Jörg Linde

I study the analysis of high-throughput transcriptom and genome data.

For transcritom data (RNA-Seq, microarrays), I perform preprocessing and statistics to identify differentially expressed genes, as well as their functional analysis. My main focus is the analysis of transcriptom data from human fungal pathogens in infection related conditions (f.e. nutrient limitation) as well as during the interaction with the host (dual RNA-seq). Experimental data is used to set up mathematical models for host-pahtogen interaction with a special focus on the prediction of gen regulatory interactions. May aim is to use modelling for the prediction of hypotheses which are tested in the lab.

Within the German Research Foundation (DFG) founded project "FungiNet" I am setting up a data warehouse for the management and visualisation of expression data (and their metadata) of human-pathogenic fungi and their host.

Gene structural prediction is a vital task for the study of micro-organisms.. Therefore, I develop and apply tools and pipelines for accurate prediction of gene structures within fungi and secondary metabolite producing bacteria. an important part of these pipeline is the facilitation of RNA-Seq data to improve gene prediction. Annotated genomes are publicly available (www.genome-resource.de).