RSS

Monthly Archives: December 2008

Another collaborative environment: Project Wonderland

This is a short post on the Sun’s Project Wonderland. Citing from its home page

Project Wonderland is a 100% Java and open source toolkit for creating collaborative 3D virtual worlds. Within those worlds, users can communicate with high-fidelity, immersive audio, share live desktop applications and documents and conduct real business. Wonderland is completely extensible; developers and graphic artists can extend its functionality to create entire new worlds and new features in existing worlds.

In my recent post I’ve mentioned Second Life and Croquet: two platforms that can evolve into decent 3D visualization environments. Obviously I didn’t research the topic enough, as I’ve just found Project Wonderland. It seems to have the best of both worlds – professional team of developers, pretty flexible architecture and possibility of running your own instance of “virtual world”.

)

Have you spotted "Biogang" written on the whiteboard? 🙂

I didn’t play with it for a long time – current version is not very feature-rich (although it already contains video player with webcam support, PDF viewer, VNC viewer and a crude whiteboard), however the roadmap looks very interesting. I really liked extensive audio features – true stereo, sounds fade out with distance, special “cone of silence” (place where you can have a private conversation) – it proves that Sun is really trying to build an effective collaboration platform.

I haven’t seen yet much about data visualization in Wonderland – although below you can find interesting example of molecular simulation trajectory shown inside Wonderland.

Reblog this post [with Zemanta]
 
Comments Off on Another collaborative environment: Project Wonderland

Posted by on December 29, 2008 in Education, Research, Visualization

 

Tags: , , ,

Bioinformatics is a visual analytics (sometimes)

Short description of my research interest is “I do proteins” (I took this phrase from my friend Ana). I try to figure out what particular protein, protein family, or set of proteins does in the wider context. Usually I start where automated methods have ended – I have all kinds of annotation so I try to put data together and form some hypothesis. I recently realized that the process is basically visualizing different kind of data – or rather looking at the same issue from many different perspectives.

It starts with alignments. Lots of alignments. And they all end up in different forms of visual representation. Sometimes it’s a conservation with secondary structure prediction (with AlignmentViewer or Jalview):

blog-0005

Sometimes I look for transmembrane beta-barrels (with ProfTMB):

blog-0005

Sometimes I try to find a pattern in hydrophobicity and side-chain size values across the alignment (Aln2Plot):

blog-0005

Afterwards I seek for patterns and interesting correlations in domain organization (PFAM, Smart):

blog-0008

Sometimes I map all these findings onto a structure or a model that I make somewhere in the meantime based on found data (Pymol, VMD, Chimera):

blog-0006

I also try to make sense out of genomic context (works for eukaryotic organisms as well – The SEED):

blog-0005

I investigate how the proteins cluster together according to their similarity (CLANS):

blog-0013

And figure out how the protein or the system I’m studying fits into interaction or metabolic networks (Cytoscape, Medusa, STRING, STITCH):

blog-0007

If there’s some additional numerical information I dump it into analysis software (R, for simpler things DiVisa):

blog-0005

And I make note along the process in the form of a mindmap (Freemind, recently switched to Xmind, because it allows to store attachments and images in the mindmap file, not just link to them like Freemind does):blog-0010

So it turns out that I mainly do visual analytics. I spend considerable amount of time on preparing various representations of biological data and then the rest of the time I look at the pictures. While that’s not something every bioinformatician does, many of my colleagues have their own workflows that also rely heavily on pictures. For some areas it’s more prominent, for others it’s not, but the fact is that pictures are everywhere.

There are two reasons I use manual workflow with lots looking at intermediate results: I work with weak signals (for example, sometimes I need to run BLAST at E-value of 1000) or I need to deeply understand the system I study. Making connections between two seemingly unrelated biological entities requires wrapping one’s brain around the problem and… lots of looking at it.

And here comes the frustration. I counted that I use more than twenty (!) different programs for visualization. And even if I’m enjoying monitor setup 4500 pixels wide which is almost enough to put all that data onto screen, the main issue is that the software isn’t connected. AlignmentViewer cannot adjust its display automatically based on the domain I’m looking at or a network node I’m investigating – I need to do it by myself. Of course I can couple alignments and structure in Jalview, Chimera or VMD but I don’t find such solution to be usable on the long run. To have the best of all worlds, I need to juggle all these applications.

I’ve been longing for some time already for a generic visualization platform that is able to show 2D and 3D data within the single environment, so I follow development of SecondLife visualization environment and Croquet/Cobalt initiatives. While these don’t look very exciting right now, I hope they will provide a common platform for different visualization methods (and of course visual collaboration environment).

But to be realistic, visual analytics in biology is not going to become a mainstream. It’s far more efficient to improve algorithms for multidimensional data analysis than to spend more time looking at pictures. I had already few such situations when I could see some weak signal and in a year or two it became obvious. But I’m still going to enjoy scientific visualization. I came to science for aesthetic reasons after all. 🙂

Reblog this post [with Zemanta]
 

Tags: , , , , , , , ,

End of freelancing as scientist (for now)

The patchwork landscape of Masuria
Image via Wikipedia

Almost a year ago I wrote a post about officially becoming “freelance scientist”. I didn’t really know what I was doing, but taking over the world from a small flat in the middle of nowhere in Poland sounded like a good idea. And it definitely was a good idea, however not in a way I thought it would be. Today I am hoping that all things will go fine and I’ll be employed since February in a calm academic environment.

What I aimed for?

My plan was to become freelance scientist – to be able to thrive financially and intelectually without relying on gaming grant systems. I had hoped to secure support from private sources, form a virtual institute and live happily in the middle of nowhere while still having an impact on the world’s science, possibly all under “open research” badge.

What didn’t work?

Side comment: if you read excellent piece by Hugh MacLeod entitled “How to be creative”, you shouldn’t find the issues below surprising :).

The main reason I started to look for a job already some weeks ago was that freelancing as a scientist turned out to be unsustainable financially. And don’t get me wrong – money wasn’t an issue, as long as I was willing to put all my time into other’s people projects. All. My. Time. Booking some time to work on my own ideas meant burning savings at a quick rate. But I had to work on my own ideas. I didn’t feel like I’m learning very much, because I worked on things I was already quite good at. Intellectual stretching was not that big.

Because of the issue above, I’ve put together far less work than I aimed to. I have lots of posts, manuscripts and presentations which I didn’t have time to finish. I was too busy doing freelance work, finishing the projects I had promised to do, inventing new projects and hiding under a bed worrying about where this is all going.

Working in the middle of nowhere was a plain mistake. It sounds nice, but f2f networking (“showing up”) is far more important than I’ve thought. Working in Poland is an issue on its own (no matter if you’re a freelancing or an academic scientist); working outside of any major city makes it even worse.

Partially connected to the former issue was the fact that I tried to do all things alone. Wrong. Very wrong. Things like virtual institute will not work, unless there’s a team. Period.

And finally, I didn’t give myself enough time to make the whole system work. It turned out that I had no idea about so many things influencing money-flow in the system, that it’s not surprising at all that it didn’t click in so short (12 months) time.

What worked?

One of two biggest advantages of this crazy 12 months was that it was a great learning experience. When I look at my older colleagues working in academic environment, I’m pretty sure they don’t experience “felling like an idiot” moments all that often. Such moments happen quite frequently in grad school, but seem to become rarer the further science career advances. On a contrary, I had such moments all the time in the last year. I was experimenting with blog posts, stupid ideas, unbalanced opinions and I was scared as hell each time. And I have learnt much more than I would do playing safe. Have you watched Ken Robinson’s talk at TED? He put a beatiful phrase – “prepared to be wrong”. Keep that in mind.

People were second most important factor here. I was amazed by a number of people that have helped me along the way. Lots of them have encouraged me, pointed to useful resources or invested significant amount of time into answering my silly questions. Many times I was blown away by the help I had not expected. Biogang/Life Scientists community rules.

Frequently quoted phrase from Bill Hooker’s essay, “I’ve never had an idea that couldn’t be improved by sharing it with as many people as possible — and I don’t think anyone else has, either.”, turned out to be absolutely true. Each time I presented my ideas, people were interacting with them, not judging them. I was given suggestions I would not come up with by myself, even if it was clear that we’re not going to do business together.

What now?

The job I hope to land next year is going to address the things I’ve written about above. I hope to have some financial stability and necessary time to advance my plans. It will also provide a support for such events like “Startup weekend in science”, which I plan to invite you all later next year.

The main goal is still valid and I don’t give up on it. I’ve found (or rather the other way round) a real-life example, ProTech Institute from Lithuania, which means that it can be done – it’s just a little harder if you’re a (still,  but not for long) PhD student.

So it’s end of freelancing for now. Lessons learned. Back to real-lifeâ„¢ again :).

Reblog this post [with Zemanta]
 
14 Comments

Posted by on December 9, 2008 in Career, Comments