Here’s a little quick round-up of some of the tools/algorithms that I’ve seen in VIZBI, which I believe can be useful for many. For more details, I strongly advise you check out the posters page (vizbi.org/Posters/2016). There were a few that I would’ve liked to re-visit, but the webapps weren’t available (e.g. MeshCloud from the Human Genome Center, Tokyo), so maybe I’ll come back with a part 3. Here are my top five:
1. Autodesk’s Protein Viewer* (shout-outs to @_merrywang on Twitter)
As a structural bioinformatician, I’m going to be really biased here, and say that Autodesk’s Molecule viewer was the best tool that was showcased in the conference. It combines not only the capacity to visualise millions of molecules from the PDB (or your own PDB files), it also allows annotation and sharing, effectively, “snapshots” of your workspace for collaboration (see this if you want to know what I mean). AND it’s free! It’s not the fastest viewer on the planet, nor the easiest thing to use, but it is effective.
Not related to protein structures, but a really interesting visualisation that shows information on, for example, insecticide resistance. With mosquitoes being such a huge part of today’s news, this kind of information is vital for fighting and understanding the distribution of insects across the globe.
This is a genome browser which, from a one-man effort, could be a game-changer. The UI needs a little bit of work I think, but otherwise, a really valuable tool for crunching lots of genomic data in a quick fashion.
4. i-PV Circos
This is a neat circular browser that helps users view protein sequences in a circularised format. With this visualisation format becoming more popular as the days go by, I think this has the potential to be a leader in the field. At the moment the website’s a bit dark and not the most user-friendly, but some of the core functionality (e.g. highlighting residues and association of domains) is a real plus!
5. Storyline visualisation
Possibly my favourite/eye-opener tool from the entire conference. Storyline visualisation helps users understand how things progress in realtime — this has been used for movie plot data (e.g. Star Wars character and plot progression) but the general concept can be useful for biological phenomena – for example, how do cells in diseased states progress over time? How does it compare to healthy states? Can we also monitor protein dynamics using a similar concept? I think the fact that it gives a very intuitive, big-picture overview of the micro-scale dynamics was the reason why I’ve been incredibly interested in Kwan-Liu Ma’s work, and I recommend checking out his website/publications list to grab insight on improving data visualisation (in particular, network visualisation when you want to avoid hairballs!)
The list isn’t ranked in any way, and do check these out! There were other tools I would’ve really liked to review (e.g. Minardo, made by David Ma @frostickle on Twitter), but I suppose I can go on and on. At the end of the day, visualisation tools like these are meant to be quick, and help us to not only EXPLORE our data, but to EXPLAIN it too. I think we’re incredibly fortunate to have some amazing minds out there who are willing to not only create these tools, but also make them available for all.