Welcome to my site. My name is Gytis Dudas and I’m a scientist who works on viruses. My interests very broadly cover the evolution and ecology of viruses and inferring patterns of virus dispersal and transmission that reflect host movements and contact networks. I have worked with diverse human viruses in the past with influenza B, MERS corona-, Zika, and Ebola viruses being the more widely known, though I also thoroughly enjoy rummaging through animal metagenomic datasets for new viruses. Whenever possible I employ state-of-the-art Bayesian phylogenetic models and make liberal use of customised data visualisation techniques to present my work. Here are a couple of examples of data visualisations I’ve made:
What to expect
In case you missed them on bioRxiv my papers also live here. I have been fortunate enough to grow up in an open academic environment where I never felt like I had to obfuscate what I do to give the impression that my contributions are indispensable, or hide my research from prying eyes seeking to scoop me at every step of the way. I try my best to make all of my work freely available, from data, to code, to publication, because I stand by the results I publish. If you find bugs in my code I’d be more than happy to fix them.
Behind the scenes
Owing to my inability to say anything between the lines in papers you can find the commentary track to the studies I’ve been involved with here. The published article rarely contains indications of its historical context, the effort that went into producing the first draft, or the changes it underwent during peer review. Since contributions to projects led by other folks are faster and easier to produce than original research the commentary section is bound to outnumber my papers.
Quite possibly the worst mix of thoughts on recent papers, Orthomyxoviridae fandom, unsought thoughts on data-vis, and unsubstantiated opinions on a variety of topics on the internet. I often have strong opinions on matters with little thought going into them, but am also ready and willing to be proven wrong. Occasionally it’s something I do know, and most often it’s stuff no one cares about.
I get it. It was the first session on the third day of the meeting, you weren’t entirely over the jet-lag, slightly hungover and conference hypoxia had fully set in. With the wonders of modern technologies you can rewind time back and look through my talk again.
Outside of science
I’m a cyclist (note the lack of “avid”). Apart from cycling to work I dabble in bicycle touring, which allows me to combine the mind blowing concept of covering large distances with muscle power and exploring Lithuania. The first bike tour through Lithuania I organised was a mixed success. The backbone of my tours is manors and manor estates, many of which have been resurrected recently.
I am also a big fan of terrible films. I used to organise bad movie nights during my time in Edinburgh. You can have a look at an analysis of what films my friends and I have shown at bad movie nights here. One of my proudest achievements in Edinburgh has been the discovery of Die Hard Dracula.
As a user of matplotlib I love data visualisation. Data are easy to display, but often difficult to display in a way that is both accurate and is interpreted correctly by the reader. Aesthetics are also often overlooked when designing figures. There might be brave souls out there who can calmly look at magenta comic-sans axis labels, but I’m not one of them.