Perturbation May 2026

Several recent papers and frameworks focus on predicting these responses using machine learning: Key Research Papers (2024–2026)

: A model that extends perturbation studies from static snapshots to dynamic cellular trajectories, allowing for the simulation of disease progression or development. perturbation

: A meta-learning framework that translates existing perturbation atlases to predict responses in new biological contexts using only a few "seed" perturbations. Several recent papers and frameworks focus on predicting

: A causally inspired graph neural network that identifies which combinations of perturbations are needed to reverse a disease phenotype. Software & Frameworks perturbation