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?

In the morning, the attendees got a high level overview of what Blender can do, followed by a crash course on scientific visualization as applied to cellular biology and biochemistry as well as an extensive Python lesson.  In the afternoon, we moved to the computer lab and covered some of the Blender fundamentals, giving a lot of the attendees their first hands-on experience with Blender.

Even though this is my third time running such an event, there is still lots of rooms for improvement.  (For example, Blender 2.5′s UI was corrupt on some of the machines running older Ubuntu installations and Intel graphics chip, which made running the tutorials very challenging)

Photos of the event are on Pisaca.  Special thanks to the Pisa Linux User Group, without them, this workshop would not have been possible.

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.

The Sintel team simply isn’t doing a good enough job, they are doing a GREAT job, and I am sure color grading is a planned part of their pipeline.  I just got carried away a bit playing with these images :D

Even though snow should be white, it doesn’t hurt to give it some tone to communicate the extreme coldness.  Blue works well in this case.

Wow, the team is doing a great job with facial animation.  This looks like a very somber scene, so it calls for some gloomy color.  I also added a dark gradient from the top, anime style.  Split toning is used to maintain the skintone while pushing the background to a cool blue.

I am speculating here, but I wanted to create a contrast between the safety of the warm tent and the harsh cold outside.  So things close to the fire is made warmer, things further away is pushed to a chilling blue.  The histogram is also very left-biased (dark), so I brightened up the image a bit.

Here, our main character isn’t emphasized enough in this (what I assume would be) high motion scene due to the similarity in color. I added a warming filter to highlight Sintel to convey the classic warm-vs-cold, good-vs-evil, light-vs-dark concept.

Just added some warmth to make the image look a bit more organic and less CG.

Everything is done in Lightroom, which is an awesome postprocessing package for photos, but the same effect can be easily achieved in Blender’s composite engine.  But seriously, Sintel is going to be amazing.

Around the Blender community, I have seen some people approach Python with certain skepticism.  (“It’s programming, it must be hard!”)  But Python is intuitive.  Writing Python code is the closest one can get to writing in an natural language.  Compare with other languages, there is no semicolons, no excessive symbols and punctuations, no long compilation process before one can test the code.  To make a program in Python is a think-type-run process.

Blender 2.49 Scripting

Perhaps due to my recently found enthusiasm, I was given a chance to take a sneak peak at Michel Anders’ upcoming book Blender 2.49 scripting.  Flipping through this ~300 page book, I realized this is exactly what I would have asked for as a beginner wanting to learn how to script in Blender.  This wonderfully comprehensive book covers everything from editing object to working with material to PyDrivers, Constraints, IPOs and shapekeys.  The only notable omission seems to be the game engine component.

Sure you can look at the Blender API documentation for help, but ingredient lists does not make a cookbook.  As there still isn’t a centralized repository for Blender scripts in the Blender community,Michel managed to bridge a rather large knowledge gap with this book that is filled with useful snippet of code.

Python is not as fast as C, or as ubiquitous as Javascript.  But one can accomplish a task in Python at a fraction of the code and mental power it takes in other languages.  Which makes it an ideal language to learn as a beginner.

Blender 2.49 Scripting is available from Packt Publishing.  I eagerly awaits a second edition of the book, no doubt slewed for Blender 2.5 and Python 3?

Realtime visualization

Import > Simulate > Export

Going nuts with F-Curves

No words today.  Just pictures.

The project team is a well balanced mixture of scientists and artists, so you know you can expect something incredible from us :D.  The short movie they made had already been submitted to Siggraph 2010.

Isn’t Relief Mapping great?

Apart from all games that will inevitably take advantage of this technique, another application I can think of that will reap huge benefit from this is the loading and displaying of large-scale terrain visualization at virtually no CPU overhead.  A 4096×4096 DEM texture can be easily displayed at 60fps.  Whereas if the same data were to be converted to real geometry, most computers will die trying to render those 33million triangles.

Download the demo (4MB)

Blender 2.5|2.6 roadmap

Basically, 2.5 will be a series of transitional releases, the final stable release will be named 2.6 in all likelihood.