Viral Footprints – a microscopic signature
2020 | data art | genomic data
What do viruses look like? This work, which started prior to the COVID-19 pandemic, attempts to put a face on the many microscopic organisms that cause human and animal disease. Through generative coding, I created portraits that depict peaceful but menacing signatures of 18 viruses.
code Check out and download the code on GitHub
a Generative Dance
During my time at the Broad Institute of MIT and Harvard, I had the privilege of working with many viral datasets (see related project here). The work I was doing there was scientific and serious, so I decided to repurpose the same data but apply a more creative and emotional approach.
I leveraged Processing to code a (semi) random walker, which is a kind of algorithm that allows an object to move across a two- or three-dimensional space. I programmed the walker so that it would read a genomic sequence, which is a long string of As, Cs, Ts, and Gs, and colored and moved certain basic shapes accordingly.
I took samples from most types of viruses, including single-stranded positive-sense and negative-sense RNA viruses, double-stranded RNA viruses, and double-stranded DNA viruses. The list includes Mumps, Zika, SARS Coronavirus, Polio, Hepatitis E, and Dengue, among others.
Final Result
I created 18 different footprints that depict a combination of some of the most known and some rare viruses that affect both humans and other animals. For instance, the Myxoma virus causes a deadly disease in rabbits.
You can download the code and run it using P3/Processing yourself by going to the GitHub repo
Exhibit
The project was featured in an art exhibit in Cambridge, MA as part of a collection of data visualization and data art.
Credits
Data Visualization: Antonio Solano-Román.
A previous version of this project was done under the guidance of Prof. Jose Luis Garcia del Castillo Lopez at Northeastern University.