Peer-Reviewed Papers
Computational
Cervera, J., Levin, M., Mafe, S. (2024), Multicellular adaptation to electrophysiological perturbations analyzed by deterministic and stochastic bioelectrical models, Scientific Reports 2024, 27608 doi:10.1038/s41598-024-79087-7
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Buckley, C.L., Lewens, T., Levin, M., Millidge, B., Tschantz, A., Watson, R.A. (2024), Natural Induction: Spontaneous Adaptive Organisation without Natural Selection, Entropy 2024, 26, 765, doi: 10.3390/e26090765
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Zhang, T., Goldstein, A., Levin M. (2024), Classical sorting algorithms as a model of morphogenesis: Self-sorting arrays reveal unexpected competencies in a minimal model of basal intelligence, Adaptive Behavior 2024, doi: 10.1177/10597123241269740
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Cervera, J., Manzanares, J. A., Levin, M., Mafe, S. (2024), Oscillatory phenomena in electrophysiological networks: The coupling between cell bioelectricity and transcription, Computers in Biology and Medicine 2024, 80 doi: 10.1016/j.compbiomed.2024.108964
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Shreesha, L., and Levin, M. (2024), Stress sharing as cognitive glue for collective intelligences: A computational model of stress as a coordinator for morphogenesis , Biochemical and Biophysical Research Communications 2024, 731 doi: 10.1016/j.bbrc.2024.150396
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Hartl, B., Risi, S., Levin, M. (2024), Evolutionary Implications of Self-Assembling Cybernetic Materials with Collective Problem-Solving Intelligence at Multiple Scales, Entropy 2024, 26(7), 532; doi:10.3390/e26070532
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Fields, C., Glazebrook, J. F., and Levin, M. (2024), Principled Limitations on Self-Representation for Generic Physical Systems, Entropy, 26(3): 194
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Etcheverry, M., Moulin-Frier, C., Oudeyer, P.-Y, and Levin, M. (2024), AI-driven Automated Discovery Tools Reveal Diverse Behavioral Competencies of Biological Networks, eLife, 13: RP92683
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Tung, A., Sperry, M., Clawson, W., Pavuluri, A., Bulatao, S., Yue, M., Flores, R. M., Pai, V. McMillen, P., Kuchling, F., and Levin, M. (2024), Embryos assist morphogenesis of others through calcium and ATP signaling mechanisms in collective teratogen resistance, Nature Communications, 15(1): 535
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O’Brien, T., Stremmel, J., Pio-Lopez, L., McMillen, P., Rasmussen-Ivey, C., and Levin, M. (2024), Machine Learning for Hypothesis Generation in Biology and Medicine: Exploring the latent space of neuroscience and developmental bioelectricity, Digital Discovery, 3(2): 249-263
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Seifert, G., Sealander, A., Marzen, S., and Levin, M. (2024), From reinforcement learning to agency: Frameworks for understanding basal cognition, BioSystems, 235(1): 105107
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Manicka, S., Pai, V. P, and Levin, M. (2023), Information integration during bioelectric regulation of morphogenesis of the embryonic frog brain, iScience, 26(12): 108398
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Blattner, M., and Levin, M. (2023) Long Range Communication via Gap Junctions and Stress in Planarian Morphogenesis: A Computational Study, Bioelectricity, 5(3): 196-209
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Grodstein, J., McMillen, P., and Levin, M. (2023), Closing the Loop on Morphogenesis: A Mathematical Model of Morphogenesis by Closed-Loop Reaction-Diffusion, Frontiers in Cell and Developmental Biology, 11: 1087650
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Cervera, J., Levin, M., and Mafé, S. (2023), Correcting instructive electric potential patterns in multicellular systems: External actions and endogenous processes, Biochimica et Biophysica Acta (BBA) - General Subjects, 1867(10): 130440
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Welch, P., Grasso, C., Gumuskaya, G., Levin, M., and Bongard, J. (2023), Searching in the Dark: Evolving Biobot Swarm Compositions to Efficiently Explore Obstructed Environments, Proceedings of ALIFE 2023: Ghost in the Machine, article 70, doi:10.1162/isal_a_00683
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Fields, C., and Levin, M. (2023), Regulative development as a model for origin of life and artificial life studies, Biosystems, 229: 104927
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Watson, R., and Levin, M. (2023), The collective intelligence of evolution and development, Collective Intelligence, 2(2), doi:10.1177/26339137231168355
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Fields, C., Fabrocini, F., Friston, K., Glazebrook, J. F., Hazan, H., Levin, M., and Marcianò, A. (2023), Control flow in active inference systems Part II: Tensor networks as general models of control flow, IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, doi:10.1109/TMBMC.2023.3272158
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Fields, C., Fabrocini, F., Friston, K., Glazebrook, J. F., Hazan, H., Levin, M., and Marcianò, A. (2023), Control flow in active inference systems Part I: Classical and quantum formulations of active inference, IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, doi:10.1109/TMBMC.2023.3272150
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Pio-Lopez, L., Bischof, J., LaPalme, J. V., and Levin, M. (2023), The scaling of goals via homeostasis: an evolutionary simulation, experiment and analysis, Interface Focus, 13(3): 20220072
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Manicka, S., Johnson, K., Levin, M., and Murrugarra, D. (2023), The nonlinearity of regulation in biological networks, npj Systems Biology and Applications, 9(1): 10
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Bongard, J., and Levin, M. (2023), There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines, Biomimetics, 8(1): 110
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Shreesha, L., and Levin, M. (2023), Cellular Competency during Development Alters Evolutionary Dynamics in an Artificial Embryogeny Model, Entropy, 25(1), 131, doi:10.3390/e25010131
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Cervera, J., Levin, M., and Mafe, S. (2023), Bioelectricity of non-excitable cells and multicellular pattern memories: Biophysical modeling, Physics Reports, 1004: 1-31, doi:10.1016/j.physrep.2022.12.003
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Biswas, S., Clawson, W., and Levin. M. (2023), Learning in Transcriptional Network Models: Computational Discovery of Pathway-level Memory and Effective Interventions, International Journal of Molecular Sciences, 24(1): 285
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Hazan, H., and Levin, M. (2022), Exploring the Behavior of Bioelectric Circuits Using Evolution Heuristic Search, Bioelectricity, 4(4): 207-227
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Pio-Lopez, L., Kuchling, F., Tung, A., Pezzulo, G., and Levin, M. (2022), Active Inference, Morphogenesis, and Computational Psychiatry, Frontiers in Computational Neuroscience, 16: 988977
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Cervera, J., Manzanares, J. A., Levin, M., and Mafe, S. (2022), Transplantation of fragments from different planaria: a bioelectrical model for head regeneration, Journal of Theoretical Biology, 558: 111356
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Fields, C., Friston, K., Glazebrook, J. F., Levin, M., and Marcianò, A. (2022), The Free Energy Principle induces neuromorphic development, Neuromorphic Computing and Engineering, 2: 042002
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McMillen, P., and Levin, M. (2022), Information Theory as an experimental tool for integrating disparate biophysical signaling modules, International Journal of Molecular Sciences, 23(17): 9580
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Cavuoti, L., Sacco, F., Randazzo, E., & Levin, M. (2022), Adversarial Takeover of Neural Cellular Automata, Proceedings of the 2022 Conference on Artificial Life (ALIFE 2022), p. 256-263
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Smiley, P., and Levin, M. (2022), Competition for Finite Resources as Coordination Mechanism for Morphogenesis: an evolutionary algorithm study of digital embryogeny, BioSystems, 221: 104672
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Sperry, M. M., Novak, R., Keshari, V., Dinis, A. L. M., Cartwright, M. J., Camacho, D. M., Paré, J. F., Super, M., Levin, M., and Ingber, D. E. (2022), Enhancers of Host Immune Tolerance to Bacterial Infection Discovered Using Linked Computational and Experimental Approaches, Advanced Science, 9(26): 2200222
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Fields, C., Glazebrook, J. F., and Levin, M. (2022), Neurons as hierarchies of quantum reference frames, Biosystems, 219: 104714
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Fields, C., Friston, K., Glazebrook, J. F., and Levin, M. (2022), A free energy principle for generic quantum systems, Progress in Biophysics and Molecular Biology, 173: 36-59
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Kuchling, F., Fields, C., and Levin, M. (2022), Metacognition as a Consequence of Competing Evolutionary Time Scales, Entropy, 24(5): 601
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Watson, R. A., Levin, M., and Buckley, C. L. (2022), Design
for an Individual: Connectionist approaches to the evolutionary transitions in individuality,
Frontiers in Ecology and Evolution, 10: 823588
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Levin, M. (2022), Technological Approach to Mind Everywhere: an experimentally-grounded framework for understanding diverse bodies and minds,
Frontiers in Systems Neuroscience, 16: 768201
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Kudithipudi, D., Aguilar-Simon, M., Babb, J., Bazhenov, M., Blackiston, D., Bongard, J., Brna, A. P., Raja, S. C., Cheney, N., Clune, J., Daram, A., Fusi, S., Helfer, P., Kay, L., Ketz, N., Kira, Z., Kolouri, S., Krichmar, J. L., Kriegman, S., Levin, M., Madireddy, S., Manicka, S., Marjaninejad, A., McNaughton, B., Miikkulainen, R., Navratilova, Z., Pandit, T., Parker, A., Pilly, P. K., Risi, S., Sejnowski, T. J., Soltoggio, A., Soures, N., Tolias, A. S., Urbina-Meléndez, D., Valero-Cuevas, F. J., van de Ven, G. M., Vogelstein, J. T., Wang, F., Weiss, R., Yanguas-Gil, A., Zou, X., and Siegelmann, H. (2022), Biological underpinnings for lifelong learning machines, Nature Machine Intelligence, 4(3): 196-210
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Grodstein, J., and Levin, M. (2022), A Computational Approach to Explaining Bioelectrically-induced Persistent, Stochastic Changes of Axial Polarity in Planarian Regeneration,
Bioelectricity, 4(1): 18-30
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Manicka, S., and Levin, M. (2022), Minimal developmental computation: a causal network
approach to understand morphogenetic pattern formation, Entropy, 24: 107
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Klein, B., Hoel, E., Swain, A., Griebenow, R., and Levin, M. (2021), Evolution and emergence: higher order information structure in protein interactomes across the tree of life,
Integrative Biology, 13(12): 283-294
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Kriegman, S., Blackiston, D., Levin, M., and Bongard, J. (2021), Kinematic self-replication in reconfigurable organisms,
Proceedings of the National Academy of Science, 118(49): e2112672118
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Minh-Thai, T. N., Samarasinghe, S., and Levin, M. (2021), A Comprehensive Conceptual and Computational Dynamics Framework for Autonomous Regeneration Systems, Artificial Life, 27(2): 80-104
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Riol, A., Cervera, J., Levin, M., and Mafe, S. (2021), Cell Systems Bioelectricity: How Different Intercellular Gap Junctions Could Regionalize a Multicellular Aggregate,
Cancers, 13(21): 5300
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Grodstein, J., and Levin, M. (2021), Stability and robustness properties of bioelectric networks: A computational approach,
Biophysics Review, 2: 031305
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Guidetti, G., Levy, G., Matzeu, G., Finkelstein, J. M., Levin, M., and Omenetto, F. G. (2021), Unmixing octopus camouflage by multispectral mapping of Octopus bimaculoides' chromatic elements, Nanophotonics, 10(9): 2441-2450
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Kriegman, S., Nasab, A-M., Blackiston, D., Steele, H., Levin, M., Kramer-Bottiglio, R., and Bongard, J. (2021), Scale invariant robot behavior with fractals, Robotics: Science and Systems (RSS 2021), doi:10.15607/RSS.2021.XVII.059
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Cervera, J., Levin, M., and Mafe, S. (2021), Morphology changes induced by intercellular
gap junction blocking: a reaction-diffusion mechanism, BioSystems, 209: 104511
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Niklasson, E., Mordvintsev, A., Randazzo, E., and Levin, M. (2021), Self-organising Textures: Neural Cellular Automata Model of Pattern Formation, Distill, 6(2), doi:10.23915/distill.00027.003
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Randazzo, E., Mordvintsev, A., Niklasson, E., and Levin, M. (2021),
Adversarial Reprogramming of Neural Cellular Automata: a robustness investigation, Distill, 6(5), doi:10.23915/distill.00027.004
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Blackiston, D., Lederer, E., Kriegman, S., Garnier, S., Bongard, J., and Levin, M. (2021),
A cellular platform for the development of synthetic living machines, Science Robotics, 6(52): eabf1571
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Bongard, J., and Levin, M. (2021), Living things are not (20th Century) machines:
updating mechanism metaphors in light of the modern science of machine behavior,
Frontiers in Ecology and Evolution, 9: 650726
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Biswas, S., Manicka, S., Hoel, E., and Levin, M. (2021), Gene Regulatory Networks
Exhibit Several Kinds of Memory: Quantification of Memory in Biological and Random Transcriptional Networks, iScience, 24(3): 102131
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Shah, D., Yang, B., Kriegman, S., Levin, M., Bongard, J., and Kramer-Bottiglio, R. (2021),
Shape changing robots: bioinspiration, simulation, and physical realization,
Advanced Materials, 33(19): 2170150
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Cervera, J., Ramirez, P., Levin, M., and Mafe, S. (2020), Community effects allow bioelectrical reprogramming of cell membrane potentials in multicellular aggregates: Model simulations, Physical Review E, 102(5): 052412
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Selberg, J., Jafari, M., Mathews, J., Jia, M., Pansodtee, P., Dechiraju, H., Wu, C., Cordero, S., Flora, A., Yonas, N., Jannetty, S., Diberardinis, M., Teodorescu, M., Levin, M., Gomez, M., and Rolandi, M. (2020), Machine Learning-Driven Bioelectronics for Closed-Loop Control of Cells, Advanced Intelligent Systems, 2(12): 2000140
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Randazzo, E., Mordvintsev, A., Niklasson, E., Levin, M., and Greydanus, S. (2020), Self-classifying MNIST Digits: Achieving Distributed Coordination with Neural Cellular Automata, Distill, 5(8), doi:10.23915/distill.00027.002
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Mordvintsev, A., Randazzo, E., Niklasson, E., and Levin, M. (2020), Growing Neural Cellular Automata: Differentiable Model of Morphogenesis, Distill, 5(2), doi:10.23915/distill.00027.002
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Kuchling, F., Friston, K., Georgiev, G., and Levin, M. (2020), Morphogenesis as Bayesian Inference: a Variational Approach to Pattern Formation and Control in Complex Biologic Systems, Physics of Life Reviews, 33: 88-108
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Hoel, E., and Levin, M. (2020), Emergence of Informative Higher Scales in Biological Systems:
a computational toolkit for optimal prediction and control, Communicative & Integrative Biology, 13(1): 108-118
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Leronni, A., Bardella, L., Dorfmann, L., Pietak, A., and Levin, M. (2020), On the coupling of mechanics with bioelectricity and its role in morphogenesis, Journal of the Royal Society Interface, 17(167): 20200177
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Pai, V., Cervera, J., Mafe, S., Willocq, V., Lederer, E., and Levin, M. (2020), HCN2 Channel-induced Rescue of Brain Teratogenesis via local and long-range bioelectric repair, Frontiers in Cellular Neuroscience, 14: 136
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Cervera, J., Levin, M., and Mafe, S. (2020), Bioelectrical Coupling of Single-Cell States in Multicellular Systems, Journal of Physical Chemistry Letters, 11(9): 3234-3241
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Kriegman, S., Nasab, A. M., Shah, D., Steele, H., Branin, G., Levin, M., Bongard, J. and Kramer-Bottiglio, R. (2020),
Scalable sim-to-real transfer of soft robot designs,
Proceedings of the 3rd IEEE International Conference on Soft Robotics (RoboSoft 2020), p. 359-366
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Kriegman, S., Blackiston, D., Levin, M., and Bongard, J. (2020), A scalable pipeline for designing reconfigurable organisms, Proceedings of the National Academy of Sciences of the United States, 432(2): 605-620
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Cervera, J., Meseguer, S., Levin, M., and Mafe, S. (2020), Bioelectrical model of head-tail patterning
based on cell ion channels and intercellular gap junctions, Bioelectrochemistry, 132: 107410
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Manicka, S., and Levin, M. (2019), Modeling somatic computation with non-neural bioelectric networks, Scientific Reports, 9: 18612
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Kriegman, S., Walker, S., Shah, D. S., Levin, M., Kramer-Bottiglio, R., and Bongard, J. (2019), Automated Shapeshifting for Function Recovery in Damaged Robots, Proceedings of Robotics: Science and Systems XV: 28
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Cervera, C., Pai, V. P., Levin, M., and Mafe, S. (2019),
From non-excitable single-cell to multicellular bioelectrical states
supported by ion channels and gap junction proteins: electrical potentials
as distributed controllers, Progress in Biophysics and Molecular Biology, 149: 39-53
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Cervera, J., Manzanares, J. A., Mafe, S., and Levin, M. (2019), Synchronization of Bioelectric Oscillations in Networks of Nonexcitable Cells: From Single-Cell to Multicellular States, Journal of Physical Chemistry B, 123(18): 3924-3934
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Manicka, S., and Levin, M. (2019), The Cognitive Lens: a primer on conceptual tools for analysing
information processing in developmental and regenerative morphogenesis, Philosophical Transactions
of the Royal Society B, 374(1774): 20180369
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Pietak, A., Bischof, J., LaPalme, J., Morokuma, J., and Levin, M. (2019), Neural control of body-plan axis in regenerating planaria,
PLOS Computational Biology, 15(4): e1006904
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Hammelman, J., Siegelmann, H., Manicka, S., and Levin, M. (2019), Toward modeling regeneration via adaptable echo state networks, in A. Adamatzky, S. Akl, and G. Sirakoulis (Eds.), From parallel to emergent computing, Chapter 6, pages 117-133, CRC Press: Boca Raton, FL
Churchill, C. D. M., Winter, P., Tuszynski, J. A., and Levin, M. (2019), EDEn - Electroceutical Design Environment: An Ion Channel Database with Small Molecule Modulators, iScience, 11: 42-56
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Minh-Thai, T. N., Aryal, J., Samarasinghe, S., and Levin, M. (2018), A Computational Framework for Autonomous Self-repair Systems, in Mitrovic, T., Xue, B., and Li, X. (Eds.), AI 2018: Advances in Artificial Intelligence. Lecture Notes in Computer Science, 11320: 153-159, Springer: Cham
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Moore, D. G., Walker, S. I., and Levin, M. (2018), Pattern Regeneration in Coupled Networks, in T. Ikegami, N. Virgo, O. Witkowski, M. Oka, R. Suzuki and H. Iizuka (Eds.), ALIFE 2018: The 2018 Conference on Artificial Life. MIT Press: Tokyo,
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Ferreira, G. B. S., Scheutz, M., and Levin, M. (2018), Modeling Cell Migration in a Simulated Bioelectrical Signaling Network for Anatomical Regeneration, in T. Ikegami, N. Virgo, O. Witkowski, M. Oka, R. Suzuki and H. Iizuka (Eds.), ALIFE 2018: The 2018 Conference on Artificial Life. MIT Press: Tokyo,
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Brodsky, M., and Levin, M. (2018), From Physics to Pattern: Uncovering Pattern Formation in Tissue Electrophysiology, in T. Ikegami, N. Virgo, O. Witkowski, M. Oka, R. Suzuki and H. Iizuka (Eds.), ALIFE 2018: The 2018 Conference on Artificial Life. MIT Press: Tokyo,
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Cervera, J., Pietak, A., Levin, M., and Mafe, S. (2018), Bioelectrical coupling in multicellular
domains regulated by gap junctions: a conceptual approach, Bioelectrochemistry, 123: 45-61
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Pietak, A., and Levin, M. (2018), Bioelectrical control of positional information in
development and regeneration: a review of conceptual and computational advances,
Progress in Biophysics and Molecular Biology, 137: 52-68
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Moore, D. G., Valentini, G., Walker, S. I., and Levin, M. (2018),
Inform: Efficient Information-Theoretic Analysis of Collective Behaviors, Frontiers in Robotics and AI,
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Pezzulo, G., and Levin, M. (2018), Embodying Markov blankets. Comment on 'Answering Schrödinger's question:
A free-energy formulation' by Maxwell James Désormeau Ramstead et al., Physics of Life Reviews, 24: 32-36
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Fields, C., and Levin, M. (2018), Are planaria individuals? What regenerative
biology is telling us about the nature of multicellularity, Evolutionary Biology,
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Pai, V. P., Pietak, A., Willocq, V., Ye, B., Shi, N-Q., and Levin, M. (2018),
HCN2 Rescues brain defects by enforcing endogenous voltage pre-patterns,
Nature Communications, 9(1): 998
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Moore, D. G., Valentini, G., Walker, S. I., and Levin, M. (2018), Inform: a toolkit for information-theoretic analysis of complex systems, Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence (SSCI), p. 3258-3265
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Ferreira, G. B. S., Scheutz, M., and Levin, M. (2018), Introducing Simulated Stem Cells
into a Bio-Inspired Cell-Cell Communication Mechanism for Structure Regeneration,
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence (SSCI), p. 2778-2785
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Pietak, A. M., and Levin, M. (2017), Bioelectric Gene and Reaction Networks: Computational Modeling of Genetic, Biochemical, and Bioelectrical Dynamics in Pattern Regulation, Journal of the Royal Society Interface, 14(134): 20170425
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Moore, D., Walker, S. I., and Levin, M. (2017), Cancer as a Disorder of Patterning Information: computational and biophysical perspectives on the cancer problem, Convergent Science Physical Oncology,
Ferreira, G. B., Scheutz, M., and Levin, M. (2017), Investigating the Effects of Noise on
a Cell-to-Cell Communication Mechanism for Structure Regeneration, in C. Knibbe, D. Parsons, D. Misevic, J. Rouzaud-Cornaba, N. Bredèche, S. Hassas, O. Simonin, and H. Soula. (Eds.),
Proceedings of the 14th European Conference on Artificial Life (ECAL 2017), Lyon, France, p. 170-177
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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., and Lobo, D. (2017), Modeling regenerative processes with
Membrane Computing, Information Sciences, 381: 229-249
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Lobo, D., and Levin, M. (2017), Computing a worm: reverse-engineering planarian regeneration, in Adamatzky, A. (Ed), Advances in Unconventional Computing. Emergence, Complexity and Computation, vol 23, Springer: Cham, pp. 637-654
De, Abhishek, Chakravarthy, V. S., and Levin, M. (2017), A Computational Model of Planarian Regeneration, International Journal of Parallel, Emergent, and Distributed Systems, 32(4): 331-347
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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(124): 20160555
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Ferreira, G., Smiley, M., Scheutz, M., and Levin, M. (2016), Dynamic structure discovery and repair for 3D cell assemblages, Proceedings of the Fifteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFEXV), 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 Fifteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFEXV), p. 528-535
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Pietak, A., and Levin, M. (2016), Exploring Instructive Physiological Signaling with
the Bioelectric Tissue Simulation Engine , Frontiers in Bioengineering and Biotechnology, 4: (55)
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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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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
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 S. Shanmuganathan and S. Samarasinghe (Eds.), Artificial Neural Network (ANN) Modeling. Studies in Computational Intelligence, vol. 628, pp. 45-65
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Pang, J., Özkucur, N., Ren, M., Kaplan, D. L., Levin, M., and Miller, E. L. (2015),
Automatic neuron segmentation and neural network analysis method for phase contrast microscopy images, Biomedical Optics Express, 6(11): 4395-4416
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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., and 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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Tosenberger, A., Bessonov, N., Levin, M., Reinberg, N., Volpert, V., and Morozova, N. (2015),
A conceptual model of morphogenesis and regeneration, Acta Biotheoretica, 63(3): 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(105): 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. (2015), Long-range gap junctional signaling
controls oncogene-mediated tumorigenesis in Xenopus laevis embryos, Frontiers in Physiology, 5: 519
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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, 1(3): 169-191
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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(1): 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(92): 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(2): 156-169
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Lobo, D., Malone, T. J., and Levin, M. (2013), Planform: an application and database of graph-encoded planarian regenerative experiments, Bioinformatics, 29(8): 1098-1100
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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, 8(4): e1002481
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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, as shown by femtosecond-laser ablation, 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), Mathematical Model of Morphogen Electrophoresis through Gap Junctions, Developmental Dynamics, 235(8): 2144-2159
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Levin, M. (1999), Matrix-based GA representations in a model of evolving animal communication, in L. Chambers (Ed.), The Practical Handbook of Genetic Algorithms: Complex Coding Systems, Vol. 3, ch.5, pp. 103-117, CRC Press: Boca Raton, FL
Levin, M. (1995), Use of Genetic Algorithms to Solve
Biomedical Problems, M.D. Computing, 12(3): 193-198
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Levin, M. (1995), The evolution of understanding: A
genetic algorithm model of the evolution of animal communication,
BioSystems, 36(3): 167-178
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Levin, M., (1995), Locating putative protein signal
sequences, in L. Chambers (Ed.), The Practical Handbook of Genetic Algorithms:
New Frontiers, Vol. 2, ch. 2, pp. 53-66, CRC Press: Boca
Raton, FL
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Levin, M. (1994), A Julia set model of field-directed morphogenesis: developmental biology
and artificial life, Computer Applications in the Biosciences, 10(2): 85-103
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Levin, M. (1994), Discontinuous and alternate q-system
fractals, Computers and Graphics, 18(6): 873-884
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