DocumentCode
3773730
Title
EBVdb: a data mining system for knowledge discovery in Epstein-Barr virus with applications in T cell immunology and vaccinology
Author
Guang Lan Zhang;Lou Chitkushev;Derin B. Keskin;Ellis L. Reinherz;Vladimir Bruisic
Author_Institution
Department of Computer Science, Metropolitan College, Boston University, Boston, MA 02215, USA
fYear
2015
fDate
7/1/2015 12:00:00 AM
Firstpage
1
Lastpage
8
Abstract
As the first cancer-causing human virus identified, Epstein-Barr virus (EBV) has been implicated in the development of a wide range of B cell lymphoproliferative disorders, a subset of T/NK cell lymphomas, and post-transplant lymphoproliferative disorders. We made use of the immunological data on EBV available through publications, technical reports, and databases and constructed Epstein-Barr virus T cell Antigen Database (EBVdb). EBVdb contains 2622 curated antigen entries of EBV antigenic proteins, 610 verified T cell epitopes and 26 verified HLA ligands. The data were subject to extensive quality control (redundancy elimination, error detection, and vocabulary consolidation). A set of computational tools for in-depth analysis, such as sequence comparison using BLAST search, multiple alignments of antigens, T cell epitope/HLA ligand visualization, T cell epitope/HLA ligand conservation analysis, and sequence variability analysis, have been integrated within the EBVdb. Predicted Class I and Class II HLA-binding peptides for 15 common HLA alleles are included in this database as putative targets. EBVdb seamlessly integrates curated data and information with tailored analysis tools to facilitate data mining for EBV vaccinology and immunology. EBVdb is a unique data source providing a comprehensive list of EBV antigens and peptides and is publicly available at http://projects.met-hilab.org/ebv/.
Keywords
"Immune system","Proteins","Databases","Data mining","Vaccines","Cancer","Peptides"
Publisher
ieee
Conference_Titel
Artificial Immune Systems (AIS), 2015 International Workshop on
Type
conf
DOI
10.1109/AISW.2015.7469232
Filename
7469232
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