Save 37% off PRO during our Black Friday Sale! »

The Automation of Science

The Automation of Science


Konrad Förstner

July 17, 2013


  1. The automation of science A lunch seminar talk Konrad U.

    F¨ orstner Sharma group & Vogel group July, 17th, 2013, W¨ urzburg
  2. This a subset of slides extracted from a lunch seminar

    talk given at the Institute for Molecular Infection Biology (IMIB).
  3. Disclaimer Yes, this might hurt and I might be wrong. – CC-BY by flickr user redjar
  4. Problem 1a: Common problem with large scale screenings Confirmation via

    manual, low-throughput methods (e.g. RNA-Seq analysis followed by northern blots to confirm candidates)
  5. Problem 1b: Scaling up experiments 10 - 100 repetitions possible

    1000 and more repetitions not possible
  6. Problem 1c: Craft vs. thinking Why does somebody who studied

    several years need to spend most of his/her time pipetting one liquid into another?
  7. Problem 2: Reproducibility/Transparency

  8. Two ways of running a BLAST query – GUI/web interface

  9. Two ways of running a BLAST query – command line

  10. Advantages of having a formal language for actions Transparency Reproducibility

    Scalability – CC-BY by flickr user jurvetson
  11. Claim We need more automation / formalization – especially in

    the life sciences. – CC-BY by flickr user jurvetson
  12. Motos ”Work on the business/system not in the business/system.” ”Be

    productive not busy.” ”Laziness is a virtue.” – CC-BY by flickr user jurvetson
  13. Microfluid system as one path – CC-BY by flickr

    user schlaus
  14. Challenges Price (as long as not coming a commondity) Lack

    of flexibility Formalization is hard Vendor lock-in ⇒ open standards required – CC-BY by flickr user jurvetson
  15. Example – the language EXACT

  16. Example – the robot scientist ADAM

  17. Example – A small LEGO Mindstorm hardware hack

  18. What is your hack? – CC-BY by flickr user