Wir freuen uns Martin Preusse zu begrüßen, der uns zeigt wie Neo4j in der Medizin eingesetzt wird.
Big Data in Genomics: How Neo4j helps to develop new Drugs
The amount of data generated in biomedical research exploded during the last decade. Experimental technologies like DNA sequencing, metabolomics and epigenomics led the way to a new understanding of the molecular organization of life. But with big data comes a big question: How do we transform information to actionable knowledge? In case of biomedical research, the key issue is to integrate the vast amounts of heterogenous data and use it for personalized therapies and drug development. Graph databases are an ideal way to represent biomedical knowledge and offer the necessary flexibility to keep up with scientific progress. A well-designed data model and Cypher queries can answer questions in seconds which previously took days of manual analysis.
Martin Preusse studied Biochemistry at TU München and is now working on his PhD in Bioinformatics at the Institute for Computational Biology (Helmholtz Zentrum München). In his scientific work, he focuses on regulatory networks of cellular decisions and integration of heterogneous experimental data sets.