Ben Noordijk

This study investigates when combining mechanistic and machine learning models improves predictions of gene regulatory network dynamics using synthetic data.

BADDADAN models gene module dynamics under stress using machine learning and ODEs, demonstrating its application on A. thaliana datasets to recover known insights and propose new hypotheses.

This study uses a nanopore assay with a CNN to detect and determine the stoichiometry of single cOAs produced by type III CRISPR-Cas systems.

baseLess detects target sequences in raw MinION data using small neural networks, achieving accurate classification on low-cost hardware.