Research articles

Publications:

1. When does additional information improve accuracy of RNA secondary structure prediction? Logan Rose, Luis Sanchez Giraldo, Duc Nguyen, Matthew Wheeler, David Murrugarra. Journal of Chemical Information and Modeling, 2025. DOI: 10.1021/acs.jcim.5c01231. https://doi.org/10.1021/acs.jcim.5c01231

2. Modular Control of Boolean Network Models. David Murrugarra, Alan Veliz-Cuba, Elena Dimitrova, Claus Kadelka, Matthew Wheeler, and Reinhard Laubenbacher. Bulletin of Mathematical Biology, 87, 91, 2025. https://doi.org/10.1007/s11538-025-01471-9 

3. Observability of complex systems via conserved quantities. Bhargav Karamched, Jack Schmidt, David Murrugarra. Physica D: Nonlinear Phenomena, 477, 134714, 2025. https://www.sciencedirect.com/science/article/pii/S0167278925001915 

4. Modular Construction of Boolean Networks. Matthew Wheeler, Claus Kadelka,  Alan Veliz-Cuba, David Murrugarra,  and Reinhard Laubenbacher. Physica D: Nonlinear Phenomena, 468, 134278, 2024. https://doi.org/10.1016/j.physd.2024.134278 

5. Cancer mutationscape: revealing the link between modular restructuring and intervention efficacy among mutations. Daniel Plaugher, and David Murrugarra. npj Systems Biology and Applications, 10, 74, 2024. https://rdcu.be/dNHqg 

6. Canalization reduces the nonlinearity of regulation in biological networks. Claus Kadelka and David Murrugarra. npj Systems Biology and Applications, 10, 67, 2024. https://doi.org/10.1038/s41540-024-00392-y 

7. Investigating the effect of changes in model parameters on optimal control policies, time to absorption, and mixing times. Kathleen Johnson, Daniel Plaugher, and David Murrugarra. Letters in Biomathematics, 10(1), 193-206, 2023. https://lettersinbiomath.org/manuscript/index.php/lib/article/view/178/158 

8. Modularity of biological systems: a link between structure and function. Claus Kadelka, Matthew Wheeler, Alan Veliz-Cuba, David Murrugarra, Reinhard Laubenbacher. Journal of the Royal Society Interface, 20: 20230505, 2023. https://royalsocietypublishing.org/doi/10.1098/rsif.2023.0505

9. Phenotype control techniques for Boolean gene regulatory networks. Daniel Plaugher and David Murrugarra. Bulletin of Mathematical Biology, 85(10):89, 2023. https://rdcu.be/dkN6A

10. Stability of Linear Boolean Networks. Karthik Chandrasekhar, Claus Kadelka, Reinhard Laubenbacher, David Murrugarra. Physica D: Nonlinear Phenomena, 451, 133775, 2023. https://doi.org/10.1016/j.physd.2023.133775 

11. The nonlinearity of regulation in biological networks. Santosh Manicka, Kathleen Johnson, Michael Levin, David Murrugarra. npj Systems Biology and Applications, 9:10, 2023. https://doi.org/10.1038/s41540-023-00273-w

12. Building model prototypes from time-course data. Alan Veliz-Cuba, Stephen Randal Voss, David Murrugarra. Letters in Biomathematics, 9(1), 107-120, 2022. https://doi.org/10.1101/2022.01.27.478080 

13. Uncovering potential interventions for pancreatic cancer patients via mathematical modeling. Daniel Plaugher, Boris Aguilar, David Murrugarra. Journal of Theoretical Biology, 548, 111197, 2022. https://www.sciencedirect.com/science/article/abs/pii/S0022519322001953

14. Revealing the canalizing structure of Boolean functions: Algorithms and applications. Elena Dimitrova, Brandilyn Stigler, Claus Kadelka, David Murrugarra. Automatica, 146, 110630, 2022. https://www.sciencedirect.com/science/article/abs/pii/S0005109822004940

15. HDAC Inhibitor Titration of Transcription and Axolotl Tail Regeneration. Stephen Randal Voss, Jeramiah James Smith, Nataliya Timoshevskaya, Larissa V Ponomareva, Jon S Thorson, Alan Veliz-Cuba, David Murrugarra. Front Cell Dev Biol, 2021, Dec 31;9:767377. https://pubmed.ncbi.nlm.nih.gov/35036404/

16. Modeling the Pancreatic Cancer Microenvironment in Search of Control Targets. Daniel Plaugher and David Murrugarra. Bulletin of Mathematical Biology, 83, (11):115, 2021. https://www.biorxiv.org/content/10.1101/2021.05.04.442611v2

17. Mathematical modeling of the Candida albicans yeast to hyphal transition reveals novel control strategies. David J. Wooten, Jorge G. T. Zañudo, David Murrugarra, Austin Perry, Anna Dongari-Bagtzoglou, Reinhard Laubenbacher, Clarissa Nobile, Reka Albert. PLOS Computational Biology, 17(3):e1008690, 2021. https://doi.org/10.1371/journal.pcbi.1008690.

18. Quantifying the Total Effect of Edge Interventions in Multistate Discrete Networks. David Murrugarra and Elena Dimitrova. Automatica, 125, 109453, 2021. https://doi.org/10.1016/j.automatica.2020.109453.

19. Evolution of Cellular Differentiation: From Hypotheses to Models. Pedro Márquez-Zacarías, Rozenn M. Pineau, Marcella Gomez, Alan Veliz-Cuba, David Murrugarra, William C. Ratcliff, Karl J. Niklas. Trends in Ecology & Evolution, 36(1):49-60, 2020. https://doi.org/10.1016/j.tree.2020.07.013.

20. A Near-Optimal Control Method for Stochastic Boolean Networks. Boris Aguilar, Pan Fang, Reinhard Laubenbacher, and David Murrugarra. Letters in Biomathematics, 7(1), 67-80, 2020. Full text.

21. Improving RNA secondary structure prediction via state inference with deep recurrent neural networks. Devin Wilmott, David Murrugarra, and Qiang Ye. Computational and Mathematical Biophysics, 8(1), 36-50, 2020. https://doi.org/10.1515/cmb-2020-0002.

22. Control of Intracellular Molecular Networks Using Algebraic Methods. Luis Sordo Vieira, Reinhard Laubenbacher, and David Murrugarra. Bulletin of Mathematical Biology. 2019 Dec 23; 82(1):2. https://pubmed.ncbi.nlm.nih.gov/31919596/.

23. Transcriptional Correlates of Proximal Distal Identify and Regeneration Timing in Axolotl Limbs. S. Randal Voss, David Murrugarra, Tyler Jensen, and James R. Monaghan. Comparative Biochemistry and Physiology, Part C, 208:53-63, 2018. Full text.

24. Conditioning and robustness of Boltzmann sampling of RNA secondary structures under thermodynamic parameter perturbations. Emily Rogers, David Murrugarra, and Christine Heitsch. Biophysical Journal, 113, 2, 321-329, 2017. Full text.

25. Estimating Propensity Parameters using Google PageRank and Genetic Algorithms. David Murrugarra, Jacob Miller, and Alex Mueller. Frontiers in Neuroscience, 10:513, 2016. Full text.

26. Identification of control targets in Boolean molecular network models via computational algebra. D. Murrugarra, A. Veliz-Cuba, B. Aguilar, and R. Laubenbacher. BMC Systems Biology, 10:94, 2016. Full text.

27. The Spruce Budworm and Forest: A Qualitative comparison of ODE and Boolean Models. Raina Robeva and David Murrugarra. Letters in Biomathematics, 3:1, 75:92, 2016. http://www.tandfonline.com/doi/full/10.1080/23737867.2016.1197804.

28. Molecular Network Control Through Boolean Canalization. David Murrugarra and Elena Dimitrova. EURASIP Journal on Bioinformatics and Systems Biology, 2015:9, 2015. http://link.springer.com/article/10.1186%2Fs13637-015-0029-2.

29. Structure and Dynamics of Acyclic Networks. Alan Veliz-Cuba, David Murrugarra, Reinhard Laubenbacher. Discrete Event Dynamic Systems. 24(4), 647-658, 2014. http://link.springer.com/article/10.1007/s10626-013-0174-2.

30. Stabilizing Gene Regulatory Networks Through Feedforward Loops. Claus Kadelka, David Murrugarra, Reinhard Laubenbacher. Chaos, 23, 025107, 2013. Paper.

31. Boolean nested canalizing functions: a comprehensive analysis. Yuan Li, John O. Adeyeye, David Murrugarra, Boris Aguilar, Reinhard Laubenbacher. Theoretical Computer Science, 481, 24-36, 2013. http://dx.doi.org/10.1016/j.tcs.2013.02.020.

32. The Number of Canalyzing Functions Over Any Finite Set. Yuan Li, David Murrugarra, John Adeyeye, Reinhard Laubenbacher. Open Journal of Discrete Mathematics, 3, 130-136, 2013. http://www.scirp.org/journal/PaperInformation.aspx?PaperID=34509.

33. Modeling Stochasticity and Variability in Gene Regulatory Networks. David Murrugarra, Alan Veliz-Cuba, Boris Aguilar, Seda Arat, Reinhard Laubenbacher. EURASIP Journal on Bioinformatics and Systems Biology, 2012:5, 2012. Paper.

34. The Number of Multistate Nested Canalyzing Functions. David Murrugarra and Reinhard Laubenbacher. Physica D: Nonlinear Phenomena, 241, 929-938, 2012. http://dx.doi.org/10.1016/j.physd.2012.02.011.

35. Bifurcations in Boolean Networks. Chris J. Kuhlman, Henning S. Mortveit, David Murrugarra, V. S. Anil Kumar. Discrete Mathematics and Theoretical Computer Science, proc, AP, 29-46, 2012. https://dmtcs.episciences.org/2975/pdf.

36. Regulatory Patterns in Molecular Interaction Networks. David Murrugarra and Reinhard Laubenbacher. Journal of Theoretical Biology, 288, 66-72, 2011. http://www.sciencedirect.com/science/article/pii/S0022519311004103.

37. A Mathematical Framework for Agent Based Models of Complex Biological Networks. Franziska Hinkelmann, David Murrugarra, Abdul Jarrah, Reinhard Laubenbacher. Bulletin of  Mathematical Biology, 73(7), 1583-1602, 2011. http://dx.doi.org/10.1007/s11538-010-9582-8.

38. Structure and Dynamics of Polynomial Dynamical Systems. Reinhard Laubenbacher, David Murrugarra, Alan Veliz-Cuba. Proc. 2011 NSF Engineering Research and Innovation Conference, Atlanta, GA, January 2011. http://arxiv.org/abs/1108.0209.

Preview Article:

1. An information theoretic approach for the inference of Boolean networks and functions from data: BoCSE. David Murrugarra and Alan Veliz-Cuba. Patterns, 3(11), 100617, 2022. https://www.sciencedirect.com/science/article/pii/S2666389922002422