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Time is important to multiple biological processes, including circadian-regulated gene expression related to metabolic, cell cycle, and immune system functions. The overarching goals of BioChronicity are the integration of math, physics, and biology to: (1) understand time-dependent gene expression, (2) generate predictive models of complex biological systems, and (3) regulate molecular clocks to modulate clinical outcomes.
Program Manager: Dr. Jim Gimlett
The content below has been generated by organizations that are partially funded by DARPA; the views and conclusions contained therein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of DARPA or the U.S. Government.
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Last updated: November 13, 2015
|University of Chicago, Northwestern University||Improved Statistical Methods Enable Greater Sensitivity in Rhythm Detection for Genome-Wide Data||http://www.ploscompbiol.org/article/fetchObject.action?uri=info:doi/10.1371/journal.pcbi.1004094&representation=PDF|
|NorthWestern subcontractor from University of Michigan||Functional Organization of the Human 4D Nucleome||http://www.pnas.org/content/112/26/8002.full|
|Duke University||On the Efficacy of State Space Reconstruction Methods in Determining Causality||http://epubs.siam.org/doi/abs/10.1137/130946344|
|Duke University||Predicting High-Codimension Critical Transitions in Dynamical Systems Using Active Learning||http://www.math.montana.edu/~gedeon/clanky/ativelearningCriticalTran.pdf|