Ben Noordijk
@bnoordijk.bsky.social
PhD Student @ Wageningen University | Bioinformatics | Merging machine learning with mechanistic models to understand plant resilience
Reposted by Ben Noordijk
Interested in Python programming and good software engineering practices? Check out my newest blog post where I introduce a "modern Python" GitHub repository template and talk about my motivation for its creation! mmzdouc.github.io/posts/2025/1...
Modern Python Project GitHub Template
TL;DR: I created a freely available template to facilitate setting up “modern” Python projects.
mmzdouc.github.io
October 22, 2025 at 2:06 PM
Interested in Python programming and good software engineering practices? Check out my newest blog post where I introduce a "modern Python" GitHub repository template and talk about my motivation for its creation! mmzdouc.github.io/posts/2025/1...
Reposted by Ben Noordijk
PhD Position in Modelling Regulation of Plant Stress Responses across Species!! 🌱🌽🌾🥬🌡️🌡️
Apply before June 16 to join this exciting project with Kirsten ten Tusscher in the context of CropXR!! www.uu.nl/en/organisat...
Apply before June 16 to join this exciting project with Kirsten ten Tusscher in the context of CropXR!! www.uu.nl/en/organisat...
PhD Position in Modelling Regulation of Plant Stress Responses across Species
Join us to model plant stress responses and help breed climate-resilient crops in a collaborative, interdisciplinary research environment!
www.uu.nl
May 12, 2025 at 6:42 PM
PhD Position in Modelling Regulation of Plant Stress Responses across Species!! 🌱🌽🌾🥬🌡️🌡️
Apply before June 16 to join this exciting project with Kirsten ten Tusscher in the context of CropXR!! www.uu.nl/en/organisat...
Apply before June 16 to join this exciting project with Kirsten ten Tusscher in the context of CropXR!! www.uu.nl/en/organisat...
Reposted by Ben Noordijk
OK, this is wild.
In September 2023, geophysicists across the world started monitoring a very odd signal coming from the ground under them.
It was picked up in the Arctic. And Antarctica. It was detected everywhere, every 90 seconds, as regular as a metronome, for *nine days*.
What the HELL?
1/
In September 2023, geophysicists across the world started monitoring a very odd signal coming from the ground under them.
It was picked up in the Arctic. And Antarctica. It was detected everywhere, every 90 seconds, as regular as a metronome, for *nine days*.
What the HELL?
1/
May 12, 2025 at 3:20 PM
OK, this is wild.
In September 2023, geophysicists across the world started monitoring a very odd signal coming from the ground under them.
It was picked up in the Arctic. And Antarctica. It was detected everywhere, every 90 seconds, as regular as a metronome, for *nine days*.
What the HELL?
1/
In September 2023, geophysicists across the world started monitoring a very odd signal coming from the ground under them.
It was picked up in the Arctic. And Antarctica. It was detected everywhere, every 90 seconds, as regular as a metronome, for *nine days*.
What the HELL?
1/
Reposted by Ben Noordijk
New preprint!
BADDADAN mechanistically models time-series response of >1000 genes to stress by clustering first, then fitting an ODE model.
Demonstrated on real Arabidopsis data: interpretable, coherent modules, plus new and existing biological insights.
doi.org/10.1101/2025.02.18.638670
BADDADAN mechanistically models time-series response of >1000 genes to stress by clustering first, then fitting an ODE model.
Demonstrated on real Arabidopsis data: interpretable, coherent modules, plus new and existing biological insights.
doi.org/10.1101/2025.02.18.638670
February 24, 2025 at 12:47 PM
New preprint!
BADDADAN mechanistically models time-series response of >1000 genes to stress by clustering first, then fitting an ODE model.
Demonstrated on real Arabidopsis data: interpretable, coherent modules, plus new and existing biological insights.
doi.org/10.1101/2025.02.18.638670
BADDADAN mechanistically models time-series response of >1000 genes to stress by clustering first, then fitting an ODE model.
Demonstrated on real Arabidopsis data: interpretable, coherent modules, plus new and existing biological insights.
doi.org/10.1101/2025.02.18.638670