What wasn't to like when people started talking about 'next-generation' sequencing? It sounds so cutting edge and futuristic. But now what?

'Next-next-generation' and the inevitable 'next-next-next-generation' bring back memories of MAPKK and MAPKKK except that those had intrinsic meaning to them that were obvious to the reader; thus, they worked.

Recently, people have started using the terms 'second generation' to refer to the 454, Illumina and SOLiD sequencing platforms and 'third generation' to refer to the Helicos and PacBio platforms. Nanopore-based platforms may also qualify for the 'third generation' moniker.

But while the acronym NGS was readily adopted by people to refer to next-generation sequencing, SGS and 2GS just haven't seen the same kind of uptake in the community as acronyms for second-generation sequencing. For some reason they just aren't as visually satisfying. Eventually, I think one of these will be picked up and popularized. While neither may be beautiful (if that can be said for any acronym), either of them would be infinitely better than NNGS and, heaven forbid, NNNGS.

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The idea of tracing the structure of stained neurons to obtain functional insights into in situ neural networks isn't new and dates back over 100 years to Ramón y Cajal. Just recently I discovered that copies of his books have been digitized by Google and the illustrations are incredible. See for example Studien über die Hirnrinde des Menschen.

Even though software now exists to automate this process, it seems that the performance still isn't good enough to replace manual tracing of image stacks of labeled neurons. Neuroanatomists often spend days to months manually tracing the structures rather than rely on the software that currently exists for automating the process.

Two big players in the neuroscience field have decided to do something about this. On April 9th the Allen Institute for Brain Science and the Janelia Farm Research Campus of the Howard Hughes Medical Institute announced the DIADEM Challenge. The acronym is derived from Digital Reconstruction of Axonal and Dendritic Morphology. I wonder how long it took to come up with that one.

Over the next year groups and individuals are invited to download image stacks of real data and use their algorithms to create digital reconstructions of the neurons and submit them for evaluation. Five finalists will be invited to compete in a final round at the Janelia Farm Research Campus. The organizers will award a $75,000 cash prize to the winner whose algorithm performs the best. The results will be submitted for publication in a special issue of the journal Neuroinformatics.

The hope is that the competition will encourage the advances in automated neuronal tracing that will be required for researchers to construct a functional atlas of the brain — one of the principle goals of the research at Janelia Farm.

It is encouraging to see a competition devoted to a small community like this. Nature Methods previously argued that such competitions would be valuable for improving algorithms in such specialized applications. I'm excited to see that it is happening and wish the organizers and competitors are successful.

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Every year Nikon treats people to some of the most spectacular images the microscopic world has to offer when they unveal the winners of their annual Small World Photomicrography Competition. Last year Nature Methods highlighted the winning image on the cover of our November issue.

Now is the chance for all you scientist-photographers to comb through your favorite images or take spectacular new ones because yesterday Nikon announced that they are accepting submissions for this year's contest from now until April 30th. Go to http://www.nikonsmallworld.com for more information and to see previous year's winners.

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