2018.04.02 A Rule Based Approach to Development
题 目：A Rule Based Approach to Development
Member of Danish Royal Academy of Sciences
Professor of Biological Physics at the Niels Bohr Institute in Copenhagen, Denmark
主持人: 汤超 教授
Development of animals proceeds from bulk, through simple spherical shapes to folds and tubes. Emerging geometrical shapes are robust for a given species and can be maintained when moved to different parts of the embryo or if the size is varied. Despite conceptually similar processes of progression through development, the resulting geometrical shapes can be very different between species. How can we reconcile this robustness with overall variability?
The progression from bulk, to tubes and folds coincides with the progressive - first apical basal and then planar - polarization of cells. To explore if cellular polarization may enable development with the ability to create diversity of robust and stable shapes we developed a tool that allows to simulate thousands of polarized cells in 3D. We find that cellular polarity enables stable complex folded shapes. When set in the context of pancreatic organoids, One polarity (Apical basal) coupled with differential growth rates is sufficient to explain emergence of folded lumens in pancreatic organoids. With two, apical basal and planar, mutually perpendicular polarities, the model recovers main stages of sea urchin gastrulation.
Kim Sneppen is a full professor of Biological Physics at the Niels Bohr Institute (NBI) in Copenhagen, the Member of Danish Royal Academy of Sciences. He received his Ph.D. in Nuclear Physics from NBI in 1989.
His research interest lies in complex and biological systems, with focus on describing these through mathematics and physics. His published articles are within evolution, punctuated equilibrium, self-organization, dynamics of transcription on DNA, translation traffic of mRNA, small RNA regulation, gene regulatory circuits, epigenetics, networks, information distribution, phage biology, phage-bacteria ecosystems, cellular automata for biological competition and diversity.