Career, Science

3 open positions in Roland Schwarz’ new lab in Berlin

The Max Delbrück Center for Molecular Medicine (Berlin) and the Berlin Institute for Medical Systems Biology (BIMSB) invite applications for

  1. PhD student (10681/2016)
  2. Postdoc (10680/2016)
  3. Scientific Programmer (10682/2016)

in the research group “Evolutionary and cancer genomics” of Dr Roland Schwarz.

The Schwarz lab investigates the relationship between genetic variation and complex phenotypes from an evolutionary perspective. A focus is thereby on the aetiology and functional implications of intra-tumour heterogeneity in human cancers. We are particularly interested in understanding the effect of structural variants and copy-number changes on cancer evolution in-vivo and closely collaborate with clinical partners to achieve this goal.

Send your application to and mention the reference number 1068x/2016 where x is in {0,1,2}.



Is there an alternative to ‘Excel is the devil’?

In my last post I shared the slides for my talk  “5 selfish reasons to work reproducibly”.

In my talk I stressed the importance of using scripts and code to make analyses reproducible. Instead of clicking, cutting and pasting as you would have to do in a tool like Excel.

I had also submitted my slides to the F1000 slides collection and after a few days got a very polite email back, asking me to rethink the keywords I had chosen in the submission:

Thank you for your slides submission: “5 selfish reasons to work reproducibly”.

Just a quick note to say that keywords are displayed alongside your presentation and are often how users will find your submission, by searching our site.

With this in mind, we were wondering if you had an alternative to “Excel is the devil” which might be more likely to appear on search results. [my emphasis]

First of all, I am impressed by how serious they take curating slides at F1000.

And, yeah, I might come up with some other keywords, even though I think ‘Excel is the devil’ remains quite accurate.

You can find the slides together with the new keywords (quite boring: Reproducible research, knitr, Sweave, Successful lab, Career advice) here:

Markowetz F.
Five selfish reasons to work reproducibly [v1; not peer reviewed].
F1000Research 2015, 4:207 (slide presentation)
(doi: 10.7490/f1000research.1000179.1)



Five selfish reasons for working reproducibly

And so, my fellow scientists: Ask not what you can do for reproducibility — ask what reproducibility can do for you!

The following is a summary of a talk I gave in my institute and at the Gurdon in Cambridge. My job was to motivate why working reproducibly is a good strategy for ambitious scientists. Right after my talk, Gordon Brown (CRUK CI) and Stephen Eglen (Cambridge DAMTP)  presented tools and case studies of reproducible work.

All materials are on github and below are my slides, thanks to slideshare:

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Books, Science

Life out of sequence – Hallam Stevens’ data-driven history of bioinformatics


How do people like you ever get last-author papers?” The person who asked me this question in 2008 during the interview for my current job was (and still is) a well-known stem cell biologist with decades of experience in science. But she still didn’t really know what to think of ‘people like me‘: bioinformaticians and computational biologists. Aren’t bioinformaticians just service providers? Handy to have, but without any real scientific vision and contribution? She clearly worried about my ability to do independent research.

And she wasn’t alone. A couple of years later I interviewed for an EMBO fellowship, which I didn’t get because the panel –mostly cell biologists, no one computational or from genomics or medicine– thought my group was a “mathematical service unit” and my research was “overly driven by my collaborators”. I’m still not sure what a ‘mathematical service unit’ could be (proofing theorems on demand maybe?) but their comments showed me how far removed their research practice was from my own.

Even though bioinformatics is by now an established field these personal experiences show that ‘old school’ biologists, who form the scientific establishment and direct mainstream research, are still very uncomfortable with ‘people like me’ who were trained in other disciplines, pursue biological questions different from their own, and use approaches not covered in classical biological training.

Life Out Of Sequence Cover

Hallam Steven’s book Life Out Of Sequence, A Data-Driven History of Bioinformatics starts with the tension between old and new biology that ‘people like me’ experience every day and describes the way biology has been and is being changed by computational methods.

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Philosophy, Science

Here be dragons! Thomas Kuhn, Statistics and System Biology

Here be dragons!

Thomas Kuhn had physics in mind when he wrote Structure of scientific revolutions but his key ideas also apply to statistics and systems biology and can explain some of the confusion in the field.

Thomas Kuhn’s Structure of scientific revolutions desribes the history of science as phases of normal science separated by revolutions and paradigm shifts. During normal science, research is guided by  a ruling paradigm, which identifies feasible problems and routes to tackle them. Normal science is a period of puzzle solving. The better your paradigm, the clearer the puzzle, the better your chances to solve it and progress.

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