Bioinformatics Strategies for the Analysis and Integration of Large-Scale Multiomics Data
Niccolo Tesi (TU Delft - Pattern Recognition and Bioinformatics, Amsterdam UMC)
S.J. van der Lee (Amsterdam UMC)
M. Hulsman (Amsterdam UMC)
H. Holstege (TU Delft - Intelligent Systems, Amsterdam UMC)
Marcel J.T. Reinders (TU Delft - Pattern Recognition and Bioinformatics)
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Abstract
The authors of the manuscript Identification of five potential predictive biomarkers for Alzheimer’s disease by integrating the unified test for molecular signatures and weighted gene co-expression network analysis in this issue of the Medical Sciences Section of the Journals of Gerontology Series A have exploited a number of different bioinformatic tools to analyze the vast amount of data that they were confronted with (1). This is increasingly happening as it is becoming easier and cheaper to generate comprehensive molecular and phenotypic data with which biological hypotheses can be sharpened. Here, we will give a basic understanding of the methods used by Zhou et al., which are becoming standard practices when analyzing high-throughput biological data (1).