Fergal P. Casey

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Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields(More)
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 system behavior depends only on a few "stiff" combinations of the parameters and is unchanged as other "sloppy" parameter combinations vary by orders of magnitude. We(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 are commonly sloppy, possessing sensitivities to different parameter combinations that range over many decades. Here we discuss how sloppiness affects the sorts of(More)
MOTIVATION Pairwise experimental perturbation is increasingly used to probe gene and protein function because these studies offer powerful insight into the activity and regulation of biological systems. Symmetric two-dimensional datasets, such as pairwise genetic interactions are amenable to an optimally designed measurement procedure because of the(More)
Most biological functions are regulated through complex networks of transient protein interactions, and, thus, finding effective ways to modulate them would represent an important step towards defining the next generation of drugs. In this study, we set out to determine if existing approved drugs may represent a good source of compounds from which initial(More)
Docking experiments of multiple compounds typically focus on a single protein. However, other targets provide information about relative binding efficiencies that is otherwise lacking. We developed a docking strategy that normalized results in both the ligand and target dimensions. This was applied to dock 287 approved small drugs with 35 peptide-binding(More)
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, Cornell University, Ithaca, NY 14853, USA 2 Center for Applied Mathematics, Cornell University, Ithaca, NY 14853, USA 3 Department of Molecular and Cellular Biology,(More)
Protein-protein interactions are central to most biological processes and represent a large and important class of targets for human therapeutics. Small molecules containing peptide substituents may mimic regions of interacting proteins and inhibit their interactions. We set out to develop efficient methods to screen for similarities between known peptide(More)
Mechanistic biosimulation can be used in drug development to form testable hypotheses, develop predictions of efficacy before clinical trial results are available, and elucidate clinical response to therapy. However, there is a lack of tools to simultaneously (1) calibrate the prevalence of mechanistically distinct, large sets of virtual patients so their(More)
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, Cornell University, Ithaca, NY 14853, USA Department of Cellular and Molecular Medicine and the Howard Hughes Medical Institute, University of California at San Diego, La(More)