Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/62658
Title: Dengue virus epitope prediction and selection
Authors: Feng, Yirui
Keywords: DRNTU::Engineering::Computer science and engineering::Data
DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences
Issue Date: 2015
Abstract: Dengue fever (DF) is a mosquito-borne tropical disease caused by the dengue virus (DENV). The mild form of DF vanishes in most of the cases but severe forms such as hemorrhagic fever (DHF) and dengue shock syndrome (DSS) could be life-threatening. DENV infection is endemic in over 100 countries, affecting between 50-100 million people each year in tropical and subtropical regions of the globe. Currently, DF is prevented and treated through various means of vector control, vaccine development, and antiviral drugs. This report is focused on selecting sequences to represent four serotypes of DENV (DENV-1, DENV-2, DENV-3, and DENV-4), understanding and using the existing tools to generate T-cell and B-cell epitope of dengue sequences. And then the novel technique is created to predict dengue epitopes by using artificial neural network. In addition, B-Cell epitopes conserved across all strains of all four serotypes discovered by the new techniques will be listed. Serotypes that are not presented in mouse and human will also be listed.
URI: http://hdl.handle.net/10356/62658
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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