How do living systems self-organize?
Life exhibits spontaneous self-organization at every scale. Small molecules self-organize into functional macromolecular structures, which interact in complex regulatory networks to carry out specific cellular functions. In multicellular organisms those functions are coordinated across tissues and precisely orchestrated across the body; individual organisms collectively form populations with complex genetic and social dynamics. How do these occur, and how do the dynamics at the smallest scale impact outcomes at the largest? Our central goal is to understand how the macroscopic properties observed in living systems emerge from the complex interplay of microscopic interactions.
Working at the interface between mathematics, statistics, physics, and biology, we develop and apply computational methods to investigate living systems at multiple scales — from the atomic level, to the gene level, to the systems level, to the tissue and organismal level, and finally to the population level. We apply these methods in close collaboration with experimentalists to investigate circadian regulation, cancer, and development. Read more about our research, the methods we have grown here, or our publications.
Interested in joining the lab? Open positions and student projects.
News
Congratulations Dr Ziyu Zhao! Congratulations to Ziyu Zhao on successfully defending his PhD.
15 February 2024
Our research in the news. Pepper Huang's recent Chaos paper — a minimal model of peripheral clocks — was highlighted in the Washington Post and other venues.
7 September 2023
Welcome Dr Sneha Kachhara! Dr Sneha Kachhara is joining the group as a postdoctoral fellow. She is interested in complex systems, nonlinear dynamics, networks, and time-series analysis, with applications ranging from cardiac dynamics to variable stars. We are terrifically excited to have her on the team.
31 July 2022
Patent awarded. The group celebrates the award of its first patent. Biomarkers of endogenous biological time (US 11,328,790) provides a method for inferring human circadian phase from blood gene expression profiles.
18 May 2022
Congratulations Dr Ness-Cohn! Congratulations to Elan Ness-Cohn on successfully defending his PhD and starting a new chapter as an Entrepreneurial Fellow of the Chicago Biomedical Consortium.
1 February 2022
Two new circadian biology papers by Elan Ness-Cohn. Elan's TimeCycle method was accepted for publication in Bioinformatics. It is a novel technique for the detection of cycling genes, combining time-delay embedding, nonlinear dimension reduction, persistence homology, and a biologically informed null model. In a separate paper in Science, Elan describes a secondary analysis of circadian transcriptomic data from skin fibroblasts of mice lacking the core clock gene Bmal1.
15 July 2021
We're hiring. We are searching for a data scientist and one to two postdocs to join the team. See join us for details.
4 January 2021
The lab joins the Department of Molecular Biosciences. Effective 1 January 2021, Rosemary is tenured faculty in the Department of Molecular Biosciences in the Weinberg College of Arts and Sciences. The lab is moving to Pancoe, closer to our colleagues and collaborators on the Evanston campus.
1 January 2021
NIH R01 grant awarded. It is well known that with age come changes to one's sleep and circadian rhythms, and evidence suggests that these changes are related to neurodegeneration. The lab has received an NIH R01 grant, "Reconstructing the temporal landscape of gene regulation in aging", to investigate the role of circadian gene regulation in these processes and to develop new mathematical models that can be used to predict Alzheimer's disease risk.
1 October 2020
TimeTrial published in the Journal of Biological Rhythms. While algorithms for detecting cycling transcripts have advanced, there has remained little guidance quantifying the effect of experimental design and analysis choices on cycling detection accuracy. TimeTrial is a user-friendly benchmarking framework for exactly that.
10 July 2020