Tag Archives: digital evolution

Do you teach a biology lab that has been disrupted by the coronavirus outbreak?

The following is a guest post written by my colleague, Rob Pennock.

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Do you teach a biology lab that has been disrupted by the coronavirus outbreak?  If so, you may want to consider using the Avida-ED experimental evolution platform as a virtual replacement.

Avida-ED logo

To limit the spread of the coronavirus, many colleages and universities have suspended in-person classes, and instructors have had to scramble to replace them with on-line instruction.  Biology faculty who teach laboratory-based courses find it especially difficult or impossible to do their planned lab exercises.  Avida-ED may provide a valuable substitute for some classes.

Avida-ED is an award-winning educational application developed at Michigan State University for undergraduate biology courses. It is aimed at helping students learn about evolution and the scientific method by allowing them to design and perform actual experiments to test hypotheses about evolutionary mechanisms using evolving digital organisms.  Funded by the NSF, Avida-ED is the educational version of a model system used by researchers to perform evolution experiments–including many that have been published in leading scientific journals (see some examples below).  Avida-ED is not a simulation, but an instantiation of the evolutionary mechanisms and process that allows for real experiments.  Avida-ED produces copious data that can be analyzed within the application or exported for statistical analysis.  Avida-ED has been used in classrooms across the country and around the world for over a decade.

Here are more reasons that Avida-ED may provide a useful, quick replacement for your lab:

  • Avida-ED is free.
  • Avida-ED requires no special registration or configuration.
  • Avida-ED is accessible on-line and runs locally in your web browser.
  • The user-friendly interface requires little technical training to use.
  • It includes ready-to-use exercises to teach a variety of evolutionary concepts.
  • It can also be used for open-ended labs where students design and perform their own experiments.
  • It can be used to teach principles of experimental design and scientific method.

See the Avida-ED web site for:

  • Link to the Avida-ED application launch page.
  • Model exercises (under the Curriculum link).
  • The Avida-ED lab book.
  • Quick start user manual.
  • Background information about digital evolution.
  • Articles about Avida-ED, including effectiveness studies.

The Avida-ED team is working to provide instructional videos for the core exercises from train-the-trainer workshops that we have offered in previous summers, where we teach faculty how to use the software in their own classes.  We can also provide instructor support materials for some exercises offline for certified instructors.  A mirror of the Avida-ED site is available in case the primary site goes down.

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Lenski, R. E., C. Ofria, T. C. Collier, and C. Adami.  1999.  Genome complexity, robustness and genetic interactions in digital organisms.  Nature 400: 661-664.

Wilke, C. O., J. Wang, C. Ofria, R. E. Lenski, and C. Adami.  2001.  Evolution of digital organisms at high mutation rates leads to survival of the flattest.  Nature 412: 331-333.

Lenski, R. E., C. Ofria, R. T. Pennock, and C. Adami.  2003.  The evolutionary origin of complex features.  Nature 423: 139-144.

Ofria, C., and C. O. Wilke.  2004.  Avida: A software platform for research in computational evolutionary biology.  Artificial Life 10: 191-229.

Chow, S. S., C. O. Wilke, C. Ofria, R. E. Lenski, and C. Adami.  2004.  Adaptive radiation from resource competition in digital organisms.  Science 305: 84-86.

Ostrowski, E. A., C. Ofria, and R. E. Lenski.  2007.  Ecological specialization and adaptive decay in digital organisms.  American Naturalist 169: E1-E20.

Clune, J., R. T. Pennock, C. Ofria, and R. E. Lenski.  2012.  Ontogeny tends to recapitulate phylogeny in digital organisms.  American Naturalist 180: E54-E63.

Goldsby, H. J., A. Dornhaus, B. Kerr, and C. Ofria.  Task-switching costs promote the evolution of division of labor and shifts in individuality.  Proceedings of the National Academy of Sciences, USA 109: 13686-13691.

Covert, A. W. III, R. E. Lenski, C. O. Wilke, and C. Ofria.  2013.  Experiments on the role of deleterious mutations as stepping stones in adaptive evolution.  Proceedings of the National Academy of Sciences, USA 110: E3171-E3178.

Goldsby, H. J., D. B. Knoester, C. Ofria, and B. Kerr.  2014.  The evolutionary origin of somatic cells under the dirty work hypothesis.  PLoS Biology 12: e1001858.

Fortuna, M. A., L. Zaman, C. Ofria, and A. Wagner.  2017.  The genotype-phenotype map of an evolving digital organism.  PLoS Computational Biology 13: e1005414.

Canino-Koning, R., M. J. Wiser, and C. Ofria.  2019.  Fluctuating environments select for short-term phenotypic variation leading to long-term exploration.  PLoS Computational Biology 15: e1006445.

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Evolving Fun and Games

Science isn’t always fun and games. But sometimes it is!

This guest post is by Terry Soule, a computer scientist, and Barrie Robison, a biologist, both on the faculty at the University of Idaho. The BEACON Center for the Study of Evolution in Action brings together biologists, computer scientists, and engineers to illuminate and harness the power of evolution as an on-going process.

With BEACON’s support, Terry and Barrie have developed a video game, called Darwin’s Demons, where you must fight off enemies that are evolving to defeat your best efforts!

Feel free to comment here.  However, please send any technical queries via email to Terry (tsoule@cs.uidaho.edu) and/or Barrie (brobison@uidaho.edu).

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Thanks to BEACON’s support, Polymorphic Games has created the evolutionary video game Darwin’s Demons, and placed it on the Steam website as part of the greenlight process.

Darwin’s Demons adds an evolutionary component and modern flair to an arcade classic.  Darwin’s Demons models biological evolution using enemies with digital genomes. Enemies acquire fitness by being the most aggressive, accurate, and longest lived, and only the most fit enemies pass their genomes to the next generation. The result? The creatures you found hardest to kill have all the babies, making each generation more challenging than the last!

The game includes in-game graphs for tracking evolution, displays the most fit enemies from each wave, and has an experiment mode where you can set parameters like the mutation rate, fitness function, etc.  It also dumps all of the evolutionary data to a file.  So, there are opportunities for experiments on user driven evolution if anyone is interested.  (We are more than happy to share the code and/or make simple modifications for controlled experiments.)

If you get the opportunity please try out the demo (downloadable at either of the sites listed above, with Windows, MAC, and Linux versions), vote for us on Steam, and send us comments, suggestions, or ideas for future directions and collaborations.

Thanks,

— Terry Soule (tsoule@cs.uidaho.edu), Computer Science, UI

— Barrie Robison (brobison@uidaho.edu), Biological Sciences, UI

 

Darwin's Demons

[Darwin’s Demons: image from the Polymorphic Games website]

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