Science

Understanding genetic interaction networks

Here is a video of a talk I gave at the Newton Institute in Cambridge on Understanding genetic interaction networks as part of a Programme on Theoretical Foundations for Statistical Network Analysis.

I would have liked to embed the video, but wordpress didn’t let me. So click here please:

http://sms.cam.ac.uk/media/2284116/embed

At the end is a surprisingly long Q&A about what type of analysis did and did not go into the iconic Figure 1 of Costanzo et al 2010. I need to learn the magic words “What a great question! Let’s discuss it offline…”

Florian

Science

Research Highlight: Computing tumor trees from single cells

Edith‘s OncoNEM paper made it into the Genome Biology Special Issue on Single-Cell Omics, together with a paper on a tree inference method called SCITE by Niko Beerenwinkel’s group.

If you need any more evidence that our two papers were -at least in my totally unbiased opinion- the obvious highlights of the whole Special Issue, just observe that Alexander Davis and Nick Navin chose us to write a Research Highlight about. They conclude:

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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 roland.schwarz@mdc-berlin.de and mention the reference number 1068x/2016 where x is in {0,1,2}.

Florian

Duty Calls, Science

If I don’t get it, you should be concerned.

The latest post at Shit My Reviewers Say is “My first concern is that I don’t get it.

And the obvious response is illustrated by a picture saying “Your problems with me are not my problems, those are your problems.

What can you do as an author if the reviewer is just too stupid to understand your ingenuity?

But … and this is a big but … there are areas of research where I would use that reviewer’s comment myself. If, say, you are writing about probabilistic models in cancer genomics and I can’t make any sense of what you are saying, it is your problem, not mine.

Here is an example. The ABSOLUTE paper on “Absolute quantification of somatic DNA alterations in human cancer”.

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Science

Ask me anything at PLOS Science Wednesday on May 18

PLOS Science Wednesday is a weekly science communication series featuring live, direct chats with PLOS authors on redditscience (/r/science), the popular online gathering place for researchers, students and others interested in science which has over 8 million registered members. The series provides a forum for PLOS authors to communicate their work and interact directly with fellow researchers and the public.

You can find the complete schedule here.

And on May 18th it’s my turn to answer anything together with my colleague James Brenton.

And when I say ‘anything’ I mean ‘anything about cancer evolution’.

Florian

Science

UAI 2016 Workshop on Machine Learning for Health

Machine Learning for Health: Learning to understand human disease

Machine learning is revolutionizing our understanding of many human health problems from obesity to cancer. With ever increasing amount of data coming from this domain, computational biology and medicine are also transforming the machine learning community by not only providing new applications but also inspiring new modeling frameworks and learning paradigms.

The goal of this workshop is to bring together machine learning scientists and computational biologists. We would like to showcase recent advances in this field and discuss challenges in computational methodology and biomedical application.

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Career, Science

Open positions – cancer evolution and networks

I have three open positions in my lab:

  1. A PhD student position for “Single-cell analysis of cancer evolution” http://www.jobs.cam.ac.uk/job/10282/
  2. A postdoc position for “Evolutionary biology in cancer”. This position is ideal for somebody trained in evolutionary biology in model systems to make the transition to biomedical applications in cancer.
  3. And finally a postdoc position broadly advertised as “Computational cancer genomics” but actually having a strong network focus. http://www.jobs.cam.ac.uk/job/10265/

More info here http://www.markowetzlab.org/positions.php

Any questions, just contact me directly.

Florian

Science

Inferring tumor evolution from single-cell genomes

Series on Tumor Evolution

Everything is better if you do it with a Nested Effects Model – even inferring tumor evolution.

Let me introduce to you Oncogenetic Nested Effects Models, or for short OncoNEMs, which we just published in the new Single Cell collection of Genome Biology (see here). They exploit the fact that tumors accumulate mutations while they evolve, which leads to (noisy) subset relations between clones – exactly the type of pattern NEMs were made for.

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Science

“Look at me, I was a terrible supervisor”

“I was a terrible PhD supervisor. Don’t make the same mistakes I did,” writes Sian Townson in the Guardian.

Lots of points I agree with:

Research points to high levels of depression among PhD students.

I am not surprised. This is one of the reasons Cambridge has such an active counseling service and, as far as I can see, there is little stigma attached to using it.

I also share her observation about the lack of training for supervisors:

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Science

‘Five selfish reasons’ is one of Genome Biology’s Most Influential Articles of 2015

Genome Biology just sent an email around with 2015’s Most Influential Articles, according to Altmetric.com.

And, guess what, one of mine made the Top 10: Five selfish reasons to work reproducibly  from last December — really a late-comer to the competition.

And so, my fellow scientists: ask not what you can do for reproducibility; ask what reproducibility can do for you! Here, I present five reasons why working reproducibly pays off in the long run and is in the self-interest of every ambitious, career-oriented scientist.

Now I just need one of my research papers to have the same impact as my opinions, and I’d be sorted …

Florian

 

Science

First parasites, now online harrassment – how has transparency harmed you lately?

An interesting post at Political Science Replication:

Getting the idea of transparency all wrong

Following an article in the New England Journal of Medicine, which portrayed scientists who re-use data as parasites, we now hear more on this from Nature. Apparently, data transparency is a menace to the public. The Nature comment “Don’t let transparency damage science” claims that the research community must protect authors from harassment by replicators. The piece further infects the discussion about openness with more absurd ideas that don’t reflect reality, and it leads the discussion backwards, not forward. 

Read more at https://politicalsciencereplication.wordpress.com/2016/01/29/getting-the-idea-of-transparency-all-wrong/

Duty Calls, Science

I am a research parasite. Got a problem with that?

In case you wondered what’s wrong with biomedical research, just read this editorial on data sharing by Longo and Drazen in the New England Journal of Medicine, a leading journal in the field. What you will find is a desperate attempt to take data hostage and to enforce co-authorships for people who didn’t make any intellectual contributions.

But let’s take it one step at a time. What did Longo and Drazen actually say? They think there are major problems with sharing data fully, timely and openly.

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