My citizen science project, BashTheBug, is launched today. Head over to the website or go straight to the Zooniverse project page and help us start classifying bacterial growth and fighting antibiotic resistance! Alternatively, read the news article on the University of Oxford website or see how the project is doing via its Twitter feed.
Zooniverse have finished beta-testing my BashTheBug citizen science project. To verify that the task is easy to do and the tutorial and help text understandable, the first version of the project was sent to a number of experienced Zooniverse beta-testers.
Over a period of two weeks, 672 volunteers made 34,791 classifications which is, on average, an astonishing 51 classifications each. The volunteers were emailed at 5pm on Wednesday 22 March and 40% of those classifications (14,157) were made by midnight! In addition around a quarter (176) of volunteers left detailed feedback on how easy the task was to do and how it could be improved. I’m currently making the changes they recommended and plan to launch in the first week of April 2017. Watch this space.
I’m planning to launch a citizen science project, bashthebug.net, in 2017 which has two distinct ways anyone can help combat antibiotic resistance. I’ve revamped and relaunched what will ultimately become the public-facing project website – please have a look.
The first strand is closer to the light of day and will help the international Tuberculosis consortium, CRyPTIC. This global group of researchers, of which I am a part, will be collecting over 100,000 samples from patients with TB. Each sample will be tested to see which antibiotics are effective as well as having the genome of its M.tuberculosis bacterium sequenced. In practice, because each sample is measured at least three different times, that means looking at 300,000 96-well plates. Step forward Zooniverse! This type of large-scale image classification is exactly the sort of thing Zooniverse Citizen Science projects excel at. I hope to launch this project in early 2017.
The second citizen science project is more complex and I have recently applied for funding. As described in my Research, I am developing methods that can predict whether novel or rarely-observed mutations cause resistance to an antibiotic (or not). These require a lot of computer resource and the idea is to build a volunteer computing project, like [climate prediction.net](http://climate prediction.net), using the BOINC framework, so that volunteers can download a program onto their laptop or desktop. When they’re not using their computer, the program will retrieve part of a problem and run the simulations on their machine before returning the results over the internet. These type of project is more complicated and requires more infrastructure to be setup, but with some luck, I’d hope to have a soft launch late in 2017.