There are plenty of user interface elements for bioinformatics available on the web, but most of them are dispersed and written in JavaScript. With Julia, we can adapt and augment these elements to make interfaces that are more relevant to user projects, have denser information, can be run/tweaked locally, and create new connections between data.
There are so many great websites and databases with nice interactive figures and tons of information presented on the screen out there. However, it can be inconvenient to reach the data or interface one is looking for on some of these sites, and there might be a lot of clutter. One aim here is to enable users to basically collect the most relevant elements together. Another aim is to connect data and events together for these elements, and to ultimately control it all with Julia. Plotting and interface packages in Julia can be used to construct new elements that provide whatever functionality or representation is missing. The result is an interface that can be optimized for a particular project, person, or purpose. The scientific machine learning and computational ecosystems in Julia can be used as a natural backend to enable powerful new data science controls and techniques.
I grew up in Grand Rapids, Michigan, but now I live in Ames, Iowa. Both are great places to live, but I hope to move closer to GR eventually. I first became truly interested in science in high school chemistry class. Later, I found organic chemistry to be the most fun, and this interest spread to biochemistry and math (BS double major). I decided to continue my exploration and get an MS in chemistry, during which I studied a family of DNA polymerases that are recruited to replicate past lesions in the DNA. After that, I still wanted more time to study, so here I am at Iowa State in a great bioinformatics and computational biology PhD program. I want my life to be about exploration of STEM, and my favorite set of tools is Julia.