We could still use more applicants for this position, so bumping the open position...

Available: Research position Biological Data Visualization and Visual Analytics


Keywords: biological data visualization; visual analytics; data integration; genomics; postdoc

Are you well-versed in the language of Tufte? Do you believe that visualization plays a key role in understanding data? Do you like to work in close collaboration with domain experts using short iterations? And do you want to use your visualization skills to help us understand what makes a cancer a cancer, and what distinguishes a healthy embryo from one that is not?

We're looking for a motivated data visualization specialist to help biological researchers understand variation within the human genome. Methodologies exist for analyzing this type of data, but are still immature and return very different results depending on what assumptions are made. The type of data can also be used for a huge amount of different research questions, which necessitates developing very exploratory tools to support hypothesis generation.

Profile
The ideal candidate is well-motivated, holds a PhD (or at least MSc) degree in computer science or bioinformatics, and has experience in data visualization (e.g. using tools like D3 [http://d3js.org] or Processing [http://processing.org]). Prior experience working with DNA sequencing data and genome-wide detection of genetic variation would be an advantage but is not crucial. Good communication skills are important for this role.

You will collaborate closely with biologists and contribute to the reporting of the project. You will be able to work semi-independently under the supervision of a senior investigator, mentor PhD students, and contribute to the acquisition of new funding. A three-year commitment is expected. Start date is as soon as possible.

Relevant publications

  • Medvedev P, Stanciu M & Brudno M. Computational methods for discovering structural variation with next-generation sequencing. Nat Methods 6(11):S13-S20 (2009)
  • Nielsen CB, Cantor M, Dubchak I, Gordon D & Ting W. Visualizing genomes: techniques and challenges. Nat Methods 7:S5-S15 (2010)
  • Bartlett C, Cheong S, Hou L, Paquette J, Lum P, Jager G, Battke F, Vehlow C, Heinrich J, Nieselt K, Sakai R, Aerts J & Ray W. An eQTL biological data visualization challenge and approaches from the visualization community. BMC Bioinformatics 13(8):S8 (2012)

Application
For more information and to apply, please contact Jan Aerts (jan.aerts@esat.kuleuven.be, @jandot, +Jan Aerts). If possible, also send screenshots and/or screencasts of previous work.
 
URL: http://www.kuleuven.be/bioinformatics/
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Ryo Sakai reminded me a couple of weeks ago about Simon Sinek's excellent TED talk "Start With Why - How Great Leaders Inspire Action"; which inspired this post... Why do I do what I do?

The way data can be analysed has been automated more and more in the last few decades. Advances in machine learning and statistics make it possible to gain a lot of information from large datasets. But are we starting to rely to much on those algorithms? Different issues seem to pop up more and more. For one thing, research in algorithm design has enabled many more applications, but at the same time makes these so complex that they start to operate as black boxes. Not only to the end-user who provides the data, but even for the algorithm developer.
2

"I'll do Angelina Jolie". Never thought I'd say that phrase while talking to well-known Belgian cartoonists, and actually be taken serious.

Backtrack about one year. We're at the table with the crème-de-la-crème of Belgium's cartoon world (Zaza, Erwin Vanmol, LECTRR, Eva Mouton, ...), in a hotel in Knokke near the coast.  "We" is a gathering of researchers covering genetics, bioinformatics, ethics, and law. The setup: the Knokke-Heist International Cartoon Festival.

We could still use more applicants for this position, so bumping the open position...

SymBioSys is a consortium of computational scientists and molecular biologists at the University of Leuven, Belgium focusing on how individual genomic variation leads to disease through cascading effects across biological networks (in specific types of constitutional disorders and cancers). We develop innovative computational strategies for next-generation sequencing and biological network analysis, with demonstrated impact on actual biological breakthroughs.

Since the publication of the human genome sequence about a decade ago, the popular press has reported on many occasion about genes allegedly found for things ranging from breast size, intelligence, popularity and homosexuality to fidgeting. The general population is constantly told that the revolution is just around the corner.
2

Bit of a technical post for my own reference, about visualization and scripting in clojure.

Clojure and visualization

Being interested in clojure, a tweet by Francesco Strozzi (@fstrozzi) caught my attention last week: "A D3 like #dataviz project for #clojure. Codename C2 and looks promising. http://keminglabs.com/c2/. They need contribs so spread the word!" I tried a while ago to do some stuff in D3, but the javascript got in the way so I gave up after a while.

Finally time to write something about the biovis/visweek conference I attended about a week ago in Providence (RI)... And I must say: they'll see me again next year. (Hopefully @infosthetics will be able to join me then). Meanwhile, several blog posts are popping up discussing it (see here and here, for example).

This was the first time that biovis (aka the IEEE Symposium on Biological Data Visualization) was organized.

I was invited last week to give a talk at this year's meeting of the Graduate School Structure and Function of Biological Macromolecules, Bioinformatics and Modeling (SFMBBM). It ended up being a day with great talks, by some bright PhD students and postdocs. There were 2 keynotes (one by Prof Bert Poolman from Groningen (NL) and one by myself), and a panel discussion on what the future holds for people nearing the end of their PhDs.
4

Last Friday I received my long-anticipated copy of "Visualize This" by Nathan Yau. On its website it is described as a "practical guide on visualization and how to approach real-world data". You can guess what my weekend looked like :-)

Overall, I believe this book is a very good choice for people interested in getting started in data visualization.

UPDATE: I encountered a blog post by Martin Theus describing a very similar approach for looking at this same data (see here).

Disclaimer 1: This is a (very!) quick hack. No effort was put in it whatsoever regarding aesthetics, interactivity, scaling (e.g. in the barcharts), ... Just wanted to get a very broad view of what happened during the Tour de France (= biggest cycling event each year).

Disclaimer 2: I don't know anything about cycling.
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Welcome
Hi there, and welcome to SaaienTist, a blog by me, for me and you. It started out long ago as a personal notebook to help me remind how to do things, but evolved to cover more opinionated posts as well. After a hiatus of 3 to 4 years (basically since I started my current position in Belgium), I resurrect it to help me organize my thoughts. It might or might not be useful to you.

Why "Saaien tist"? Because it's pronounced as 'scientist', and means 'boring bloke' in Flemish.
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