摘要
To establish a relation between an protein amino acid sequence and its tendencies to generate antibody response,and to investigate an improved in silico method for linear B-cell epitope（LBE）prediction.We present a sequence-based LBE predictor developed using deep maxout network（DMN）with dropout training techniques.A graphics processing unit（GPU）was used to reduce the training time of the model.A 10-fold cross-validation test on a large,non-redundant and
To establish a relation between an protein amino acid sequence and its tendencies to generate antibody response,and to investigate an improved in silico method for linear B-cell epitope（LBE）prediction.We present a sequence-based LBE predictor developed using deep maxout network（DMN）with dropout training techniques.A graphics processing unit（GPU）was used to reduce the training time of the model.A 10-fold cross-validation test on a large,non-redundant and
基金
supported by grant 2009CB918801 from the Ministry of Science and Technology of China
