Bioelectric Networks – Taming Cells’ Collective Intelligence for Regenerative Medicine
Seminar summary: https://foresight.org/summary/bioelectric-networks-taming-th…-medicine/
Program & apply to join: https://foresight.org/biotech-health-extension-program/
100 Plus Capital sponsors the Foresight Health & Biotech Extension Meeting.
Michael Levin Tufts Center for Regenerative and Developmental Biology
Bioelectric Networks – Taming Cells’ Collective Intelligence for Regenerative Medicine
Michael Levin is a Distinguished Professor and Vannevar Bush chair in the Biology Department at Tufts University. He also serves as the director of the Tufts Center for Regenerative and Developmental Biology. Scientist of Vision Award and Distinguished Scholar Award are recent honors. The group focuses on the biophysical mechanisms of decision-making in complex pattern regulation and harnessing endogenous dynamics to rationally control growth and form. The lab’s main current directions are:
Understanding how somatic cell networks form to store and recall pattern memories which guide morphogenesis.
* Create next-generation AI to help scientists understand the top-down regulation of patterns (a new bioinformatics for shape);
* Use these insights to develop new capabilities in regenerative engineering and medicine.
Michael Levin was a software developer and independent contractor before he went to college. He studied at Tufts University and was interested in unconventional computations and artificial intelligence. He obtained a dual B.S. to explore the algorithms that the biological world uses to implement complex adaptive behaviors. He received a PhD at Harvard University after receiving degrees in CS and Biology. He completed post-doctoral research at Harvard Medical School from 1996 to 2000, where he discovered a bioelectric language that cells use to coordinate their activity in embryogenesis. His independent lab (2000-2007, Forsyth Institute at Harvard; 2008-present, Tufts University), develops new molecular genetic and conceptual tools for large-scale information processes in regeneration, embryogenesis and cancer suppression.
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