The EMBO Journal non-scientific cover prize is awarded for the most interesting and beautiful image made outside the lab. Contestants may submit, for example, photos or artistic impressions of wildlife animals, plants or landscapes. Particularly welcome will also be hand or computer-generated paintings or drawings (or photographs of other works of art) related to a biological or molecular biological topic.
The EMBO Journal scientific cover prize is awarded for the most captivating and thought-provoking contribution depicting a piece of molecular biology research. Entries can include light or electron micrographs, 3D reconstructions or models of biological specimen or molecules, spectacular artefacts collected in the lab, original new views of lab equipment (but not of colleagues!), or other research-based images to be of interest to molecular biologists.
The 2011 winners have been announced. The scientific image winner was Heiti Paves, who submitted a confocal image of an Arabidopsis thaliana anther filled with pollen grains. The non-scientific winner was Dieter Lampl, with his "Blue Ice" photo — a glacier in Los Glaciares National Park in Patagonia.
My non-scientific entry (photo of fiber optics) received honourable mention and was included in the Favourites of the Jury gallery.
My non-scientific entry was an abstract image photo of fiber optics. It received honourable mention and were included in the Favourites of the Jury gallery.
The motivation and technical details behind these photos are described here.
My submission of a large Circos figure for its cover (see right), which was originally designed for a poster that introduced Circos, was awarded the 2010 EMBO Journal best scientific cover prize.
Some time ago, I did a personal project of photos of fiber optic strands. These worked out well. I had not done anything with these images, and thought they would make a competitive entry into the cover contest.
I revisited the fiber optic lamp with a higher resolution camera (Canon 5D — original images were from a Canon 20D) and a dedicated macro lens (Sigma 150mm f2.8 EX APO DG HSM Macro) (original images were shot with the Canon EF 24-70L).
From these new images, shown below, I created five EMBO Journal cover submissions.
The submissions would render on the cover as shown below.
This month we continue with the theme of Bayesian statistics and look at Bayesian networks, which combine network analysis with Bayesian statistics.
In a Bayesian network, nodes represent entities, such as genes, and the influence that one gene has over another is represented by a edge and probability table (or function). Bayes' Theorem is used to calculate the probability of a state for any entity.
In our previous columns about Bayesian statistics, we saw how new information (likelihood) can be incorporated into the probability model (prior) to update our belief of the state of the system (posterior). In the context of a Bayesian network, relationships called conditional dependencies can arise between nodes when information is added to the network. Using a small gene regulation network we show how these dependencies may connect nodes along different paths.
Puga, J.L, Krzywinski, M. & Altman, N. (2015) Points of Significance: Bayesian Statistics Nature Methods 12:277-278.
Puga, J.L, Krzywinski, M. & Altman, N. (2015) Points of Significance: Bayes' Theorem Nature Methods 12:277-278.
The Points of Significance column is on vacation this month.
Meanwhile, we're showing you how to manage small multiple plots in the Points of View column Unentangling Complex Plots.
Data in small multiples can vary in range, noise level and trend. Gregor McInerny and myself show you how you can deal with this by cropped and scaling the multiples to a different range to emphasize relative changes while preserving the context of the full data range to show absolute changes.
McInerny, G. & Krzywinski, M. (2015) Points of View: Unentangling complex plots. Nature Methods 12:591.