We are thrilled to announce that D2D was recently funded to use cutting edge machine learning tools to investigate how student outcomes from engaging in research vary across the many different contexts that D2D is taught in. For example, members in our network teach D2D in first-quarter freshman classes and senior-level capstone classes; D2D is integrated into organic chemistry labs and in molecular genetics courses, and everything in between!

We are thrilled to announce that this fall we were awarded an NSF-RCN grant! We can't wait to get started and grow the D2D network team. We aim to double in size in 2022 and grow to over 40 institutions by 2030. We are actively seeking new partners and will put out a formal call for new D2D network members soon. Stay tuned and don't hesitate to reach out with questions. A huge thanks to our team for all of their help on applying for this award. We can't wait to see our network grow!

Our 2019 D2D Network team published a descriptive article on the D2D CURE and incubator Network in the Journal of Chemical Education. This was a great team effort and experience working together to summarize the course and research project, available learning resources, and salient student outcomes! Check out the full paper here (it's open access). 

Recent study uses student-generated data to examines predictive efficacy of a suite of computational tools to better model enzyme thermal stability  

Huang, P., Chu, S. K., Frizzo, H. N., Connolly, M. P., Caster, R. W., & Siegel, J. B. (2020). Evaluating Protein Engineering Thermostability Prediction Tools Using an Independently Generated Dataset. ACS omega, 5(12), 6487-6493. https://pubs.acs.org/doi/abs/10.1021/acsomega.9b04105

We are thrilled to be reporting that students have published papers in bioRxiv describing their mutant characterization results. View here in Google Scholar.

Luong, J. A., Vater, A., & Siegel, J. B. (2020). Design to Data for mutants of β− Glucosidase B from Paenibacillus polymyxa: I45K, A357S, I20A, I20V, and I20E. bioRxiv.

The CUREnet Collection serves as a repository and hub for examples of CUREs and mechanism for connecting with teams who are implementing CUREs.

Finally, after a long semester of hard work designing, building and testing your mutant, you will be able to characterize its enzymatic activity!