Kadelka, C. ., Murrugarra, D. ., & Laubenbacher, R. . (2013). Stabilizing gene regulatory networks through feedforward loops. Chaos (Woodbury, N.Y.), 23(2), 025107. https://doi.org/10.1063/1.4808248

Murrugarra, D. ., Veliz-Cuba, A. ., Aguilar, B. ., Arat, S. ., & Laubenbacher, R. . (2012). Modeling stochasticity and variability in gene regulatory networks. EURASIP Journal on Bioinformatics & Systems Biology, 2012(1), 5. https://doi.org/10.1186/1687-4153-2012-5 (Original work published 2012)

Murrugarra, D. ., & Laubenbacher, R. . (2011). Regulatory patterns in molecular interaction networks. Journal of Theoretical Biology, 288, 66-72. https://doi.org/10.1016/j.jtbi.2011.08.015 (Original work published 2011)

Hinkelmann, F. ., Murrugarra, D. ., Jarrah, A. ., & Laubenbacher, R. . (2011). A mathematical framework for agent based models of complex biological networks. Bulletin of Mathematical Biology, 73(7), 1583-602. https://doi.org/10.1007/s11538-010-9582-8

Murrugarra, D. ., Veliz-Cuba, A. ., Aguilar, B. ., & Laubenbacher, R. . (2016). Identification of control targets in Boolean molecular network models via computational algebra. BMC Systems Biology, 10(1), 94. https://doi.org/10.1186/s12918-016-0332-x (Original work published 2016)

Wooten, D. ., Zañudo, J. ., Murrugarra, D. ., Perry, A. ., Dongari-Bagtzoglou, A. ., Laubenbacher, R. ., … Albert, R. . (2021). Mathematical modeling of the Candida albicans yeast to hyphal transition reveals novel control strategies. PLoS Computational Biology, 17(3), e1008690. https://doi.org/10.1371/journal.pcbi.1008690

Aguilar, B. ., Fang, P. ., Laubenbacher, R. ., & Murrugarra, D. . (2020). A Near-Optimal Control Method for Stochastic Boolean Networks. Letters in Biomathematics, 7(1), 67-80. (Original work published 2020)