Publications
[38] Claus Kadelka, Reinhard Laubenbacher, David Murrugarra, Alan Veliz-Cuba, and Matthew Wheeler. Modularizing the Control Search for Biological Systems. In preparation.
[37] Alan Veliz-Cuba and Zeyu Wang. Designing Arbitrary Multistationarity with AND Gates. In preparation.
[36] Alan Veliz-Cuba, Stephen Randal Voss, and David Murrugarra. Reverse engineering using response data. Submitted.
[35] Elena Dimitrova, Cameron Fredrickson, Nicholas Rondoni, Brandy Stigler, and Alan Veliz-Cuba. Algebraic experimental design: theory and computation. Submitted.
[34] Alan Veliz-Cuba, Vanessa Newsome-Slade, and Elena Dimitrova. A unified approach to reverse engineering and data selection for unique network identification. SIAM Journal on Applied Dynamical Systems. Accepted, 2023.
[33] Claus Kadelka, Matthew Wheeler, Alan Veliz-Cuba, David Murrugarra, and Reinhard Laubenbacher. Modularity of biological systems: a link between structure and function. Journal of the Royal Society Interface. Accepted, 2023.
[32] Heather Harrington, Mike Stillman, and Alan Veliz-Cuba. Algebraic network reconstruction of discrete dynamical systems. Advances in Applied Mathematics. Accepted, 2023.
[31] Alan Veliz-Cuba. Primary decomposition of squarefree pseudomonomial ideals. Journal of software for algebra and geometry. 12:27-32, 2022. pdf
CODE: https://github.com/Macaulay2/M2/pull/2686 (written in Macaulay2)
[30] David Murrugarra and Alan Veliz-Cuba. An information theoretic approach for the inference of Boolean networks and functions from data: BoCSE. Patterns, 3(11):100617, 2022. pdf
[29] Alan Veliz-Cuba, Stephen Randal Voss, and David Murrugarra, Building model prototypes from time-course data. Letters in Biomathematics, 9(1):107-120, 2022. pdf
CODE: https://github.com/alanavc/prototype-model (written in Matlab/Octave)
[28] Stephen Randal Voss, Jeramiah James Smith, Nataliya Timoshevskaya, Larissa V Ponomareva, Jon S Thorson, Alan Veliz-Cuba, David Murrugarra. HDAC Inhibitor Titration of Transcription and Axolotl Tail Regeneration. Frontiers in Cell and Developmental Biology, 9:767377, 2021. pdf
[27] P. Márquez-Zacarías, Rozenn M Pineau, Marcella Gomez, Alan Veliz-Cuba, David Murrugarra, William C Ratcliff, Karl J Niklas. Evolution of cellular differentiation: from hypotheses to models. Trends in Ecology & Evolution, 36(1):49-60, 2021. pdf
[26] Adrian E Radillo, Alan Veliz-Cuba, Krešimir Josić, Zachary P Kilpatrick. Performance of normative and approximate evidence accumulation on the dynamic clicks task. Neuron Behav Data Anal Theory, 2019; 3(1). pdf
[25] A. Veliz-Cuba and Lauren Geiser. The Number of Fixed Points of AND-OR Networks with Chain Topology. Involve, 12(6):1051-1068, 2019. pdf
[24] A. Veliz-Cuba and R. Laubenbacher. Dynamics of semilattice networks with strongly connected dependency graph. Automatica, 99(2019): 167-174, 2019. pdf
[23] M. Sadeghpour, A. Veliz-Cuba, G. Orosz, K. Josic, and M. Bennett. Bistability and oscillations in co-repressive synthetic microbial consortia. Quantitative Biology, 5(1): 55-66, 2017. pdf
[22] A. Radillo, A. Veliz-Cuba, K. Josic, and Z. Kilpatrick. Evidence accumulation and change rate inference in dynamic environments. Neural Computation, 29(6): 1561-1610, 2017. pdf
[21] A. Veliz-Cuba, C. Gupta, M. Bennett, K. Josic, and W. Ott. Effects of cell cycle noise on excitable gene circuits. Physical Biology, 13(6): 066007, 2016. pdf
[20] D. Murrugarra, A. Veliz-Cuba, B. Aguilar, and R. Laubenbacher. Identification of control targets of Boolean molecular network models via computational algebra. BMC Systems Biology, 10(1): 94, 2016. pdf
[19] A. Veliz-Cuba, Z. Kilpatrick, and K. Josic. Stochastic models of evidence accumulation in changing environments. SIAM Review, 58(2): 264-289, 2016. pdf
[18] A. Veliz-Cuba, A. Hirning, A. Atanas, F. Hussain, F. Vancia, and K. Josic, and M. Bennett. Sources of Variability in a Synthetic Gene Oscillator. PLOS Computational Biology, 11(12): e1004674, 2015. pdf
[17] A. Veliz-Cuba, H. Shouval, K. Josic, and Z. Kilpatrick. Neural networks that learn the precise timing of event sequences. Journal of Computational Neuroscience, 39(3): 235-254, 2015. pdf
[16] A. Veliz-Cuba, B. Aguilar, and R. Laubenbacher. Dimension Reduction of Large Sparse AND-NOT Network Models. Electronic Notes in Theoretical Computer Science, 316: 83-95, 2015. pdf
[15] A. Veliz-Cuba, A. Kumar, and K. Josic. Piecewise linear and Boolean models of chemical reaction networks. Bulletin of Mathematical Biology, 76(12):2945-2984, 2014. pdf
[14] A. Veliz-Cuba, B. Aguilar, F. Hinkelmann, and R. Laubenbacher. Steady state analysis of Boolean molecular network models via model reduction and computational algebra. BMC Bioinformatics 15:221, 2014. pdf
CODE: github.com/alanavc/BNReduction (written in C++, Perl, Macaulay2)
[13] A. Veliz-Cuba, D. Murrugarra, and R. Laubenbacher. Structure and Dynamics of Acyclic Networks. Discrete Event Dynamic Systems, 24(4): 647-658, 2014. pdf
[12] C. Curto, V. Itskov, A. Veliz-Cuba, and N. Youngs. The Neural Ring: An Algebraic Tool for Analyzing the Intrinsic Structure of Neural Codes. Bulletin of Mathematical Biology. 75(9): 1571-1611, 2013. pdf
[11] A. Veliz-Cuba, K. Buschur, R. Hamershock, A. Kniss, E. Wolff and R. Laubenbacher. AND-NOT logic framework for steady state analysis of Boolean network models. Applied Mathematics and Information Sciences. 7(4): 1263-1274, 2013. pdf
[10] A. Veliz-Cuba. An Algebraic Approach to Reverse Engineering Finite Dynamical Systems Arising from Biology. SIAM Journal on Applied Dynamical Systems, 11(1):31-48, 2012. pdf
[9] A. Veliz-Cuba, J. Arthur, L. Hochstetler, V. Klomps, and E. Korpi. On the Relationship of Steady States of Continuous and Discrete Models Arising from Biology. Bulletin of Mathematical Biology. 74(12), 2779-2792, 2012. pdf
[8] A. Veliz-Cuba and R. Laubenbacher. On the computation of fixed points in Boolean networks. Journal of Applied Mathematics and Computing, 39(1-2):145-153, 2012. pdf
[7] D. Murrugarra, A. Veliz-Cuba, B. Aguilar, S. Arat, and R. Laubenbacher. Modeling Stochasticity and Variability in Gene Regulatory Networks. EURASIP Journal on Bioinformatics and Systems Biology, 2012:5. pdf
[6] A. Veliz-Cuba. Reduction of Boolean Network Models. Journal of Theoretical Biology, 289:167-172, 2011. pdf
CODE: RedBN (written in Mathematica)
[5] A. Veliz-Cuba and B. Stigler. Boolean Models can Explain Bistability in the lac Operon. Journal of Computational Biology, 18(6):783-794, 2011. pdf
[4] F. Hinkelmann, M. Brandon, B. Guang, R. McNeill, G. Blekherman, A. Veliz-Cuba, and R. Laubenbacher. ADAM: Analysis of Discrete Models of Biological Systems Using Computer Algebra. BMC Bioinformatics, 12:295, 2011. pdf
[3] A. Veliz-Cuba, A. Jarrah, and R. Laubenbacher. Polynomial Algebra of Discrete Models in Systems Biology. Bioinformatics, 26:1637-1643, 2010. pdf
[2] A. Jarrah, R. Laubenbacher, and A. Veliz-Cuba. The Dynamics of Conjunctive and Disjunctive Boolean Network Models. Bull. Math. Bio., 72(6):1425-1447, 2010. pdf
[1] E. Sontag, A. Veliz-Cuba, R. Laubenbacher, and A. Jarrah. The Effect of Negative Feedback Loops on the Dynamics of Boolean Networks. Biophysical Journal, 95:518–526, 2008. pdf
Other Publications:
A. Veliz-Cuba and D. Murrugarra. Steady State Analysis of Boolean Models: A Dimension Reduction Approach (book chapter). Algebraic and Discrete Mathematical Methods for Modern Biology: A Modern Algebra Approach, edited by Raina Robeva, Academic Press, ISBN: 9780128012710, 2015.
R. Laubenbacher, F. Hinkelmann, D. Murrugarra, and A. Veliz-Cuba. Algebraic Models and Their Use in Systems Biology (peer-reviewed book chapter). Discrete and Topological Models in Molecular Biology, edited by Natasa Jonoska and Masahico Saito, Springer, ISBN: 9783642401923, 2013.