We develop a technology that makes your data useful again. We efficiently integrate the plethora of available data to a universal cell map, giving you easy access to accelerate your analysis. We work on launching a product that provides simple, transparent and fast access to the cell map. Ultimately, our goal is to help you harvest all your data to identify biomarkers and drug targets for personalized therapies.
You struggle with slow and tedious data anaysis, because of fragmented and complex data.
Our universal cell map connects and structures your data.
You get more results in a fast and reproducible way.
Who we are
Knowing is a pre-seed startup from the Institute for Computational Biology at the Helmholtz Zentrum München.
Our business idea was sparked by the desire to make a contribution to research by accelerating discoveries in the field of Life Sciences. In December of 2015 we received the m4 award granted by the Ministry of Economic Affairs of Bavaria and managed by Bio-M. In fall 2017 we take part in the EIT Health LaunchLab.
Dr. Nikola Müller
Leading knowing Nikola is driven by a keen interest to integrate all data and has leadership experience.
Dr. Martin Preusse
Leading knowing Martin develops our Cell Map technology and creates new data solutions.
Software engineer Tanya connects our vision with todays best software technologies.
Rebecca Vázquez Kiesel
Business development Rebecca brings our solution to the market by bridging science and economy.
Working student Tan contributes to our software development.
Fabian Theis – Mentor and scientific advisor
Director of ICB, Professor for Mathematics at TUM
Using the cell map we link genome-wide association studies with gene expression and DNA methylation to identify common molecular patterns of depression. We store all multi-dimensional omics data sets and uncover new relationships.
Max Planck Institute of Psychiatry
Prof. Elisabeth Binder, Department for Translational Research in Psychiatry
knowing skin diseases
With our knowing technology we store expression patterns of several skin diseases for fast and comprehensive analysis. We aim to identify unique molecular features for psoriasis and eczema.
Technische Universität München
Prof. Kilian Eyerich, Department of Dermatology, Rechts der Isar
We are currently seeking for motivated talents and offer job opportunities to expand our team. We offer working student, internship, PhD and full staff positions. If you are interested to work on a fascinating project at the interface of life science and big data and wish to build a business from the very beginning send us a short motivation statement and CV.