Graph Databases in Life Sciences: 
Bringing Biology Back to Its Nature

Thursday October 17 08:00 PDT / 17:00 CEST

Today's life science research is about genes, proteins, metabolites, relationships, interactions and biological networks. Data storing and mining brings a huge potential for biologists, however classical storage formats such as SQL and Excel involve various issues, such as scalability and performance problems with data growth, complexity and accessibility.  Finally, most of the storage models are far from biological reality: Graph databases and Neo4j meet the need in life sciences for an appropriate data and database model. 

Speaker: Thilo Muth, PhD Student, Max-Planck-Institut Magdeburg

Thilo Muth

Graduated in 2011 in bioinformatics at the university of Jena. Topic of the diploma thesis: "Cloud computing in proteomics for the in-depth analysis of high-quality unidentified spectra". Collaboration with the CompOmics group at the UGent (Ghent University/Belgium) with Prof. Lennart Martens since 2007 and performed the main part of the Amazon Cloud Computing in Ghent. PhD student since summer 2011 at the Max Institute Magdeburg, doing high-throughput analysis of metaproteomics and glycomics data. Shared PhD student with Prof. Martens. Interested in all sorts of data mining and storage techniques, more and more NOSQL techniques such as graph databases and Neo4j. Programming in Java, Python, PHP and Perl.



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