@article{open595,
          volume = {409},
          author = {Sudipto Saha and G.P.S. Raghava},
            note = {Book Title: Immunoinformatics : Predicting Immunogenicity In Silico
Copyright of this article belongs to Springer Science},
           title = {Prediction methods for B-cell epitopes.},
       publisher = {Springer Science},
         journal = {Methods in molecular biology (Clifton, N.J.)},
           pages = {387--94},
            year = {2007},
        keywords = { B-cell epitope - linear epitope - physico-chemical properties - flexibility - hydrophilicity - surface accessibility - turns - recurrent neural network - vaccine },
             url = {http://crdd.osdd.net/open/595/},
        abstract = {In this chapter, two prediction servers of linear B-cell epiotpes have been described; (i) BcePred, based on physico-chemical properties that include hydrophilicity, flexibility/mobility, accessibility, polarity, exposed surface, turns, and antigenicity and ii) ABCpred, based on recurrent neural network. Both of the servers assist in locating linear epitope regions in a protein.}
}