Machine learning approaches for prediction of linear B‐cell epitopes on proteins

@article{Sllner2006MachineLA,
  title={Machine learning approaches for prediction of linear B‐cell epitopes on proteins},
  author={J. S{\"o}llner and B. Mayer},
  journal={Journal of Molecular Recognition},
  year={2006},
  volume={19}
}
Identification and characterization of antigenic determinants on proteins has received considerable attention utilizing both, experimental as well as computational methods. For computational routines mostly structural as well as physicochemical parameters have been utilized for predicting the antigenic propensity of protein sites. However, the performance of computational routines has been low when compared to experimental alternatives. 
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A novel encoding scheme which combines several groups of sequence-derived structural and physicochemical features, and support vector machine was used to construct the prediction models, and demonstrated better results than benchmark methods. Expand
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  • E. Roggen
  • Biology, Medicine
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TLDR
It is concluded that antigenicity is not described by physicochemical and structural characteristics of a protein alone, and molecular characteristics of the antigenic amino acids are required. Expand
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TLDR
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The recent advance of bioinformatics resources and tools in conformational B-cell epitope prediction, including databases, algorithms, web servers, and their applications in solving problems in related areas are reviewed. Expand
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TLDR
Recent advances in computational methods for B-cell epitope prediction are reviewed, some gaps in the current state of the art are identified, and some promising directions for improving the reliability of such methods are outlined. Expand
Computational Prediction of Conformational B-Cell Epitopes from Antigen Primary Structures by Ensemble Learning
TLDR
This paper explores various sequence-derived features, which have been observed to be associated with the location of epitopes or ever used in the similar tasks, and develops the ensemble model to predict conformational epitopes from antigen sequences. Expand
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TLDR
An overview of the important databases associated with the B-cell epitopes is presented and how to compile datasets for the development of B- cell epitope prediction tools is introduced. Expand
SVM-based prediction of linear B-cell epitopes using Bayes Feature Extraction
TLDR
A support vector machines (SVM) prediction model utilizing Bayes Feature Extraction was developed and showed that it was effective in discriminating epitopes from non-epitopes in benchmark datasets and annotated antigenic proteins. Expand
Hybrid methods for B-cell epitope prediction.
  • S. C. Caoili
  • Computer Science, Medicine
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TLDR
These tasks are considered together herein to clarify their close but often overlooked interrelationship, thereby providing a guide to their performance in mutual support of one another, with emphasis on key physicochemical and biological considerations that are relevant from an applications perspective. Expand
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