Ludwig Geistlinger

Post-Doctoral Fellow
in Cancer Genomics

Ph.D Bioinformatics
University of Munich

M.S Bioinformatics
University of Munich

Dr. Geistlinger is trained in Bioinformatics. His research interests are in computational biology and biostatistics, focusing on the field of functional enrichment analysis of high-throughput genomic assay data.

Prior to his work at CUNY ISPH, Dr. Geistlinger completed a PhD on network-based analysis of gene expression data at the University of Munich, Germany, and a post-doctoral fellowship at the University of São Paulo, Brazil, where he analyzed the effects of structural genome variation on gene expression.

Dr. Geistlinger’s implementation science experience centers on designing and implementing methods for the analysis of large-scale genomic assay data to improve the understanding of molecular mechanisms underlying specific cancer types. This also includes assessment of the clinical relevance of molecular cancer subtypes, especially whether their incorporation in personalized healthcare could improve treatment and clinical outcome.

Key Projects:

Recent Publications:

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Geistlinger L, Da Silva VH, Cesar A, Tizioto PC, Waldron L, Zimmer R, De Almeida Regitano LC, Coutinho L. Widespread modulation of gene expression by copy number variation in skeletal muscle. Scientific reports. (2018) 8:1399. DOI:10.1038/s41598-018-19782-4.

Silva VH, Regitano LC, Geistlinger L, Pertille F, Giacchetto PF, Brassaloti RA, Morosini NS, Zimmer R, Coutinho LL (2016) Genome-wide detection of CNVs and their association with meat tenderness in Nelore cattle. PLoS One, 11(6), e0157711.

Geistlinger L, Csaba G, Zimmer R (2016) Bioconductor’s EnrichmentBrowser: seamless navigation through combined results of set- & network-based enrichment analysis. BMC Bioinformatics, 17, 45.

Petri T, Altmann S, Geistlinger L, Zimmer R, Küffner R (2015) Addressing false discoveries in network inference. Bioinformatics, 31(17), 2836-43.

Geistlinger L, Csaba G, Dirmeier S, Küffner R, Zimmer R (2013) A comprehensive gene regulatory network for the diauxic shift in Saccharomyces cerevisiae. Nucleic Acids Research, 41(18), 8452-63.

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