BcePred: Prediction of Continuous B-Cell Epitopes in Antigenic Sequences Using Physico-chemical Properties

By Sudipto Saha, Gajendra P. Raghava. International Conference on Artificial Immune Systems, 2004

459 citations recorded by the source corpus.

Subfields: Microbiology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/6f2b4efb34f4482985c6fd99c9505e4801b7237f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Microbiology

1. Gajendra P. Raghava
2. Sudipto Saha

In Molecular Biology

1. Sudipto Saha
2. Gajendra P. Raghava
3. Irini A. Doytchinova
4. Ivan Dimitrov
5. Kuo-Chen Chou
6. Manoj Bhasin

Citations in the corpus

• Prediction of continuous B‐cell epitopes in an antigen using recurrent neural network (2006, methodology): “7% accuracy.(24) Blythe and Flower found underperformance of the existing 484 amino acid propensity scales while benchmarking B cell epitope prediction.”
• AlgPred: prediction of allergenic proteins and mapping of IgE epitopes (2006, background): “epitopes-based approach fails due to limited number of known epitopes and low accuracy of existing epitope prediction methods (23,24).”
• Predicting linear B-cell epitopes using string kernels (2008, unknown): “1985; Emini et al ., 1985; Parker et al ., 1986; Pellequer et al ., 1991; Pellequer et al ., 1993; Saha and Raghava, 2004), the training examples are windows of five or seven amino acids labeled according to whether the amino acid at the center of the window is included in a linear B-cell epitope…”