Our overall goal is to develop computational approaches to elucidate the design principles underlying biological control circuits. Rather than taking a traditional approach of asking how any one circuit works, however, we will take the inverse approach of asking what are all circuit architectures that could perform a particular target function.
Our aims are to: 1) Develop algorithms to computationally enumerate and classify core circuit architectures that can robustly achieve a given target function. These methods will involve coarse-grained representations of circuits, which can be efficiently searched and evaluated. 2) Use high resolution circuit analysis methods to identify compatible parameter sets and functional tradeoffs associated with specific architectures. 3) Test the validity the above analysis by using the results as a guide for both design of synthetic circuits (AIM 2) and the identification and classification of natural circuits (AIM 3) that can perform the target function. Our efforts will initially focus on analyzing one testbed target behavior ? Perfect Adaptation. Perfect Adaptation is a biologically important sensory function in which a sensing system produces an output spike in response to an input, but restores itself to the initial basal output level if the input is sustained. This adaptation behavior allows responses to small input changes over a wide dynamic range. Subsequently we will apply these approaches to understand and design circuit architectures compatible with other target functions.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Specialized Center (P50)
Project #
Application #
Study Section
Special Emphasis Panel (ZGM1-CBCB-2)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of California San Francisco
San Francisco
United States
Zip Code
Davis, Zoe H; Verschueren, Erik; Jang, Gwendolyn M et al. (2015) Global mapping of herpesvirus-host protein complexes reveals a transcription strategy for late genes. Mol Cell 57:349-60
Zalatan, Jesse G; Lee, Michael E; Almeida, Ricardo et al. (2015) Engineering complex synthetic transcriptional programs with CRISPR RNA scaffolds. Cell 160:339-50
Liang, Samantha I; McFarland, Jesse M; Rabuka, David et al. (2014) A modular approach for assembling aldehyde-tagged proteins on DNA scaffolds. J Am Chem Soc 136:10850-3
Park, Jason S; Rhau, Benjamin; Hermann, Aynur et al. (2014) Synthetic control of mammalian-cell motility by engineering chemotaxis to an orthogonal bioinert chemical signal. Proc Natl Acad Sci U S A 111:5896-901
Braberg, Hannes; Alexander, Richard; Shales, Michael et al. (2014) Quantitative analysis of triple-mutant genetic interactions. Nat Protoc 9:1867-81
Martín, Glòria Mas; King, Devin A; Green, Erin M et al. (2014) Set5 and Set1 cooperate to repress gene expression at telomeres and retrotransposons. Epigenetics 9:513-22
Sivak, David A; Thomson, Matt (2014) Environmental statistics and optimal regulation. PLoS Comput Biol 10:e1003826
Braberg, Hannes; Moehle, Erica A; Shales, Michael et al. (2014) Genetic interaction analysis of point mutations enables interrogation of gene function at a residue-level resolution: exploring the applications of high-resolution genetic interaction mapping of point mutations. Bioessays 36:706-13
Youk, Hyun; Lim, Wendell A (2014) Secreting and sensing the same molecule allows cells to achieve versatile social behaviors. Science 343:1242782
Keedy, Daniel A; van den Bedem, Henry; Sivak, David A et al. (2014) Crystal cryocooling distorts conformational heterogeneity in a model Michaelis complex of DHFR. Structure 22:899-910

Showing the most recent 10 out of 71 publications