A mathematical framework for agent based models of complex biological networks F Hinkelmann, D Murrugarra, AS Jarrah, R Laubenbacher Bulletin of mathematical biology 73 (7), 1583-1602, 2011 | 114 | 2011 |
Modeling stochasticity and variability in gene regulatory networks D Murrugarra, A Veliz-Cuba, B Aguilar, S Arat, R Laubenbacher EURASIP Journal on Bioinformatics and Systems Biology 2012, 1-11, 2012 | 85 | 2012 |
Identification of control targets in Boolean molecular network models via computational algebra D Murrugarra, A Veliz-Cuba, B Aguilar, R Laubenbacher BMC systems biology 10, 1-11, 2016 | 77 | 2016 |
Boolean nested canalizing functions: A comprehensive analysis Y Li, JO Adeyeye, D Murrugarra, B Aguilar, R Laubenbacher Theoretical Computer Science 481, 24-36, 2013 | 69 | 2013 |
Regulatory patterns in molecular interaction networks D Murrugarra, R Laubenbacher Journal of theoretical biology 288, 66-72, 2011 | 41 | 2011 |
Evolution of cellular differentiation: from hypotheses to models P Márquez-Zacarías, RM Pineau, M Gomez, A Veliz-Cuba, D Murrugarra, ... Trends in Ecology & Evolution 36 (1), 49-60, 2021 | 35 | 2021 |
The number of multistate nested canalyzing functions D Murrugarra, R Laubenbacher Physica D: Nonlinear Phenomena 241 (10), 929-938, 2012 | 33 | 2012 |
Molecular network control through boolean canalization D Murrugarra, ES Dimitrova EURASIP Journal on Bioinformatics and Systems Biology 2015, 1-8, 2015 | 28 | 2015 |
The spruce budworm and forest: a qualitative comparison of ODE and Boolean models R Robeva, D Murrugarra Letters in Biomathematics 3 (1), 75-92, 2016 | 24 | 2016 |
Mathematical modeling of the Candida albicans yeast to hyphal transition reveals novel control strategies DJ Wooten, JGT Zañudo, D Murrugarra, AM Perry, A Dongari-Bagtzoglou, ... PLoS computational biology 17 (3), e1008690, 2021 | 20 | 2021 |
Bifurcations in Boolean networks C Kuhlman, H Mortveit, D Murrugarra, A Kumar Discrete Mathematics & Theoretical Computer Science, 2011 | 20 | 2011 |
Improving RNA secondary structure prediction via state inference with deep recurrent neural networks D Willmott, D Murrugarra, Q Ye Computational and Mathematical Biophysics 8 (1), 36-50, 2020 | 16 | 2020 |
A near-optimal control method for stochastic boolean networks B Aguilar, P Fang, R Laubenbacher, D Murrugarra Letters in biomathematics 7 (1), 67, 2020 | 15 | 2020 |
Modeling the pancreatic cancer microenvironment in search of control targets D Plaugher, D Murrugarra Bulletin of Mathematical Biology 83 (11), 115, 2021 | 14 | 2021 |
Control of intracellular molecular networks using algebraic methods L Sordo Vieira, RC Laubenbacher, D Murrugarra Bulletin of mathematical biology 82 (1), 2, 2020 | 14 | 2020 |
The nonlinearity of regulation in biological networks S Manicka, K Johnson, M Levin, D Murrugarra NPJ Systems Biology and Applications 9 (1), 10, 2023 | 13 | 2023 |
Transcriptional correlates of proximal-distal identify and regeneration timing in axolotl limbs SR Voss, D Murrugarra, TB Jensen, JR Monaghan Comparative Biochemistry and Physiology Part C: Toxicology & Pharmacology …, 2018 | 13 | 2018 |
Algebraic models and their use in systems biology R Laubenbacher, F Hinkelmann, D Murrugarra, A Veliz-Cuba Discrete and Topological Models in Molecular Biology, 443-474, 2013 | 11 | 2013 |
Stabilizing gene regulatory networks through feedforward loops C Kadelka, D Murrugarra, R Laubenbacher Chaos: An Interdisciplinary Journal of Nonlinear Science 23 (2), 2013 | 11 | 2013 |
Revealing the canalizing structure of Boolean functions: Algorithms and applications E Dimitrova, B Stigler, C Kadelka, D Murrugarra Automatica 146, 110630, 2022 | 10 | 2022 |