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Vaccine. 2015 Sep 29;33(40):5249-55. doi: 10.1016/j.vaccine.2015.04.096. Epub 2015 May 11.

High-throughput data analysis and data integration for vaccine trials.

Author information

1
Department of Immunology, Max Planck Institute for Infection Biology, Charitéplatz 1, D-10117, Berlin, Germany. Electronic address: january.weiner@mpiib-berlin.mpg.de.
2
Department of Immunology, Max Planck Institute for Infection Biology, Charitéplatz 1, D-10117, Berlin, Germany. Electronic address: kaufmann@mpiib-berlin.mpg.de.
3
Department of Immunology, Max Planck Institute for Infection Biology, Charitéplatz 1, D-10117, Berlin, Germany.

Abstract

Rational vaccine development can benefit from biomarker studies, which help to predict, optimize and evaluate the immunogenicity of vaccines and ultimately provide surrogate endpoints for vaccine trials. Systems biology approaches facilitate acquisition of both simple biomarkers and complex biosignatures. Yet, evaluation of high-throughput (HT) data requires a plethora of tools for data integration and analysis. In this review, we present an overview of methods for evaluation and integration of large amounts of data collected in vaccine trials from similar and divergent molecular HT techniques, such as transcriptomic, proteomic and metabolic profiling. We will describe a selection of relevant statistical and bioinformatic approaches that are frequently associated with systems biology. We will present data dimension reduction techniques, functional analysis approaches and methods of integrating heterogeneous HT data. Finally, we will provide a few examples of applications of these techniques in vaccine research and development.

KEYWORDS:

Data integration; Systems biology; Systems vaccinology

PMID:
25976544
DOI:
10.1016/j.vaccine.2015.04.096
[Indexed for MEDLINE]

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