Enrico Glaab

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Integrative analysis of high-throughput omics datasets (WGS, WES, RNAseq, CHIPseq, microarrays, GWAS, GC-MS and LC-MS proteomics and metabolomics data) and cellular pathway and molecular network data using machine learning, graph algorithms, pathway analysis and combinatorial optimization approaches. Implementation of bioinformatics algorithms and web-applications for online analysis of biological data, including: * ArrayMining.net, a web-application for microarray data analysis, * EnrichNet, a web-service for network-based gene and protein set enrichment analysis, * TopoGSA, a web-based software for comparative network topological analysis of genes/proteins, * PathExpand, a web-applicat...

microarray bioinformatics aging transcriptomics statistics omics analysis gene expression network brain tauopathy du145 ubiquitin alzheimer's disease tau neurodegeneration zebrafish cell culture improved proteomics noise replicates heat map technical visualization differential variance metabolomics ranking disease gene prioritization case-control parkinson's disease phenologs over-representation pathway statistic functional interpretation protein set enrichment process graph gene set association computational cancer normlization cross-study clustering classification gene set analysis topogsa computational biology integrative expression protein prediction feature selection gene protein interaction

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Enrico Glaab

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Integrative analysis of transcriptomics and proteomics data with ArrayMining and TopoGSA

EnrichNet: Graph-based statistic and web-application for gene/protein set enrichment analysis

Integrative bioinformatics analysis of Parkinson's disease related omics data

Exploiting technical replicate variance in omics data analysis (RepExplore)

Modelling gender-specific regulation of tau in Alzheimer’s disease