[Interview] Gerd Moe-Behrens–Leukippos: Synthetic Biology Lab in the Cloud

HackYourPhD had the chance to interview Gerd Moe-Behrens about his project, the Leukippos Institute.
He also shared his vision about the future challenges and perspectives for Open Science.

Who are you?

gerdI have a PhD from the Faculty of Medicine, University of Oslo, Norway. During a brief Post Doc at the Max Planck Institute for Molecular Genetics, Berlin, Germany my scientific focus was on Induced Pluripotent Stem Cells. This work introduced me to Systems Biology. This was the starting point for my interest in Synthetic Biology. Moreover, I have a background in computer science, and work as an Apple developer. I am the founder of the Leukippos Institute for Synthetic Biology, a research institute solely in the cloud. I have a strong interest to explore novel forms of scientific work on a web platform. My present work is in the intersection between computer science and biology. I am founder and CEO of a company (CytoComp – http://www.cytocomp.com) developing a microprocessor built from biological parts (see my recent review http://bit.ly/1cwM43X).

What is Leukippos?

Leukippos is a cloud based collaboration platform.

Social networks and the ability to organise collaborative work via the cloud will become important factors in driving innovations in modern science and technology.These social networks provide a potential frame for a global connectivity among researchers. This dramatically expands our combined knowledge, expertise and abilities, because large groups of people are more likely to find solutions to complex problems (Nielsen). Moreover, collaborations become independent of the physical location of the collaborators or the development level of the member countries, thus, reducing the transaction costs to zero (Treuille). In addition, social networks can also help to deal with the enormous amount of data accumulated as it is very difficult for a single individual to analyze and process such data.
At Leukippos we try to find out how to organize such cloud collaboration (http://bit.ly/TtuNOP). We focus on Synthetic Biology dry lab work as this is very well suited for online collaboration. Everybody with a computer and internet access can join independent of their location.

The mission of Leukippos is to build a synthetic biology dry lab in the cloud open for everybody with interest in this kind of work.

 A list of our core team can be found on our webpage.

How did the project emerge?

The Leukippos Institute was founded in summer 2010. I see “networked science” as a revolutionary tool, which has enormous potential for the scientific discovery process. I think it is very exciting to figure out how to organize such collaboration and thus started with a webpage announcing the project. I was tweeting about the project and soon got other people interested to join. We have in the following done many experiments in order to find out how to organize cloud collaboration. These experiments were reaching from a journal club to experimenting with a web application for idea generation.
We have both worked a lot on our coding platform and also how to organize the social part. We figured out, that the most successful strategy was to build on top of major social networks. Especially our Facebook group works very nice to organize the social network. A brief introduction to our coding platform can be found on our web site.

What are the current ongoing projects?

At present we are working on two mobile web applications:

  1. SynBioAppSelector: We crowd sourced all existing synthetic biology software and built a mash-up app where you can search for software in a novel way.
  2. SynBrick: Game for synthetic biology inspired by FoldIt.

Very early prototypes for both apps can be found on our webpage.

How this has been integrated in your career as researcher?

Basically, Leukippos represents an experimental approach. I have no commercial or career interest with this project. Leukippos is a not for profit, open science experiment. We are financed by voluntary work and crowd funding. All donations are welcome.

My driver is my personal interest and fascination for these novel forms of how to do science.

My career focus is on my company CytoComp.

What are the major changes you have noticed in the scientific community recently?

As we move to the digital age, there are three main changes:

1. Social networks & Social systems
Social networks and cloud collaboration will, as described above, change the scientific methodology. This will have major impact in the scientific discovery process.
Moreover recent developments in open online education will have impact on the traditional tenure track system. In combination with a lack of public funding for at least the next ten years, we will see very few public financed positions, a tendency we already can observe. This will place science in a novel economic context of private funding and entrepreneurship.

2. Big data
An important trend is the enormous storage and processing capacity which has emerged (http://bit.ly/TtuNOP). “We talk about a magnitude in the “petabyte” scale, which is equivalent to 1000 terabytes (TB) = 1 quadrillion bytes = 10E+15 bytes. Google processes about 24 petabytes per day. Within the last decade or so, scientific research (such as research in biology, bioinformatics, and medicine, to name a few) has increasingly produced vast amounts of data from high throughput experiments. We have also witnessed an exponential increase in the number and/or size of data sets, in particular in biology and bioinformatics research. For example, the 1000 Genomes Project has so far produced 200 TB publicly available data sets since its inception. Moreover, the output in scientific literature has become so vast and complex, that it has become difficult to read, assimilate and process such research production.” (http://bit.ly/TtuNOP)

Systems theory can give us a theoretical ground of how to deal with this data amount.

A talk about our move from hypothesis to data driven science can be found here (http://bit.ly/OkBAMt). Both analysis of data in a social context and automated analysis in form of the semantic web might contribute to solve this problem.

3. Publication
Open access will be crucial to solve the big data problem. We need structurally that papers are publish in the form of the semantic web, and allow robots to crawl this information. Moreover, the publication industry is changing as a whole. We move away from a system where a little group of editors was defining the agenda. Modern publication is ongoing in a social context. We can publish directly on the web and do not need the middle man any longer. It looks like, that we will get a system of direct publishing in a social context and maybe post publication review.

Publications will be more dynamic. Thus experiments get published real time and are discussed and further developed in a social context.

A major question will also be, if the publication format at all is adequate in our digital age or if other kinds of applications will substitute it, such as applications which can present data in novel forms. Thus, the business model of the academic scientist (high impact factor journal publications results in a tax payer financed position) is in question.

What are the key challenges that Open Science is facing?

The main problem is how to finance open projects. Entrepreneurial thinking might show novel directions. Another important challenge will be how to structurally organize open science projects. The Leukippos project is trying to find answers with the many experiments we are performing. It will be important to find the right people for projects, motivate them and be able to fragment a project, so that everybody can get a specific task fitting their interests. A good role model is the development of the Linux operating system. The way the development of this software has been organized might provide hints of how we can organize science projects.

How would you define Open Science, as a movement, values, methods?

Open software development might be the initial role model. Science has fallen behind, as people are bound by the above mentioned outdated business model for scientists. Values and methods are still under development. We can learn a lot from open software development. A very good book discussing these questions is: Reinventing Discovery: The New Era of Networked Science by Michael Nielsen. An application for the correct framework (a Facebook for science) still needs to be developed.

How do you think young scientists can help?

We need to think out of the box and try to analyse the recent developments. People can help with a collaborative spirit and the will to try something new. By the way the people who adapt early to all these changes will be the winners of the future.
What we basically need is to collaborate.

We need to move away from the high impact factor obsession, and reorganize for this new context. Jump out of the train, put effort into figure out how to do it.

I don’t think anybody have figured it out yet. So we need to be open minded to experiment and try, not fear to fail.

If you like to try it out, you are very welcome to join us at Leukippos.


Official Leukippos website: http://www.leukippos.org
GitHub repository of Leukippos projects: https://github.com/Leukippos
Leukippos Facebook group: http://on.fb.me/1lnTRtM
Email: leukipposinstitute@googlemail.com