High-throughput data analysis and data integration for vaccine trials

被引:6
|
作者
Weiner, January, III [1 ]
Kaufmann, Stefan H. E. [1 ]
Maertzdorf, Jeroen [1 ]
机构
[1] Max Planck Inst Infect Biol, Dept Immunol, D-10117 Berlin, Germany
关键词
Data integration; Systems vaccinology; Systems biology; GENE SET ENRICHMENT; DIFFERENTIAL EXPRESSION; PROTEOMICS DATA; BIOMARKERS; DISCOVERY; SELECTION; RESOURCE; IMMUNITY; GENOME; TERMS;
D O I
10.1016/j.vaccine.2015.04.096
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
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. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:5249 / 5255
页数:7
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