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Mathematical biology, computational algebra (Groebner bases), gene regulatory networks. 

Professor Stigler's research focuses on the development of a mathematical framework for the reverse engineering of gene networks, using computational algebra as a primary source of tools. The main tool is that of Groebner bases of polynomial ideals. The models used in this work are time- and state-discrete finite dynamical systems, described by polynomial functions over a finite field. She and collaborators have developed an algorithm for reverse engineering gene networks from experimental time series data, including concentrations of mRNAs, proteins, and/or metabolite. She has applied this method to an oxidative stress response network in yeast and developmental networks in C. elegans and the fruit fly.

She has been actively involved with the DREAM (Dialogue for Reverse Engineering Assessments and Methods) Initiative and SACNAS (Society for Advancement of Chicanos and Native Americans in Science). One of her main collaborations is with the Applied Discrete Mathematics Group at the Virginia Bioinformatics Institute. Her work has been listed as one of the top 25 Hottest Articles in Journal of Theoretical Biology.