Plant Immunologist x Machine Learning, occasional biochemist | 🌱-🧫 interactions | UC Berkeley Postdoc | 2 x USDA NIFA Fellow
Dani Stevens, Ph.D.
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While there's lots of work to be done, mamp-ml is a critical advancement in plant immunology for accelerating receptor-epitope characterization and engineering resistance. Mamp-ml is on Github and we implemented a version on Google Colab for easy use. Please check it out!
github.com/DanielleMSte...
Mamp-ml was built upon two decades of foundational research. To generate the training data required, I manually pulled receptor and epitope sequences from every paper I could find, small or large. In total, we were able to capture over 1,300+ combinations across 11 receptors and 91 plant species.
#2025ISMPMI 📣 In silico screening of PRR-epitope interactions is now possible!
Here, we developed mamp-ml to predict their immunogenic outcomes without structural context. Let's accelerate engineering plant receptors for robust resistance! 🚀🌱 Small 🧵
www.biorxiv.org/content/10.1...
An artificial intelligence tool developed by @microsoft.com researchers can predict the multiple conformational states of proteins in minutes with a fraction of the resources required by other techniques. cen.acs.org/biological-c... #chemsky 🧪
While I'm not going to be at #2025ISMPMI this year (🥲),
@kseniakrasileva.bsky.social will be there presenting on some of our latest work that was submitted to BioRxiv today. Teaser: Plant immunity + large language models will transform receptor discovery and engineering for disease resistance. 🌱🚀
