Existence of Causation without Correlation in Transcriptional Networks
Gerald M. Pao, Ethan R. Deyle, Hao Ye, Junko Ogawa, Marisela Guaderrma, Manching Ku, Tom Lorimer, Nina U Tonnu, Erik T. Saberski, Joseph C. Park, Eugene Ke, Curt Wittenberg, Inder M. Verma, George Sugihara
The paper shows that causal relationships can exist in transcriptional networks without correlation, using nonlinear causality tests to detect uncorrelated causal links in yeast and mouse.
bioRxiv · Feb 10, 2026 · PreprintSystems Biology