Tag Archives: biology

Play Game, Do Science

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And finding a cure for cancer is definitely lvl 80.

My daily reading usually does not include anything from Science or Nature, but this article stood out among all the other academia mumble-jumbos.  In a nut shell, the paper described a software that evaluates protein conformations faster than any existing computer.  How?  By taking advantage of human brain’s immense cognitive power.  Researchers found that even a casual player (non-biochemist) can solve complex protein folding problems much faster than a computer.  (Ars has some very good background info explaining the biology aspect of the paper, take a look if you are unfamiliar with terms like amino-acid and hydrophilicity)

So a game called FoldIt is devised to takes advantage of of people’s boredom.  A series of incrementally difficult scenarios teaches players the basic mechanics of the game, then real data is streamed from online for player to solve.  Results are sent back for cumulative analysis.  So far, the result looks wonderfully promising.  It turns out, our monkey brains can easily out-perform a cluster of Intel i7s, both in accuracy and speed.

In the US, 200,000 Million (200Billion) hours are spent in front of a television, each year.  A total of 500 million hours were spent in Second Life in 2009, and a mere 100 million hours was spent in creating the entire Wikipedia.  Perhaps we can cure cancer in a week if we all just skip our weekly quota of Grey’s Anatomy?

Biochemical Visualization Using Blender

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Here at the Scientific Visualization Unit of the National Research Council in Pisa, Italy, we have been using Blender since 2008 for doing some very interesting bio-molecular visualization at the sub-cellular level.  I myself joined the team just over 3 months ago, and am eager to share some of our work with the Blender community now that the Italian soccer team can stop embarrassing themselves in South Africa.

We use Blender to visualize protein motions and interactions, as well as making short animations that show the inside of a cell in a way that had never been seen with the unaided eye.  Because one key focus of the project is scientific accuracy, a lot of time is spent to ensure that the visualization is not only nice-looking, but also scientifically accurate. The process involves using numerous third-party programs to convert the input data (atomic coordinates of a protein) into something Blender can read. We use Python extensively to help facilitate data conversion between different formats.  The result is this video:

To really appreciate the video, it helps to understand the science going on behind it.  If you are a bit lost, have a look at the explanatory note associated with the video.  The video is made and rendered with Blender in 1080p HD, we also toyed with stereoscopic rendering with some very good result.  You can download the HD stereo version from the SciVis site.

Currently, we are working to build an interactive protein viewer inside Blender.  Using Blender 2.5 as the platform, we built an interface that will allow biologist to load a text description of any protein (a PDB file), and Blender will display the imported file in an intuitive interactive viewer. (As shown below)

Why Blender? Blender is especially suitable for this task for several reasons. Its python support allows us to accomplish a lot of custom features in relatively very little coding.  Having a game engine and a physics engine built-in means we can use do realtime visualization all from one software package.  Its open source nature allows us to easily modify (at least have access to) the source code if needed.

Above is our BioBlender interface for Blender 2.5.  The protein on the right is MLCK backbone, a 1845 residue long protein.

There is still a lot of work to be done.  Blender is currently having a hard time handling large proteins that contains thousands of amino acid groups, the interface turns sluggish with as the number of object increases.   Surprisingly, the game engine performance is very fast, it manages to maintain 20fps on a laptop even with a fancy ambient occlusion shader.