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. It's similar to the 2-year old vizbi, but has an agenda that is more focused on research in visualization rather than application of visualization in the biological sciences. Really interesting talks, posters and people.

The biovis contest
This first installment of biovis included a data visualization contest, focusing on "specific biological problem domains, and based on realistic domain data and domain questions". The topic this year was on eQTL (expression quantitative trait loci) data, and I'm really happy that Ryo Sakai -  now a PhD student in my lab - won the "biologists' favourite" award!! The biologist jury was impressed with the ease in which his visualizations of the eQTL data highlighted and confirmed prior knowledge, and how it suggested directions for further experiments. It was interesting to see that there was a huge variation in the submissions, going from just showing the raw data in an interesting way (which Sakai-san did) to advanced statistical and algorithmic munging of the input data and visualizing the end result (which the winner of the "dataviz professionals' favourite" award did). See how this relates to my previous post on humanizing bioinformatics?


Interesting talks - amazing (good & bad) talks
As this was the first time that I attended visweek, I was really looking forward to the high quality presentations/papers and posters. Overall, I got what I wanted. But there were some examples of papers and posters that I have major doubts about (taking into account that I have to be humble here in talking about people working in the field for far longer than I do).
One example that seemed pretty counterintuitive was a presentation by Basak Alper from Microsoft about a new set visualization technique that they baptized LineSets. The main issue that they want to solve is the visualization of intersections of >3 sets (up to 3 you'd just use Venn diagrams). Their approach is to connect the different elements from a set by a line; hence: linesets. However, I (and many others with me) felt that this approach has some very serious drawbacks. Most of all, it suggests that there is an implicit ordering of the elements, which there isn't. In the image below, for example, line sets were used to connect Italian restaurants (in orange) and Mexican restaurants (in purple). That's the only thing this visualization wants to do: tell me which of the restaurants are Italian and which are Mexican. But give this picture to 10 people, and every single one of them will think that the lines are actually paths or routes between these restaurants. Which they're not... The example below shows data that has specific positions on a map, but they demonstrate this approach on social networks as well.
LineSets
Another example comes from the biovis conference: TIALA or Time Series Alignment Analysis. Suppose you have the time-dependent gene expression values for a single gene, which you'd plot using a line plot. Now what would you do if you have that type of data for 100 genes? Would you put those plots into 3D? I know I wouldn't... And better still: would you then connect these plots so you end up with some sort of 3D-landscape? That's like connecting the tops of a barchart displaying categorical data with a line...

TIALA - Time Series Alignment Analysis


But of course there were plenty really good talks as well. Some of the talks I really enjoyed are those about HiTSEE (by Bertini et al) on the analysis of high-throughput screening experiments, EVEVis (Miller et al) on multi-scale visualization for dense evolutionary data, arc length-based aspect ratio selection (Talbot et al) which is an alternative to banking to 45 degrees, drawing road networks with focus regions (Haunert et al), and especially DICON which showed an amazing application of visual analysis of multidimensional clusters using healthcare data.

HiTSEE

EVEVis
Road networks with focus regions
DICON - interactive visual analysis of multidimensional clusters

Meeting interesting people
But of course this was very much about meeting interesting people as well. It was really nice to exchange ideas again with the biovis crowd (Nils Gehlenborg, Cydney, Tamara, Will Ray, ...), and I finally had the chance to have a chat with @filwd Enrico. All those discussions with Thorri from Icelandic DataMarket were both useful and fun (as was our day hanging out in town, chatting to the Occupy Providence woman (forgot her name, I'm afraid) and trying to find a good hat).
At the airport on my way back, as I was trying to find out how to get to Brussels (as our flights were cancelled due to the weather), a chap comes to me and introduces himself as someone from Belgium. From Leuven. From our very own faculty. So together with @infosthetics Andrew that now makes three of us :-)

Anyway: I'll definitely be back next year (have to play some more official role anyway) and already looking forward to it.

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.
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"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.
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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.
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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.
Welcome
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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