHC restricted T-cell response is critical for vaccine development. ...
Approaches to identify T-cell epitopes based on the prediction of which peptides would be good binders for specific MHC molecules are not accurate, since a functional T-cell response requires adequate ...
doi:10.1093/bioinformatics/btg255
pmid:14555632
fatcat:otbruqiyqzcs7hzc2bvhucqowm
Fundamentals and Methods for T- and B-Cell Epitope Prediction
2017
Journal of Immunology Research
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Here, we analyze aspects of antigen recognition by T- and B-cells that are relevant for epitope prediction. ...
Subsequently, we provide a systematic and inclusive review of the most relevant B- and T-cell epitope prediction methods and tools, paying particular attention to their foundations. ...
Acknowledgments The authors wish to thank Inmunotek, SL and the Spanish Department of Science at MINECO for supporting the Immunomedicine group research through Grants SAF2006: 07879, SAF2009:08301, and ...
doi:10.1155/2017/2680160
pmid:29445754
pmcid:PMC5763123
fatcat:ybrdo4uyknerdbwictznmvris4
Machine Learning-Based Ensemble Model for Zika Virus T-Cell Epitope Prediction
2021
Journal of Healthcare Engineering
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The in silico machine-learning-based approach for ZIKV T-cell epitope prediction would save a lot of physical experimental time and efforts for speedy vaccine development compared to in vivo approaches ...
We hereby have trained a machine-learning-based computational model to predict novel ZIKV T-cell epitopes by employing physicochemical properties of amino acids. ...
Machine Learning Classifiers Used in the Current Study. Classifiers used for the prediction of ZIKV T-cell epitopes are listed in Table 4 . ...
doi:10.1155/2021/9591670
pmid:34631001
pmcid:PMC8500748
fatcat:utulldardzd27iyxmrotb5b3le
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