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IMMUNOCAT—A Data Management System for Epitope Mapping Studies

To enable rationale vaccine design, studies of molecular and cellular mechanisms of immune recognition need to be linked with clinical studies in humans. A major challenge in conducting such translational research studies lies in the management and integration of large amounts and various types of d...

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Autores principales: Chung, Jo L., Sun, Jian, Sidney, John, Sette, Alessandro, Peters, Bjoern
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2871663/
https://www.ncbi.nlm.nih.gov/pubmed/20490281
http://dx.doi.org/10.1155/2010/856842
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author Chung, Jo L.
Sun, Jian
Sidney, John
Sette, Alessandro
Peters, Bjoern
author_facet Chung, Jo L.
Sun, Jian
Sidney, John
Sette, Alessandro
Peters, Bjoern
author_sort Chung, Jo L.
collection PubMed
description To enable rationale vaccine design, studies of molecular and cellular mechanisms of immune recognition need to be linked with clinical studies in humans. A major challenge in conducting such translational research studies lies in the management and integration of large amounts and various types of data collected from multiple sources. For this purpose, we have established “IMMUNOCAT”, an interactive data management system for the epitope discovery research projects conducted by our group. The system provides functions to store, query, and analyze clinical and experimental data, enabling efficient, systematic, and integrative data management. We demonstrate how IMMUNOCAT is utilized in a large-scale research contract that aims to identify epitopes in common allergens recognized by T cells from human donors, in order to facilitate the rational design of allergy vaccines. At clinical sites, demographic information and disease history of each enrolled donor are captured, followed by results of an allergen skin test and blood draw. At the laboratory site, T cells derived from blood samples are tested for reactivity against a panel of peptides derived from common human allergens. IMMUNOCAT stores results from these T cell assays along with MHC:peptide binding data, results from RAST tests for antibody titers in donor serum, and the respective donor HLA typing results. Through this system, we are able to perform queries and integrated analyses of the various types of data. This provides a case study for the use of bioinformatics and information management techniques to track and analyze data produced in a translational research study aimed at epitope identification.
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spelling pubmed-28716632010-05-20 IMMUNOCAT—A Data Management System for Epitope Mapping Studies Chung, Jo L. Sun, Jian Sidney, John Sette, Alessandro Peters, Bjoern J Biomed Biotechnol Methodology Report To enable rationale vaccine design, studies of molecular and cellular mechanisms of immune recognition need to be linked with clinical studies in humans. A major challenge in conducting such translational research studies lies in the management and integration of large amounts and various types of data collected from multiple sources. For this purpose, we have established “IMMUNOCAT”, an interactive data management system for the epitope discovery research projects conducted by our group. The system provides functions to store, query, and analyze clinical and experimental data, enabling efficient, systematic, and integrative data management. We demonstrate how IMMUNOCAT is utilized in a large-scale research contract that aims to identify epitopes in common allergens recognized by T cells from human donors, in order to facilitate the rational design of allergy vaccines. At clinical sites, demographic information and disease history of each enrolled donor are captured, followed by results of an allergen skin test and blood draw. At the laboratory site, T cells derived from blood samples are tested for reactivity against a panel of peptides derived from common human allergens. IMMUNOCAT stores results from these T cell assays along with MHC:peptide binding data, results from RAST tests for antibody titers in donor serum, and the respective donor HLA typing results. Through this system, we are able to perform queries and integrated analyses of the various types of data. This provides a case study for the use of bioinformatics and information management techniques to track and analyze data produced in a translational research study aimed at epitope identification. Hindawi Publishing Corporation 2010 2010-05-17 /pmc/articles/PMC2871663/ /pubmed/20490281 http://dx.doi.org/10.1155/2010/856842 Text en Copyright © 2010 Jo L. Chung et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Report
Chung, Jo L.
Sun, Jian
Sidney, John
Sette, Alessandro
Peters, Bjoern
IMMUNOCAT—A Data Management System for Epitope Mapping Studies
title IMMUNOCAT—A Data Management System for Epitope Mapping Studies
title_full IMMUNOCAT—A Data Management System for Epitope Mapping Studies
title_fullStr IMMUNOCAT—A Data Management System for Epitope Mapping Studies
title_full_unstemmed IMMUNOCAT—A Data Management System for Epitope Mapping Studies
title_short IMMUNOCAT—A Data Management System for Epitope Mapping Studies
title_sort immunocat—a data management system for epitope mapping studies
topic Methodology Report
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2871663/
https://www.ncbi.nlm.nih.gov/pubmed/20490281
http://dx.doi.org/10.1155/2010/856842
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