the community site for and by developmental biologists

About: Mike Levin

I was originally trained in computer science, working in artificial intelligence and information processing. My interest in the engineering of systems with adaptive behavior and self-repairing abilities led me to study the robust patterning mechanisms of living systems. After a PhD with Cliff Tabin at the Genetics department of Harvard Medical School, and a post-doc with Mark Mercola at the Cell Biology department at HMS, I started my lab at Forsyth Institute in 2000. I moved my group to the main campus of Tufts University in 2009 to be closer to interdisciplinary collaborators in computer science, bioengineering, and cognitive science. The Levin lab studies storage and processing of patterning information among living cells during regeneration, development, and cancer suppression. Our specific focus is on endogenous bioelectric cues – standing voltage gradients in complex tissues that serve as prepatterns for anatomical polarity, organ identity, and gene expression. Our development of novel tools for molecular tracking and manipulation of bioelectric signals in vivo has enabled the discovery and manipulation of ionic controls of eye induction, tail regeneration, left-right asymmetry, regenerative polarity control, and stem cell regulation. Through biophysics and computational modeling, we are beginning to understand how the real-time dynamics of physiological networks guides establishment, repair, and maintenance of morphology; gaining control of this new set of controls may offer unprecedented opportunities for developmental biology, cancer biology, regenerative medicine, and synthetic bioengineering. See more at

Posts by Mike Levin:

AI tackles variability of metastatic conversion triggered by bioelectric disregulation

Posted by on November 7th, 2015

  One of the most important problems in experimental biology has to do with variability / heterogeneity (Rubin, 1990): why do different organisms react differently to the same perturbation or reagent? This is observed even among clonal populations (e.g., cohorts of planarian flatworms descended from the fission of 1 animal and living in the same[…]

Computing the worm: artificial intelligence approaches to planarian regeneration and beyond

Posted by on October 30th, 2015

Pattern formation and regulation emerges from cellular activity determined by specific biophysical and genetic rules. A major challenge for developmental biology, biomedicine, and synthetic bioengineering is this highly indirect (Lobo et al., 2014b) relationship between the rules that govern processes at the lower scales, and the anatomical outcomes observed at the macroscopic scale. It is[…]

Gap junctions: versatile mediators of long-range developmental signals

Posted by on August 13th, 2015

My lab works on developmental bioelectricity, studying how cells communicate via endogenous gradients of plasma membrane resting potential (Vmem) in order to coordinate their activity during pattern regulation (Levin, 2013; Levin, 2014b; Tseng and Levin, 2013). It is well-known that resting potential is an important regulatory parameter for individual cells’ proliferation, differentiation, and oncogenic potential[…]

Nerves read the electrical topography of their microenvironment in making growth decisions

Posted by on June 29th, 2015

A really interesting recent paper on bioartificial limbs underscored the prospect of transplantation for problems in regenerative medicine. One key issue facing transplant technology is establishing appropriate innervation to the host. What factors control the amount of nerve emanating from an organ graft and the paths that this innervation takes? Alongside the familiar diffusible signaling[…]

Remembrance of Brains Past

Posted by on July 30th, 2013

What would happen to your memories and personality if, after decades of adult life, some portion of your brain was replaced with the progeny of fresh stem cells (as might happen in a treatment for degenerative brain disease)? Given the fascinating but poorly-understood examples of memory in aneural systems such as plants, ciliates, etc. (Eisenstein,[…]