University of Munich
University of Munich email@example.com
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.
|• Human Microbiome Analysis for Public Health|
|• Validation and Clinical Relevance of Ovarian Cancer Molecular Subtypes|
|• Cancer genomics: integrative and scalable solutions in R/Bioconductor|
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.
Kurome M, Geistlinger L*, Kessler B, Zakhartchenko V, Klymiuk N, Wuensch A, Richter A, Baehr A, Kraehe K, Burkhardt K, Flisikowski K, Flisikowska T, Merkl C, Landmann M, Durkovic M, Tschukes A, Kraner S, Schindelhauer D, Petri T, Kind A, Nagashima H, Schnieke A, Zimmer R, Wolf E (2013) Factors influencing the efficiency of generating genetically engineered pigs by nuclear transfer: multi-factorial analysis of a large data set. BMC Biotechnology, 13, 43.