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Micha Hersch


  • email: micha.hersch at



I am involved in the Plant Growth project from I am mainly interested in understanding, through a combination of mathematical modeling and experiments, how biological systems can robustly self-regulate their behavior. I studied this in the context of the gene regulatory network of the shade avoidance mechanism in the model plant Arabidopsis Thaliana and in cell size determination in the fission yeast.

I developed HypoPhen, an image analysis software for the semi-automatic phenotyping of Arabidopsis seedlings and Cellophane, an ImageJ plugin for the semi-automatic extraction of flourescent-tagged protein profiles along the cell membrane.

I also did some genome-wide data analysis related to human genetics, for example Genome Wide Association Studies, and another one showing the higher resilience of females to mutations in genes involved in neuro-developmental disorders such as autism.

My scientific interests include dynamical systems theory, self-organization, statistical learning theory and large-scale biological data analysis. For additional information, you can consult my web page.

I did my ph.D at the lasa (EPFL), where I worked on bio-inspired motor control and artificial cognition for humanoid robots. See this page for more details on this.

And before this, I worked on automatic speech recognition at the International Computer Science Institute in Berkeley.

Academic titles


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Teaching and outreach

  • I also visit schools and tell them about medical genetics as part of the gene days