Claire J. Tomlin

This paper reviews the use of ordinary differential equations to model cancer biology dynamics and generate hypotheses through simulation.

This paper introduces an algorithm to estimate bias in gene regulatory network inference under perturbations and repair common graph structures across perturbed networks.

This paper introduces hybrid systems modeling to address limitations of continuous dynamics in biological systems by incorporating discrete events like gene switching and mutations.

The paper introduces an RPCA-based method to decompose multidimensional spatio-temporal data into common and aberrant responses, enabling robust analysis of biological datasets.

This paper develops a compressive sensing method to reconstruct gene regulatory networks from limited time series data, showing exact reconstruction in ideal conditions and reliable results in noisy scenarios.