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Publications

Computational

Pietak, A. M., and Levin, M., (2017), Bioelectric Gene and Reaction Networks: Computational Modeling of Genetic, Biochemical, and Bioelectrical Dynamics in Pattern Regulation, J. Royal Society Interface, 14: 20170425
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Moore, D., Walker, S., and Levin, M., (2017), Cancer as a Disorder of Patterning Information: computational and biophysical perspectives on the cancer problem, Convergent Science Physical Oncology, in press

Ferreira, G. B., M. Levin, and Scheutz, M., (2017), Investigating the Effects of Noise on a Cell-to-Cell Communication Mechanism for Structure Regeneration, 14th European Conference on Artificial Life, Lyon, France

Lobo, D., Lobikin, M., and Levin, M., (2017), Discovering novel phenotypes with automatically inferred dynamic models: partial melanocyte conversion in Xenopus, Scientific Reports, 7: 41339
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Garcia-Quismondo, M., Levin, M., Lobo, D. (2017), Modeling regenerative processes with Membrane Computing, Information Sciences, 381: 229-249
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Pezzulo, G., and Levin, M., (2016), Top-down Models in biology: Explanation and control of complex living systems above the molecular level, Journal of the Royal Society Interface, 13: 20160555
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Ferreira, G. B. S., Smiley, M., Scheutz, M., and Levin, M., (2016), Dynamic structure discovery and repair for 3D cell assemblages, Proceedings of the Artificial Life Conference 2016, p. 352-359
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Serlin, Z., Rife, J., and Levin, M., (2016), A Level Set Approach to Simulating Xenopus laevis Tail Regeneration, Proceedings of the Artificial Life Conference 2016, p. 528-535
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Pietak, A., and Levin, M., (2016), Exploring Instructive Physiological Signaling with the Bioelectric Tissue Simulation Engine (BETSE), Frontiers in Bioengineering and Biotechnology, 4(55): doi 10.3389/fbioe.2016.00055
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Lobo, D., Morokuma, J., and Levin, M., (2016), Computational discovery and in vivo validation of hnf4 as a regulatory gene in planarian re-generation, Bioinformatics, 32(17): 2681-2685
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De, Abhishek, Chakravarthy, V. Srinivasa , and Levin, M., (2016), A Computational Model of Planarian Regeneration, International Journal of Parallel, Emergent, and Distributed Systems, 32(4): 331-347
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Lobo, D., Hammelman, J., and Levin, M., (2016), MoCha: molecular characterization of unknown pathways, Journal of Computational Biology, 23(4): 291-297
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Whiting, J. G. H., Jones, J., Bull, L., Levin, M., and Adamatzky, A., (2016), Towards a physarum learning chip, Scientific Reports, 6:19948 (1-14)

Hammelman, J., Lobo, D., and Levin, M., (2016), Artificial neural networks as models of robustness in development and regeneration: stability of memory during morphological remodeling, in Artificial Neural Network (ANN) Modelling, S. Shanmuganathan and S. Samarasinghe editors, in press

Pang, J., Ozkucur, N., Ren, M., Kaplan, D. L., Levin, M., and Miller, E. L., (2015), An automatic neuron segmentation and neural network analysis method for phase contrast microscopy images, Biomedical Optics Express, 6(11) 4395-4416
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Lobo, D., and Levin, M., (2016), Computing a worm: reverse-engineering planarian regeneration, Advances in Unconventional Computing, Andrew Adamatzky ed., Vol. 2, Springer, p. 637-654

Lobikin, M., Lobo, D., Blackiston, D. J., Martyniuk, C. J., Tkachenko, E., and Levin, M., (2015), Serotonergic regulation of melanocyte conversion: A bioelectrically regulated network for stochastic all-or-none hyperpigmentation, Science Signaling, 8(397): ra99
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Law, R., and Levin, M., (2015), Bioelectric memory: modeling resting potential bistability in amphibian embryos and mammalian cells, Theoretical Biology and Medical Modelling, 12: (1): 22
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Bessonov, N., Levin, M., Morozova, N., Reinberg, N., Tosenberger, A., Volpert, V., (2015), Target morphology and cell memory: a model of regenerative pattern formation, Neural Regeneration Research, 10(12): 1901-1905
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Lobo, D., and Levin, M., (2015), Inferring regulatory networks from experimental morphological phenotypes: a computational method reverse-engineers planarian regeneration, PLoS Computational Biology, 11(6): e1004295
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A. Tosenberger, N. Bessonov, M. Levin, N. Reinberg, V.Volpert, N. Morozova, (2015), A conceptual model of morphogenesis and regeneration, Acta Biotheoretica, 63: 283-294
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Friston, K., Levin, M., Sengupta B., and Pezzulo, G., (2015), 'Knowing one's place' a free energy approach to pattern regulation, Journal of the Royal Society Interface, 12: 20141383
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Bessonov, N., Levin, M., Morozova, N., Reinberg, N., Tosenberger, A., and Volpert, V., (2015), On a model of pattern recognition based on cell memory, PLoS One, 10(2): e0118091
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Chernet, B. T., Fields, C., and Levin, M., (2014), Long-range gap junctional signaling controls oncogene-mediated tumorigenesis in Xenopus laevis embryos, Frontiers in Physiology, 5(519) 1-15, doi: 10.3389/fphys.2014.00519
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Lobo, D., Feldman, E. B., Shah, M., Malone, T. J., and Levin, M., (2014), Limbform: a functional ontology-based database of limb regeneration experiments, Bioinformatics, 30(24): 3598-3600
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Mustard, J., and Levin, M., (2014), Bioelectrical mechanisms for programming growth and form: taming physiological networks for soft body robotics, Soft Robotics, 2(3): 1-23
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Lobo, D., Feldman E. B., Shah, M., Malone, T., and Levin, M., (2014), A bioinformatics expert system linking functional data to anatomical outcomes in limb regeneration, Regeneration, 1(2): 37-56
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Budnikova, M., Habig, J. W., Cornia, N., Levin. M., Lobo, D., and Andersen, T., (2014), Design of a flexible component gathering algorithm for converting cell-based models to graph representations for use in evolutionary search, BMC Bioinformatics, 15: 178
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Lobo, D., Solano, M., Bubenik, G. A., and Levin, M., (2014), A linear-encoding model explains the variability of the target morphology in regeneration, Journal of the Royal Society Interface, 11: 20130918
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Lobo, D., Malone, T. J., and Levin, M., (2013), Towards a bioinformatics of patterning: a computational approach to understanding regulative morphogenesis, Biology Open, 2:156-169, doi: 10.1242/bio.20123400
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Daniel Lobo; Taylor J. Malone; Michael Levin, (2013), Planform: an application and database of graph-encoded planarian regenerative experiments, Bioinformatics, 29(8): 1098-1100, doi: 10.1093/bioinformatics/btt088
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Lobo, D., Beane, W., and Levin, M., (2012), Modeling planarian regeneration: a primer for reverse-engineering the worm, PLoS Computational Biology, doi: 10.1371/journal.pcbi.1002481
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Mondia, J. P., Levin, M., Omenetto, F. G., Orendorff, R. D., Branch, M. R., and Adams, D. S., (2011), Long-distance signals are required for morphogenesis of the regenerating Xenopus tadpole tail. PLoS One, 6(9): e24953.
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Levin, M., (2011), The wisdom of the body: future techniques and approaches to morphogenetic fields in regenerative medicine, developmental biology, and cancer. Regenerative Medicine, 6(6): 667-673
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Zhang, Y., and M. Levin, (2009), Particle tracking model of electrophoretic morphogen movement reveals stochastic dynamics of embryonic gradient, Developmental Dynamics, 238(8): 1923-1935
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Esser, A. T., Smith, K. C., Weaver, J. C., and Levin, M., (2006), A Mathematical Model of Morphogen Electrophoresis through Gap Junctions. Developmental Dynamics, 235: 2144-2159
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Levin, Michael, (1995), Use of Genetic Algorithms to solve biomedical Problems. M.D. Computing, 12(3): 193-198
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Levin, Michael, (1995), A genetic algorithm model of the evolution of animal communication. BioSystems, 36: 167-178
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Levin, Michael, (1995), Locating putative protein signal sequences using genetic algorithms, in Applications Handbook of Genetic Algorithms, Vol. 2, pp. 53-66, CRC Press: FL
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Levin, Michael, A Julia set model of field-directed morphogenesis, (1994), Computer Applications in the Biosciences, 10(2): 85-103
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Levin, Michael, (1994), Discontinuous and alternate q-system fractals. Computers and Graphics, 18(6): 873-884
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