Network Systems Biology
Planned future work in this research area focuses on the problem of extending spectral graph theory to correctly model dynamics on cyclic, directed, weighted, and signed networks. Spectral graph theory is a powerful technique for quantifying how changes to a network’s structure impact its dynamics, making it useful for predicting the activity of regulatory networks. In its current form, however, these inferences are often limited to networks that are unsigned (meaning that they do not discriminate between activation and inhibition) or undirected (meaning that they cannot correctly model delays in feedback loops). Addressing these limitations is a mathematically interesting problem and will considerably advance our ability to turn High Throughput data into predictive and actionable insights.
Deducing the “Rules of Life”
Planned future work in this research area has two components: the development of rich multi-layer and multiplex network models that describe interactions at the transcriptional level and at the protein level, as well as the connections between them; and validation of these interaction models in silico using molecular simulation techniques.
Temporal Organization of Living Sytems
Our work in this area has developed into a robust research program devoted to computational modeling of circadian dynamics. As part of the recently-awarded NSF-Simons Center for Quantitative Biology (a consortium of 13 research groups on both the Evanston and Chicago Campus), we are developing mathematical models for how the circadian clock responds to perturbations such as changes in temperature and diet, and mediates the relationships between those exposures and lifespan. Through a combination of mathematical modeling and experiments in Drosophila carried out by collaborator Ravi Allada, we aim to understand how the clock achieves the seemingly contradictory properties of temperature compensation and temperature-responsive entrainment, encodes seasonality, and enables the organism to adapt to changing nutritional environments by enacting seasonal metabolic programs. In addition to this basic science work, our Lab also works with Phyllis Zee and the Center for Circadian and Sleep Medicine to study circadian interventions and examine circadian rhythms in aging.
There is considerable synergy between methodological and applied work within each of our research areas. In addition, there is also considerable synergy across the research areas. For example, the network–based metrics we develop in (Research Area 1- Network Systems Biology) have implications for the dynamics of processes involving those networks (Research Area 3 – Temporal Organization of Living Systems). Similarly, our discovery of temporal biomarkers (Research Area 3 – Temporal Organization of Living Systems) enables us to infer causality for network reconstruction (Research Area 2 – Deducing the “Rules of Life”). Together, this constitutes a coherent, well-defined independent research program in computational biology that creatively harnesses our diverse expertise to advance our understanding of complex biological processes.