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Elucidating Biological Complexity

Elucidating Biological Complexity

Our central goal is to elucidate, predict, and modulate the behavior of the complex molecular networks that underly all living processes.   

Computational Biology at Multiple Scales

We develop and apply powerful mathematical and computational methods to investigate living systems at multiple scales — from the atomic level, to the gene level, to the systems level, to the tissue/organismal level, and finally to the population level — and apply these methods in close collaboration with experimentalists and clinicians to address pressing biomedical questions, from circadian disruption to cancer. Working at the interface between mathematics, computation, and biology, we advance our understanding of how macroscopic phenotypes emerge from the complex interplay of microscopic interactions.

Overview

Why Biocomplexity?

Why Biocomplexity?

Emergence. Adaptation. A wealth of data.

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Join Us

Join Us

Learn about positions for undergrads, graduate students, and post-docs!

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Research Areas

Network Analysis

Network systems biology

Analyzing omics data in the context of regulatory networks

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Integrative Omics Analysis

Deducing the “Rules of Life”

Combining multi-omic data to identify novel regulators and understand disease mechanisms

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Circadian Biology and Dynamical Systems

Temporal organization of living systems

Modeling biological dynamics and predicting the responses to environmental perturbations

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