Michael Levin

@drmichaellevin

Scientist working at Tufts University; my lab studies patterning and computation in a range of biological systems.

Joined May 2013

Tweets

You blocked @drmichaellevin

Are you sure you want to view these Tweets? Viewing Tweets won't unblock @drmichaellevin

  1. Found a quite interesting paper on evolution, aging, and mice as a biomedical test model: from an also interesting (long) podcast episode:

    Undo
  2. Retweeted
    26 Dec 2016

    Permanently 2-headed planaria, being themselves. Footage by Junji Morokuma in the Levin lab, music by Edvard Grieg.

    Undo
  3. Feb 1

    Here's one of the long-form essays on Causation in biology expanding on : "Biophysics of Regenerative Repair Suggests New Perspectives on Biological Causation": Others' (like 's) should be out soon in forthcoming collection.

    Undo
  4. Jan 31

    What model systems’ embryos are easily dissociated into cells? Chemical method, ideally (not manual dissection), and we want the cells to stay alive (not for fixation). Can zebrafish? C. elegans? Other invertebrates? The weirder the better. Ideas?

    Undo
  5. Jan 31

    Rubber Hand Illusion & more generally Isn't it weird that despite long evolutionary time of dependable (constant) body structure, brain is willing to abandon default, & revise somatic self-model after mere ~20 minutes of experience?

    Undo
  6. Jan 30

    This is quite useful: "The Node Network is a global directory of developmental and stem cell biologists, designed to help you find speakers, referees, panel members and potential collaborators."

    Undo
  7. Jan 30

    Very interesting collection: "Evolution, Development and Complexity: Multiscale Evolutionary Models of Complex Adaptive Systems"

    Undo
  8. Jan 28

    Final version of methods paper on workflow for quantifying calcium/bioelectricity tracking in frog embryos, by Patrick McMillen (from our lab) and Richard Novak, a great collaborator and scientist at :

    Undo
  9. Jan 27

    Classic on multi-headed snakes.

    Undo
  10. Jan 26

    Lots to think about here: "The neuron-level phenomena underlying cognition and consciousness: synaptic activity and the action potential."

    Undo
  11. Jan 26

    Before very important Jan. event, told myself "no thinking about new directions until all prep is done & we get past it." Oddly, this triggered flood of new ideas (written down for later). Is this a known thing? What strategies do you all use for enhancing actionable creativity?

    Undo
  12. Jan 25

    There are molecular/physiological markers of stress, both on cellular level and organismal level. Are there markers of happiness? Is there anything that can be assayed to detect when a cell/tissue/organ is within optimal allostatic point (opposite of stressed)?

    Undo
  13. Jan 24

    A very nice tutorial chapter on gene networks processing positional information: "Modelling Time-Dependent Acquisition of Positional Information."

    Undo
  14. Jan 17

    "Living matter is the repetitive production of ordered heterogeneity." – Rollin Hotchkiss, 1958

    Undo
  15. Jan 13

    More info here: This is just the beginning - stay tuned later this year; these critters have *amazing* behavior.

    Undo
  16. Jan 13

    Check out our (, , Doug Blackiston) latest in PNAS: 1st of a series of papers on new synthetic living machines. What kinds of bodies can frog cells (no genomic editing) make when liberated from the embryo? Guided self-assembly.

    Undo
  17. Undo
  18. Jan 11

    Does biology have truly difficult ideas? Studying math, comp sci, physics, etc., one quickly encounters material that is hard to truly grasp (and many of us get to a point where we mentally just can't go further, while some others can). Does this exist in biology? If not, why?

    Undo
  19. Jan 11

    In the spirit of I ask folks who infer gene regulatory networks: has anyone tried 1) create a synthetic (cell free?) set of transcription factors, 2) profile gene levels, 3) reconstruct GRN - does the result look anything like circuit that's really there?

    Undo
  20. Jan 10

    Re. deep net models that get answers right without explaining what's inside the black box. Isn't this what quantum physicists say - QM theory is great because it gives right answers to huge precision, and that asking for an understandable picture of what's inside is misguided?

    Undo

Loading seems to be taking a while.

Twitter may be over capacity or experiencing a momentary hiccup. Try again or visit Twitter Status for more information.

    You may also like

    ·