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Guest Talk from Jan Baumbach - University of Southern Denmark (Big Data Biological Analytics)
21.02.2017 - 15:04

In March, we are lucky to host the visit of Jan Baumbach, Associate Professor at the University of Southern Denmark. He will be giving a talk on 20.3.2017 at 11:00 in room 02.134 (Informatik Turm).



Big Data in Bioinformatics - When molecular networks meet complex multi-OMICS data



 Recent advances in modern OMICS technology allow measuring the expression of all kinds of biological entities (genes, proteins, metabolites, miRNAs, etc.) at low cost and in high-throughput. Computational challenges for analyzing such big data emerge, ranging from the low signal to noise ratio to high model complexity, which render simple statistical questions arbitrarily complicated. We will discuss several bioinformatics tools for de-isolating biological networks and multiple OMICS data types: de novo pathway enrichment, in vitro high-throughput screening (HTS) data integration, time-course network enrichment, and cancer subtyping. Using Huntington’s disease patients’ expression data as running example, we will employ a guilt-by-association approach to illuminate the power of networks to identify novel disease mechanisms. We will then extend this principle to study HTS data gained from large-scale chemical compound screens, siRNA knock-down and CRISPR/CAS9 knock-out screens, as well as microRNA inhibitor and -mimics screens. In addition, we discuss how this kind of computational network biology has strong potential to enable precision medicine by classifying breast cancer subtypes utilizing complex combo-features gained from combining networks with gene expression data and DNA methylation data. Finally, I will briefly illustrate how one can use metabolomics data of human exhaled air for non-invasive, early detection of respiratory diseases, such as COPD and lung cancer.



About the Speaker:

Jan Baumbach studied Applied Computer Science in the Natural Sciences at Bielefeld University in Germany. His research career started at Rothamsted Research in Harpenden (UK) where he worked on computational methods for the integration of molecular biology data. He returned to the Center for Biotechnology in Bielefeld for his PhD studies on the reconstruction of bacterial transcriptional regulatory networks. He developed CoryneRegNet, the reference database and analysis platform for corynebacterial gene regulations. Afterwards, at the University of California at Berkeley, he worked in the Algorithms group of Richard Karp on protein homology detection. In Berkeley, he also developed Transitivity Clustering, a novel clustering framework for large-scale biomedical data sets. Since March 2010, Jan was head of the Computational Systems Biology group at the Max Planck Institute for Informatics in Saarbrücken, Germany. In October 2012, he moved to the University of Southern Denmark as head of the Computational Biology group, leader of the Computational BioMedicine program, and steering board member of the Center for Precision Medicine. His current research concentrates on the combined analysis of molecular networks together with OMICS data, the modeling of genetic expression pathways as well as biomarker discovery and computational methods for personalized medicine.

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