Ten simple rules to increase computational skills among biologists with Code Clubs


For most biologists, the ability to generate data has outpaced the ability to analyze those data. High throughput data comes to us from DNA and RNA sequencing, flow cytometry, metabolomics, molecular screens, and more. Although some accept the approach of compartmentalizing data generation and data analysis, we have found scientists feel empowered when they can both ask and answer their own biological questions. In our experience performing microbiome research, it is more common to find exceptional bench scientists who are inexperienced at analyzing large data sets than to find the reverse. Of course, this raises a challenge: how do we train bench scientists to effectively answer biological questions with these larger data sets?

In PLOS Computational Biology
Ada K. Hagan, Ph.D.
Ada K. Hagan, Ph.D.

I am a microbiologist with a passion for making science accessible. I hope to use my background in communications and higher education to help make scientific concepts more easily understood and make the academy more inclusive to future scientists from all backgrounds.