Data for: Prediction of cytotoxic T lymphocyte epitope using sequence weighting and artificial neural network based EasyPred modeler

Published: 28 June 2020| Version 1 | DOI: 10.17632/dxz3dk3tcm.1
Contributors:
Satarudra Prakash Singh,
Garima Singh,
Bhartendu Mishra

Description

Prediction of T-cell epitopes are now obligatory steps in designing most of the biopharmaceuticals including vaccines. The present study involved the development of model for integrated prediction of cytotoxic T lymphocyte (CTL) epitopes using EasyPred modeler involving techniques position specific scoring matrices (PSSM) and artificial neural networks (ANN). A similarity reduced peptides dataset for 22 MHC class I molecules were used in training and evaluation of models by area under ROC (Aroc) values.

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