Interactive Cloud Experimentation for Biology: An Online Education Case Study

Interacting with biological systems via experiments is important for academia, industry, and education, but access barriers exist due to training, costs, safety, logistics, and spatial separation. High-throughput equipment combined with web streaming could enable interactive biology experiments online, but no such platform currently exists. We present a cloud experimentation architecture (paralleling cloud computation), which is optimized for a class of domain-specific equipments (biotic processing units - BPU) to share and execute many experiments in parallel remotely and interactively at all time. We implemented an instance of this architecture that enables chemotactic experiments with a slime mold Physarum Polycephelum. A user study in the blended teaching and research setting of a graduate-level biophysics class demonstrated that this platform lowers the access barrier for non-biologists, enables discovery, and facilitates learning analytics. This architecture is flexible for integration with various biological specimens and equipments to facilitate scalable interactive online education, collaborations, research, and citizen science.

[1]  Paulo Blikstein,et al.  Gears of our childhood: constructionist toolkits, robotics, and physical computing, past and future , 2013, IDC.

[2]  J. Bose,et al.  Comparative electro-physiology, a physico-physiological study , 2009 .

[3]  J. Ellenberg,et al.  High-throughput fluorescence microscopy for systems biology , 2006, Nature Reviews Molecular Cell Biology.

[4]  Christophe Gravier,et al.  State of the Art About Remote Laboratories Paradigms - Foundations of Ongoing Mutations , 2008, Int. J. Online Eng..

[5]  Toshiyuki Nakagaki,et al.  Flow-network adaptation in Physarum amoebae , 2008, Theory in Biosciences.

[6]  Sang-Hoon Kim,et al.  Fractal dimensions of a green broccoli and a white cauliflower , 2004, cond-mat/0411597.

[7]  D. T. Emerson,et al.  The work of Jagadis Chandra Bose: 100 years of millimeter-wave research , 1997 .

[8]  Dharmarus Rizal,et al.  Remote access to laboratories through the world-wide-web , 2000 .

[9]  Marios Papaevripidou,et al.  Effects of experimenting with physical and virtual manipulatives on students' conceptual understanding in heat and temperature , 2008 .

[10]  E. Alparslan,et al.  Image enhancement by local histogram stretching , 1981 .

[11]  Ryan S. Baker,et al.  The State of Educational Data Mining in 2009: A Review and Future Visions. , 2009, EDM 2009.

[12]  T. Nakagaki,et al.  Smart network solutions in an amoeboid organism. , 2004, Biophysical chemistry.

[13]  Lara M. Triona,et al.  Point and Click or Grab and Heft: Comparing the Influence of Physical and Virtual Instructional Materials on Elementary School Students' Ability to Design Experiments , 2003 .

[14]  Corporate Ieee.  1996 IEEE Conference on Emerging Technologies and Factory Automation , 1996 .

[15]  C. Wieman,et al.  PhET: Interactive Simulations for Teaching and Learning Physics , 2006 .

[16]  Adrien Treuille,et al.  Predicting protein structures with a multiplayer online game , 2010, Nature.

[17]  Sebastián Ventura,et al.  Educational Data Mining: A Review of the State of the Art , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[18]  Juan F Medrano,et al.  Real-time PCR for mRNA quantitation. , 2005, BioTechniques.

[19]  Lara M. Triona,et al.  Hands on What? The Relative Effectiveness of Physical versus Virtual Materials in an Engineering Design Project by Middle School Children , 2007 .

[20]  K. Wohlfarth-Bottermann.  Oscillatory contraction activity in Physarum. , 1979, The Journal of experimental biology.

[21]  F.J.R. Fernandez,et al.  Remote laboratory , 2003, 2003 IEEE International Symposium on Industrial Electronics ( Cat. No.03TH8692).

[22]  Tomohiro Shirakawa,et al.  A model of network formation by Physarum plasmodium: Interplay between cell mobility and morphogenesis , 2010, Biosyst..

[23]  Paulo Blikstein,et al.  Multimodal learning analytics , 2013, LAK '13.

[24]  M.E. Macias,et al.  eLab - Remote electronics lab in real time , 2007, 2007 37th Annual Frontiers In Education Conference - Global Engineering: Knowledge Without Borders, Opportunities Without Passports.

[25]  Christina Oettmeier,et al.  Physarum polycephalum percolation as a paradigm for topological phase transitions in transportation networks. , 2012, Physical review letters.

[26]  A. Tero,et al.  Rules for Biologically Inspired Adaptive Network Design , 2010, Science.

[27]  Arie van Deursen,et al.  Domain-specific languages: an annotated bibliography , 2000, SIGP.

[28]  Steve Cooper,et al.  Reflections on Stanford's MOOCs , 2013, CACM.

[29]  Alexander Serebrenik,et al.  StackOverflow and GitHub: Associations between Software Development and Crowdsourced Knowledge , 2013, 2013 International Conference on Social Computing.

[30]  M. Brenner,et al.  Random network peristalsis in Physarum polycephalum organizes fluid flows across an individual , 2013, Proceedings of the National Academy of Sciences.

[31]  Paulo Blikstein,et al.  Bifocal modeling: a study on the learning outcomes of comparing physical and computational models linked in real time , 2012, ICMI '12.

[32]  Minjae Lee,et al.  RNA design rules from a massive open laboratory , 2014, Proceedings of the National Academy of Sciences.

[33]  Andrew Adamatzky,et al.  Physarum Machines: Computers from Slime Mould , 2010 .

[34]  Jagadis Chunder Bose.  On the determination of the wave-length of electric radiation by diffraction grating , 1897, Proceedings of the Royal Society of London.

[35]  M. Mitchell Waldrop,et al.  Education online: The virtual lab , 2013, Nature.

[36]  Thomas Hankemeier,et al.  Lab-on-a-chip technologies for massive parallel data generation in the life sciences: A review , 2011 .

[37]  G. Whitesides.  The origins and the future of microfluidics , 2006, Nature.

[38]  Burak Dura,et al.  Design, engineering and utility of biotic games. , 2011, Lab on a chip.

[39]  Z. Zacharia,et al.  Physical and Virtual Laboratories in Science and Engineering Education , 2013, Science.

[40]  Noah S. Podolefsky,et al.  When learning about the real world is better done virtually: A study of substituting computer simulations for laboratory equipment , 2005 .

[41]  Yuan F. Zheng,et al.  Automatic liquid handling for life sciences - A critical review of the current state-of-the-art , 2009, 2008 IEEE International Conference on Robotics and Biomimetics.

[42]  N. Stanietsky,et al.  The interaction of TIGIT with PVR and PVRL2 inhibits human NK cell cytotoxicity , 2009, Proceedings of the National Academy of Sciences.

[43]  Paulo Blikstein.  Connecting the science classroom and tangible interfaces: the bifocal modeling framework , 2010, ICLS.

[44]  Luís Gomes,et al.  Current Trends in Remote Laboratories , 2009, IEEE Transactions on Industrial Electronics.