Prediction and modelling of viral miRNA target networks

Coordinator:    Prof. Dr. Ralf Zimmer
Institution: Institut für Informatik, LMU München
The goal of this sub-project is the prediction of viral and cellular miRNAs targets relevant for herpes infections. In addition, cellular transcription networks will be modelled in order to predict, visualize, and better understand possible patho-genetic mechanisms affected by these miRNAs. Using network models the subproject will analyse the transcriptome and proteome data from the IG.
It is known that Herpes viruses express a few miRNAs, which probably regulate viral and/or host gene expression. We try to identify the regulated targets of these miRNA based on the set of identified miRNAs of different herpes viruses (EBV, KSHV, HSV, VZV, MHV, mCMV, …), the set of protein-protein interactions between virus and host, and gene (DNA-chip) as well as protein (MS) expression data. Based on the data obtained from the project partners, specific graph models, Petri Nets with Fuzzy Logic (PNFL), will be derived to represent the underlying regulation mechanisms and processes. With a comparative analysis of various viruses studied in the project we will reveal common and shared as well as distinctive pathomechanisms of the respective virus infections.

Towards these goals the project will focus on the following work packages
•    Prediction of targets for viral miRNAs with established and newly developed methods,
•    interaction of viral proteins with cellular proteins and its effect on miRNA processes,
•    comparative analysis of miRNA models for various herpes viruses,
•    analysis of expression and sequence data using network models,
•    development of methods to estimate miRNA and mRNA halflifes and their use in systems biology models,
•    identification of novel viral miRNAs and their integration into network models,
•    regulation and dynamics of miRNA related processes,
•    use of DNA computing techniques for context-specific and target-oriented miRNA production.
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