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Neo4j GraphDay Munich - Improve Health Research

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Neo4j GraphDay Munich - Health & Life Sciences
Martin Preusse, Knowing

Published in: Technology
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Neo4j GraphDay Munich - Improve Health Research

  1. 1. Martin Preusse I work with data to improve health research
  2. 2. Martin Preusse PhD Computational Biology Consulting Postdoc Knowing Health 2016 2018 2019 2017 2012
  3. 3. communicate understand clean structure store label model validate transfer collect integrate predict
  4. 4. clean structure store label model validatecollect integrate predictcommunicate transfer
  5. 5. clean structure store label model validatecollect integrate predictcommunicate transfer deeplearning
  6. 6. Cell Map A map of all things in the cell, implemented in neo4j.
  7. 7. A startup to improve data integration and make data more accessible.
  8. 8. metabolite gene mutation biomarker or drug target risk mutation regulated gene associated metabolite
  9. 9. "Low-input, high-throughput, no-output biology." Sydney Brenner
  10. 10. neo4j
  11. 11. micro arrays RNA-seq metabolomics ChIP-seq proteomics Associations CNV
  12. 12. Can you build a recurrent neural network for gene activity prediction based on combined histone ChIP-seq and RNA- seq experiments to improve current prediction models and allow cross-referencing DNA methylation in order to decipher multi-level epigenomics?
  13. 13. I found gene Klr2, does it regulate DNA methylation?
  14. 14. Dr. Nikola Müller Founder Dr. Martin Preusse Founder Tanya Kozel Software Development Rebecca Vázquez Marketing & Business Development & Prof. Dr. Dr. Fabian Theis Mentor & Scientific advisor Annette Leonhard Mentor We are Peter Kreitmaier Bioinformatician
  15. 15. martin.preusse@gmail.com

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