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- Bryan C. Daniels, Yan-Jiun Chen, James P Sethna, Ryan N. Gutenkunst, Christopher R. Myers
- Current opinion in biotechnology
- 2008

The functioning of many biochemical networks is often robust-remarkably stable under changes in external conditions and internal reaction parameters. Much recent work on robustness and evolvabilityâ€¦ (More)

- Joshua J. Waterfall, Fergal P. Casey, +5 authors James P Sethna
- Physical review letters
- 2006

In a variety of contexts, physicists study complex, nonlinear models with many unknown or tunable parameters to explain experimental data. We explain why such systems so often are sloppy: the systemâ€¦ (More)

- Ryan N. Gutenkunst, Fergal P. Casey, Joshua J. Waterfall, Christopher R. Myers, James P Sethna
- Annals of the New York Academy of Sciences
- 2007

Successful predictions are among the most compelling validations of any model. Extracting falsifiable predictions from nonlinear multiparameter models is complicated by the fact that such models areâ€¦ (More)

- Fiona Casey, Dan Baird, +6 authors James P. Sethna
- IET systems biology
- 2007

We apply the methods of optimal experimental design to a differential equation model for epidermal growth factor receptor signalling, trafficking and down-regulation. The model incorporates the roleâ€¦ (More)

- Joshua J. Waterfall, Fergal P. Casey, +5 authors James P Sethna
- 2006

Joshua J. Waterfall, Fergal P. Casey, Ryan N. Gutenkunst, Kevin S. Brown, Christopher R. Myers, Piet W. Brouwer, Veit Elser, James P. Sethna 1 Laboratory of Atomic and Solid State Physics, Cornellâ€¦ (More)

- Ryan N. Gutenkunst, Nathaniel K. Newlands, Molly Lutcavage, Leah Edelstein-Keshet
- Journal of theoretical biology
- 2007

We use observed movement tracks of Atlantic bluefin tuna in the Gulf of Maine and mathematical modeling of this movement to identify possible resource patches. We infer bounds on the overall sizesâ€¦ (More)

When modeling complex biological systems, exploring parameter space is critical, because parameter values are typically poorly known a priori. This exploration can be challenging, because parameterâ€¦ (More)

Consider an observation y of a random vector Y = (Y1, . . . , Yn), where Y has probability density f(y; âœ“), y 2 Y, parameterized by âœ“ âœ“ Rn. The log-likelihood is l(âœ“; y) = log(f(y; âœ“)). Usually, theâ€¦ (More)

Successful predictions are among the most compelling validations of any model. Extracting falsifiable predictions from nonlinear multiparameter models is complicated by the fact that such models areâ€¦ (More)

- Fergal P. Casey, Dan Baird, +6 authors James P Sethna
- 2006

Fergal P. Casey, Dan Baird, Qiyu Feng, Ryan N. Gutenkunst, Joshua J. Waterfall, Christopher R. Myers, Kevin S. Brown, Richard A. Cerione, James P. Sethna 1 Center for Applied Mathematics, Cornellâ€¦ (More)