Research articles

Publications:

1. Pancreatic cancer mutationscape: revealing the link between modular restructuring and intervention efficacy amidst common mutations. Daniel Plaugher, and David Murrugarra. npj Systems Biology and Applications, accepted. https://www.biorxiv.org/content/10.1101/2024.01.27.577546v1 

2. Canalization reduces the nonlinearity of regulation in biological networks. Claus Kadelka and David Murrugarra. npj Systems Biology and Applications, accepted, 2024. https://arxiv.org/abs/2402.09703 

3. 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://doi.org/10.1101/2023.01.23.525286 

4. 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

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

6. 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 

7. 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

8. 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 

9. 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 

10. 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

11. 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

12. 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/

13. 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

14. 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.

15. 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.

16. 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.

17. 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.

18. 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.

19. 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. Full Text.

20. 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.

21. 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.

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

23. 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.

24. 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.

25. 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.

26. 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.

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

28. 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.

29. 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.

30. 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.

31. 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.

32. 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. http://www.dmtcs.org/dmtcs-ojs/index.php/proceedings/article/view/dmAP0103.

33. 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.

34. 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.

35. 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.