Readers of this blog who rely on RSS feeds may have not noticed that I had put a separate page containing computer-generated images of various molecules – Molecular renderings. Any comments, suggestions, critique are always welcome.
From time to time I’ll post new images there – from time to time I need to remind myself that science is pretty too :).
Impressive thing about Qutemol rendering with ambient occlusion is that this method is used in real time. I’ve put a small video showing a difference between typical rendering and Qutemol’s method (well, I hope it’s visible, quality of this video is pretty bad, but it’s my first file posted on YouTube).
The bad thing about Qutemol is that so far it works mostly only on the Windows OS (I’m not the last person having problems running it on the OSX). Linux users are out of luck – Qutemol needs hardware support for 3D rendering, so a virtual machine with Windows is not a solution.
Currently almost all scientific journals provide a RSS feed of their content. I am very grateful for that, as many other scientists. However, I see a large disproportion between what I would like to scan through and what I’m actually able to. Abstracts, which are usually provided in these feeds, look almost exactly the same, and after thirty or fifty I’m not really sure if I understand what I read (most likely even Robert Scoble would have the same problem, although at a different level). Biochemistry journal found a solution (see below) – providing images instead of abstracts in the feed (in fact, they used this approach on their homepage long before RSS feeds became a standard). It’s simple, very effective and I have no idea at all why it’s not more popular. So here I’m asking – publishers of scientific journals: please give me images in the journal’s feed. I don’t mind having also the abstracts, but visual summary would be much more useful. In return I promise read these feeds instead of relying on Pubmed searches or my colleagues recommendations and GR shared items.
(via The Biotech Weblog) BioMed Central has launched the Biology Image Library – online collection of scientifically interesting and meaningful images across biology and biomedicine.
Most of the images at BIL are available free of charge for non-commercial purposes (like teaching), but buying commercial-use rights is also possible. I don’t really agree that the library is aimed at students (teachers, lecturers – maybe), since personal subscriptions are $293 per annum and I could imagine that institute subscriptions are not cheaper. UPDATE: See comments below. To me a corporate client is a main target of this initiative, but I may agree that relatively high subscription rates may be dictated by the nature of the images – most of them come from experiments (almost no computer generated illustrations).
Microstock photography sites hold quite a lot of science-related images, however their scientific value is very often zero (as an example, search for DNA). It is overall nice idea to have a scientific equivalent of a microstock, but I would rather leave the subscriptions out and release low quality (for web/computer screen use) material under non-commercial Creative Commons license.
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I got the privilege of hosting the next edition of Bio::Blogs. If you have anything you would like to have included please send an email to szczesny dot pawel at gmail dot com or to bioblogs at gmail dot com before 1st of November.
The title says it all – have a look at Steve Brenner’s commentary in Nature (looks like its freely accessible) and the Genome Commons web page.
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Yes, you can use Blender to prepare figures for your next paper and the results for sure will look different than the ones obtained with a standard software (hemoglobin [1HBG] as example below)… But given amount of work and really steep learning curve (at least for somebody who tries that for the very first time), I would not recommend Blender that much… 🙂
UPDATE: if you look for a way to import a PDB file into Blender, some instructions are at the bottom of this page.
I’ve just read an introduction to the supplemental issue of the journal PROTEINS, dedicated to the most recent round of the CASP experiment. It describes the progress of the protein structure prediction over the last few CASP editions.
The list of advancements include:
I believe that this was possible thanks to the progress that has been made in the area of sequence homology searches. Finding similarity between two sequences well beyond any reasonable identity thresholds is now doable thanks to profile-to-profile comparison, meta-servers (joining predictions from many different methods) or recent hmm-to-hmm algorithms (comparison of Hidden Markov Models). If you can find a suitable template for your protein, the rest is then much easier, isn’t it?
There are of course fields that still need some work. One of these often stirs a lot of discussion: automated assessing of model similarity to the real structure. The current methods have proven their suitability, I definitely agree. However I hope that at some point the protein structure comparison software will refuse to superimpose eight- and ten-stranded beta-barrels or left- and right-handed coiled-coil with a message: “It doesn’t make sense.”
Yet another secretion system was described, this time from Gram-positive bacteria (types I to VI were from Gram-negative). I expect that the further microbiology will go from E. coli, the more secretion systems will be found. Within the large spectrum of bacterial species we still know very little on bacteria outside proteobacterial group.
This is from Nature Reviews Microbiology, and subscription may be required.
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Shared items GR starred items (not necessarily scientific)
Freelancing science 
Wolfram Mathematica 6 – no New Kind of Science (yet)
Not so long ago Animesh Sharma pointed to quite old interview of Steven Wolfram about the book “The New Kind of Science” and asked if concepts concerning a biological framework made their way into Mathematica software.
I’ve just returned from Poland Mathematica Conference, and I can answer that question: no, they didn’t. While there were people using Modelica and Mathematica to model some stochastic processes in cells, Mathematica itself does not provide much of a support for any sophisticated description of biological mechanisms. Implications of concepts from The New Kind of Science book looked very promising – it’s a pity that we are not given tools to verify them ourselves.
Posted by Pawel Szczesny on October 30, 2007 in bioinformatics, Comments, Software
Tags: bioinformatics, mathematica, wolfram