Predicting gene level sensitivity to JAK-STAT signaling perturbation using a mechanistic-to-machine learning framework
Neha Cheemalavagu, Karsen E. Shoger, Yuqi Cao, Brandon Alan Michalides, Samuel A. Botta, James R. Faeder, Rachel A. Gottschalk
The paper predicts gene sensitivity to JAK-STAT perturbation by linking STAT phosphorylation dynamics to gene expression using a mechanistic-to-machine learning framework.
Cell Systems · Jan 1, 2024Peer-reviewedSystems Biology