Bioinformatics-Compute-Server

• Subject Area: Basic Research in Biology and Medicine
• Term: Funded in 2019
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 422216132

We develop innovative bioinformatics approaches for applications in modern molecular biology, biomedicine and systems/network medicine. We require compute hardware allowing for storing and analyzing massive so-called omics data. Our aim is to extract new knowledge and to generate novel hypothesis, such as mechanistic biomarkers. We employ advanced bid data technologies as well as artificial intelligence and machine learning. Our research focus lies on the combined analysis of multi-scale omics data (e.g. transcriptomics and epigenomics) in spatiotemporal resolution together with molecular signaling pathways. The later are modeled as graphs with nodes and edges between them. We develop innovative heuristic methods for high-throughput omics data (terabytes of sequence and spectrometry data) and genome-scale networks (with thousands of nodes and hundreds of thousands of edges) to deliver systems (bio)medicine results and targets. Those are used afterwards as mechanistic biomarkers and may help, for instance in medicine, to identify novel drug targets, to suggest drug repurposing candidates, and to find synergistic mechanisms of multiple drugs (network pharmacology). This requires a local highly parallel compute server infrastructure with many processor cores (>48) and big main memory (>256 GB), which can be accessed concurrently by all compute cores. The typical services offered, for instance, by our Leibniz Rechenzentrum, do not cover this specific area. However, such a system is the only way to associate tens of thousands of genes and small RNAs over hundreds of biomedical samples over 5-10 time points and 5-10 locations with each other and with the molecular signaling networks to effectively identify differentially altered hot spots. Such spots are the novel, mechanistic hypotheses that we aim to generate, which can be tested for drugability and validated in wet labs afterwards.

• DFG Programme: Major Research Instrumentation
• Major Instrumentation: Bioinformatik-Compute-Server
• Instrumentation Group: 7030 Dedizierte, dezentrale Rechenanlagen, Prozeßrechner
• Applicant Institution: Technische Universität München (TUM)
• Leader: Professor Dr. Jan Baumbach