Computational

Embryos assist morphogenesis of others through calcium and ATP signaling mechanisms in collective teratogen resistance
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)
Nature Communications, 15(1): 535

Machine Learning for Hypothesis Generation in Biology and Medicine: Exploring the latent space of neuroscience and developmental bioelectricity
O’Brien, T., Stremmel, J., Pio-Lopez, L., McMillen, P., Rasmussen-Ivey, C., and Levin, M. (2024)
Digital Discovery, 3(2): 249-263

From reinforcement learning to agency: Frameworks for understanding basal cognition
Seifert, G., Sealander, A., Marzen, S., and Levin, M. (2024)
BioSystems, 235(1): 105107

Information integration during bioelectric regulation of morphogenesis of the embryonic frog brain
Manicka, S., Pai, V. P, and Levin, M. (2023)
iScience, 26(12): 108398

Long Range Communication via Gap Junctions and Stress in Planarian Morphogenesis: A Computational Study
Blattner, M., and Levin, M. (2023)
Bioelectricity, 5(3): 196-209

Closing the Loop on Morphogenesis: A Mathematical Model of Morphogenesis by Closed-Loop Reaction-Diffusion
Grodstein, J., McMillen, P., and Levin, M. (2023)
Frontiers in Cell and Developmental Biology, 11: 1087650

Correcting instructive electric potential patterns in multicellular systems: External actions and endogenous processes
Cervera, J., Levin, M., and Mafé, S. (2023)
Biochimica et Biophysica Acta (BBA) - General Subjects, 1867(10): 130440

Searching in the Dark: Evolving Biobot Swarm Compositions to Efficiently Explore Obstructed Environments
Welch, P., Grasso, C., Gumuskaya, G., Levin, M., and Bongard, J. (2023)
Proceedings of ALIFE 2023: Ghost in the Machine, article 70, doi:10.1162/isal_a_00683

Regulative development as a model for origin of life and artificial life studies
Fields, C., and Levin, M. (2023)
Biosystems, 229: 104927

The collective intelligence of evolution and development
Watson, R., and Levin, M. (2023)
Collective Intelligence, 2(2), doi:10.1177/26339137231168355

Control flow in active inference systems Part II: Tensor networks as general models of control flow
Fields, C., Fabrocini, F., Friston, K., Glazebrook, J. F., Hazan, H., Levin, M., and Marcianò, A. (2023)
IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, doi:10.1109/TMBMC.2023.3272158

Control flow in active inference systems Part I: Classical and quantum formulations of active inference
Fields, C., Fabrocini, F., Friston, K., Glazebrook, J. F., Hazan, H., Levin, M., and Marcianò, A. (2023)
IEEE Transactions on Molecular, Biological, and Multi-Scale Communications, doi:10.1109/TMBMC.2023.3272150

The scaling of goals via homeostasis: an evolutionary simulation, experiment and analysis
Pio-Lopez, L., Bischof, J., LaPalme, J. V., and Levin, M. (2023)
Interface Focus, 13(3): 20220072

The nonlinearity of regulation in biological networks
Manicka, S., Johnson, K., Levin, M., and Murrugarra, D. (2023)
npj Systems Biology and Applications, 9(1): 10

There’s Plenty of Room Right Here: Biological Systems as Evolved, Overloaded, Multi-Scale Machines
Bongard, J., and Levin, M. (2023)
Biomimetics, 8(1): 110

Cellular Competency during Development Alters Evolutionary Dynamics in an Artificial Embryogeny Model
Shreesha, L., and Levin, M. (2023)
Entropy, 25(1): 131

Bioelectricity of non-excitable cells and multicellular pattern memories: Biophysical modeling
Cervera, J., Levin, M., and Mafe, S. (2023)
Physics Reports, 1004: 1-31

Learning in Transcriptional Network Models: Computational Discovery of Pathway-level Memory and Effective Interventions
Biswas, S., Clawson, W., and Levin, M. (2023)
International Journal of Molecular Sciences, 24(1): 285

Transplantation of fragments from different planaria: a bioelectrical model for head regeneration
Cervera, J., Manzanares, J. A., Levin, M.,  and Mafe, S. (2023)
Journal of Theoretical Biology, 558: 111356

Exploring the Behavior of Bioelectric Circuits Using Evolution Heuristic Search
Hazan, H., and Levin, M. (2022)
Bioelectricity, 4(4): 207-227

Active Inference, Morphogenesis, and Computational Psychiatry
Pio-Lopez, L., Kuchling, F., Tung, A., Pezzulo, G., and Levin, M. (2022)
Frontiers in Computational Neuroscience, 16: 988977

The Free Energy Principle induces neuromorphic development
Fields, C., Friston, K., Glazebrook, J. F., Levin, M., and Marcianò, A. (2022)
Neuromorphic Computing and Engineering, 2: 042002

Information Theory as an experimental tool for integrating disparate biophysical signaling modules
McMillen, P., Walker, S. I., and Levin, M. (2022)
International Journal of Molecular Sciences, 23(17): 9580

Adversarial Takeover of Neural Cellular Automata
Cavuoti, L., Sacco, F., Randazzo, E., and Levin, M. (2022)
Proceedings of the 2022 Conference on Artificial Life (ALIFE 2022),  pp. 256-263

Competition for Finite Resources as Coordination Mechanism for Morphogenesis: an evolutionary algorithm study of digital embryogeny
Smiley, P., and Levin, M. (2022)
BioSystems, 221: 104672

Enhancers of Host Immune Tolerance to Bacterial Infection Discovered Using Linked Computational and Experimental Approaches
Sperry, M. M., Novak, R., Keshari, V., Dinis, A. L. M., Cartwright, M. J., Camacho, D. M., Paré, J. F., Super, M., Levin, M., & Ingber, D. E. (2022)
Advanced Science, 9(26): 2200222

Neurons as hierarchies of quantum reference frames
Fields, C., Glazebrook, J. F., and Levin, M. (2022)
Biosystems, 219: 104714

A free energy principle for generic quantum systems 
Fields, C., Friston, K., Glazebrook, J. F., and Levin, M. (2022)
Progress in Biophysics and Molecular Biology, 173: 36-59

Metacognition as a Consequence of Competing Evolutionary Time Scales
Kuchling, F., Fields, C., and Levin, M. (2022)
Entropy, 24(5): 601

Design for an Individual: Connectionist approaches to the evolutionary transitions in individuality
Watson, R. A., Levin, M., and Buckley, C. L. (2022)
Frontiers in Ecology and Evolution, 10: 823588

Technological Approach to Mind Everywhere: an experimentally-grounded framework for understanding diverse bodies and minds
Levin, M. (2022)
Frontiers in Systems Neuroscience, 16: 768201

Biological underpinnings for lifelong learning machines
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)
Nature Machine Intelligence, 4(3): 196-210

A Computational Approach to Explaining Bioelectrically-induced Persistent, Stochastic Changes of Axial Polarity in Planarian Regeneration
Grodstein, J., and Levin, M. (2022)
Bioelectricity, 4(1): 18-30

Minimal developmental computation: a causal network approach to understand morphogenetic pattern formation
Manicka, S., and Levin, M. (2022)
Entropy, 24: 107

Morphology changes induced by intercellular gap junction blocking: a reaction-diffusion mechanism
Cervera, J., Levin, M., and Mafe, S. (2021)
BioSystems, 209: 104511

Evolution and emergence: higher order information structure in protein interactomes across the tree of life
Klein, B., Hoel, E., Swain, A., Griebenow, R., and Levin, M. (2021)
Integrative Biology, 13(12): 283-294

Kinematic self-replication in reconfigurable organisms
Kriegman, S., Blackiston, D., Levin, M., and Bongard, J. (2021)
Proceedings of the National Academy of Science, 118(49): e2112672118

Cell Systems Bioelectricity: How Different Intercellular Gap Junctions Could Regionalize a Multicellular Aggregate
Riol, A., Cervera, J., Levin, M., and Mafe, S. (2021)
Cancers, 13(21): 5300

Stability and robustness properties of bioelectric networks: A computational approach
Grodstein, J., and Levin, M. (2021)
Biophysics Review, 2(3): 031305

Scale invariant robot behavior with fractals
Kriegman, S., Nasab, A-M., Blackiston, D., Steele, H., Levin, M., Kramer-Bottiglio, R., and Bongard, R. (2021)
Robotics: Science and Systems (RSS), doi:10.15607/RSS.2021.XVII.059

Unmixing octopus camouflage by multispectral mapping of Octopus bimaculoides' chromatic elements
Guidetti, G., Levy, G., Matzeu, G., Finkelstein, J. M., Levin, M., and Omenetto, F. G. (2021)
Nanophotonics, 10(9): 2441-2450

Adversarial Reprogramming of Neural Cellular Automata: a robustness investigation
Randazzo, E., Mordvintsev, A., Niklasson, E., and Levin, M. (2021)
Distill, 6(5), doi:10.23915/distill.00027.004

Gene Regulatory Networks Exhibit Several Kinds of Memory: Quantification of Memory in Biological and Random Transcriptional Networks
Biswas, S., Manicka, S., Hoel, E., and Levin, M. (2021)
iScience, 24(3): 102131

A cellular platform for the development of synthetic living machines
Blackiston, D., Lederer, E., Kriegman, S., Garnier, S., Bongard, J., and Levin, M. (2021)
Science Robotics, 6(52): eabf1571

Living things are not (20th Century) machines: updating mechanism metaphors in light of the modern science of machine behavior
Bongard, J., and Levin, M. (2021)
Frontiers in Ecology and Evolution, 9: 650726

Self-organising Textures: Neural Cellular Automata Model of Pattern Formation
Niklasson, E., Mordvintsev, A., Randazzo, E., and Levin, M. (2021)
Distill, 6(2), doi:10.23915/distill.00027.003

Shape changing robots: bioinspiration, simulation, and physical realization
Shah, D., Yang, B., Kriegman, S., Levin, M., Bongard, J., and Kramer-Bottiglio, R. (2021)
Advanced Materials, 33(19): 2002882

A Comprehensive Conceptual and Computational Dynamics Framework for Autonomous Regeneration Systems
Minh-Thai, T. N., Samarasinghe, S., and Levin, M. (2021)
Artificial Life, 27(2): 80-104

Community effects allow bioelectrical reprogramming of cell membrane potentials in multicellular aggregates: Model simulations
Cervera, J., Ramirez, P., Levin, M., and Mafe, S. (2020)
Physical Review E, 102(5): 052412

Self-classifying MNIST Digits: Achieving Distributed Coordination with Neural Cellular Automata
Randazzo, E., Mordvintsev, A., Niklasson, E., Levin, M., and Greydanus, S. (2020)
Distill, 5(8), doi:10.23915/distill.00027.002

Emergence of Informative Higher Scales in Biological Systems: a computational toolkit for optimal prediction and control
Hoel, E., and Levin, M. (2020)
Communicative & Integrative Biology, 13(1): 108-118

Growing Neural Cellular Automata
Mordvintsev, A., Randazzo, E., Niklasson, E., and Levin, M. (2020)
Distill, 5(2), doi:10.23915/distill.00027.002

Morphogenesis as Bayesian Inference: a Variational Approach to Pattern Formation and Control in Complex Biological Systems
Kuchling, F., Friston, K., Georgiev, G., and Levin, M. (2020)
Physics of Life Reviews, 33: 88-108

On the coupling of mechanics with bioelectricity and its role in morphogenesis
Leronni, A., Bardella, L., Dorfmann, L., Pietak, A., and Levin, M. (2020)
Journal of the Royal Society Interface, 17(167): 20200177

Richard Borgens, 1946-2019
Levin, M., and Rajnicek, A. M. (2020)
Bioelectricity, 2(2): 205

HCN2 Channel-induced Rescue of Brain Teratogenesis via local and long-range bioelectric repair
Pai, V., Cervera, J., Mafe, S., Willocq, V., Lederer, E., and Levin, M. (2020)
Frontiers in Cellular Neuroscience, 14: 136

Scalable sim-to-real transfer of soft robot designs
Kriegman, S., Nasab, A. M., Shah, D., Steele, H., Branin, G., Levin, M., Bongard, J. and Kramer-Bottiglio, R. (2020)
Proceedings of the 3rd IEEE International Conference on Soft Robotics (RoboSoft 2020), p. 359-366

Bioelectrical Coupling of Single-Cell States in Multicellular Systems
Cervera, J., Levin, M., and Mafe, S. (2020), 
The Journal of Physical Chemistry Letters, 11(9): 3234-3241

Machine Learning-Driven Bioelectronics for Closed-Loop Control of Cells
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)
Advanced Intelligent Systems, 2(12): 2000140

A Scalable Pipeline for Designing Reconfigurable Organisms
Kriegman, S., Blackiston, D., Levin, M., and Bongard, J. (2020) 
Proceedings of the National Academy of Sciences of the United States, 117(4): 1853-1859

Bioelectrical model of head-tail patterning based on cell ion channels and intercellular gap junctions
Cervera, J., Meseguer, S., Levin, M., and Mafe, S. (2020)
Bioelectrochemistry, 132: 107410

Modeling somatic computation with non-neural bioelectric networks
Manicka, S., and Levin, M. (2019)
Scientific Reports 9: 18612

Automated Shapeshifting for Function Recovery in Damaged Robots
Kriegman, S., Walker, S., Shah, D. S., Kramer-Bottiglio, R., and Bongard, J. (2019)
Proceedings of Robotics: Science and Systems XV: 28

From non-excitable single-cell to multicellular bioelectrical states supported by ion channels and gap junction proteins: electrical potentials as distributed controllers
Cervera, C., Pai, V. P., Levin, M., and Mafe, S. (2019)
Progress in Biophysics and Molecular Biology, 149: 39-53

Synchronization of Bioelectric Oscillations in Networks of Nonexcitable Cells: From Single-Cell to Multicellular States
Cervera, J., Manzanares, J. A., Mafe, S., and Levin, M. (2019)
Journal of Physical Chemistry B, 123(18): 3924-3934

The Cognitive Lens: a primer on conceptual tools for analysing information processing in developmental and regenerative morphogenesis
Manicka, S., and Levin, M. (2019)
Philosophical Transactions of the Royal Society B, 374(1774): 20180369

Neural control of body-plan axis in regenerating planaria
Pietak, A., Bischof, J., LaPalme, J., Morokuma, J., and Levin, M. (2019)
PLOS Computational Biology, 15(4): e1006904

Toward modeling regeneration via adaptable echo state networks
Hammelman, J., Siegelmann, H., Manicka, S., and Levin, M. (2019)
in A. Adamatzky, S. Akl, and G. Sirakoulis (Eds.), From parallel to emergent computing, Chapter 6, pages 117-133, CRC Press: Boca Raton, FL

EDEn – Electroceutical Design Environment: An Ion Channel Database with Small Molecule Modulators
Churchill, C. D. M., Winter, P., Tuszynski, J. A., and Levin, M. (2019)
iScience, 11: 42-56

A Computational Framework for Autonomous Self-repair Systems
Minh-Thai, T. N., Aryal, J., Samarasinghe, S., and Levin, M. (2018)
in Mitrovic, T., Xue, B., and Li, X. (Eds.), AI 2018: Advances in Artificial Intelligence, p153-159. Lecture Notes in Computer Science, vol 11320. Springer, Cham

Pattern Regeneration in Coupled Networks
Moore, D. G., Walker, S. I., and Levin, M. (2018)
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, p. 204-205

Modeling Cell Migration in a Simulated Bioelectrical Signaling Network for Anatomical Regeneration
Ferreira, G. B. S., Scheutz, M., and Levin, M. (2018)
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, p. 194-201

From Physics to Pattern: Uncovering Pattern Formation in Tissue Electrophysiology
Brodsky, M., and Levin, M. (2018)
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, p. 351-358

Inform: Efficient Information-Theoretic Analysis of Collective Behaviors
Moore, D. G., Valentini, G., Walker, S. I., and Levin, M. (2018)
Frontiers in Robotics and AI, 5: 60

Embodying Markov blankets. Comment on 'Answering Schrödinger's question: A free-energy formulation' by Maxwell James Désormeau Ramstead et al.
Pezzulo, G., and Levin, M. (2018)
Physics of Life Reviews, 24: 32-36

Bioelectrical coupling in multicellular domains regulated by gap junctions: a conceptual approach
Cervera, J., Pietak, A., Levin, M., and Mafe, S. (2018)
Bioelectrochemistry, 123: 45-61

Bioelectrical control of positional information in development and regeneration: a review of conceptual and computational advances
Pietak, A., and Levin, M. (2018)
Progress in Biophysics and Molecular Biology, 137: 52-68

Are planaria individuals? What regenerative biology is telling us about the nature of multicellularity
Fields, C., and Levin, M. (2018)
Evolutionary Biology, 45(3): 237-247  

HCN2 Rescues brain defects by enforcing endogenous voltage pre-patterns
Pai, V. P., Pietak, A., Willocq, V., Ye, B., Shi, N-Q., and Levin, M. (2018)
Nature Communications, 9(1): 998

Inform: a toolkit for information-theoretic analysis of complex systems
Moore, D. G., Valentini, G., Walker, S. I., and Levin, M. (2018)
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 3258-3265

Introducing Simulated Stem Cells into a Bio-Inspired Cell-Cell Communication Mechanism for Structure Regeneration
Ferreira, G. B. S., Scheutz, M., and Levin, M. (2018)
Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence (SSCI), 2778-2785

Bioelectric Gene and Reaction Networks: Computational Modeling of Genetic, Biochemical, and Bioelectrical Dynamics in Pattern Regulation
Pietak, A. M., and Levin, M. (2017)
Journal of the Royal Society Interface, 14(134): 20170425

Cancer as a Disorder of Patterning Information: computational and biophysical perspectives on the cancer problem
Moore, D., Walker, S., and Levin, M. (2017)
Convergent Science Physical Oncology, 3(4): 043001

Investigating the Effects of Noise on a Cell-to-Cell Communication Mechanism for Structure Regeneration
Ferreira, G. B., Scheutz, M., and Levin, M. (2017)
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, pp. 170-177

Discovering novel phenotypes with automatically inferred dynamic models: partial melanocyte conversion in Xenopus
Lobo, D., Lobikin, M., and Levin, M. (2017)
Scientific Reports, 7: 41339

Modeling regenerative processes with Membrane Computing
Garcia-Quismondo, M., Levin, M., and Lobo, D. (2017)
Information Sciences, 381: 229-249

Computing a worm: reverse-engineering planarian regeneration
Lobo, D., and Levin, M. (2017)
in Adamatzky, A. (Ed), Advances in Unconventional Computing. Emergence, Complexity and Computation, vol 23, Springer: Cham, pp. 637-654

A Computational Model of Planarian Regeneration
De, A., Chakravarthy, V. S., and Levin, M. (2017)
International Journal of Parallel, Emergent, and Distributed Systems, 32(4): 331-347

Top-down models in biology: explanation and control of complex living systems above the molecular level
Pezzulo, G., and Levin, M. (2016)
Journal of the Royal Society Interface, 13(124): 20160555

Dynamic structure discovery and repair for 3D cell assemblages
Ferreira, G., Smiley, M., Scheutz, M., and Levin, M. (2016)
Proceedings of the Fifteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFEXV), pp. 352-359

A Level Set Approach to Simulating Xenopus laevis Tail Regeneration
Serlin, Z., Rife, J., and Levin, M. (2016)
Proceedings of the Fifteenth International Conference on the Synthesis and Simulation of Living Systems (ALIFEXV), pp. 528-535

Exploring Instructive Physiological Signaling with the Bioelectric Tissue Simulation Engine (BETSE)
Pietak, A., and Levin, M. (2016)
Frontiers in Bioengineering and Biotechnology, 4: 55

Computational discovery and in vivo validation of hnf4 as a regulatory gene in planarian re-generation
Lobo, D., Morokuma, J., and Levin, M. (2016)
Bioinformatics, 32(17): 2681-2685

MoCha: molecular characterization of unknown pathways
Lobo, D., Hammelman, J., and Levin, M. (2016)
Journal of Computational Biology, 23(4): 291-297

Towards a physarum learning chip
Whiting, J. G. H., Jones, J., Bull, L., Levin, M., and Adamatzky, A. (2016)
Scientific Reports, 6: 19948

Artificial neural networks as models of robustness in development and regeneration: stability of memory during morphological remodeling
Hammelman, J., Lobo, D., and Levin, M. (2016)
in S. Shanmuganathan and S. Samarasinghe (Eds.), Artificial Neural Network (ANN) Modeling, vol. 628, pp. 45-65

Automatic neuron segmentation and neural network analysis method for phase contrast microscopy images
Pang, J., Özkucur, N., Ren, M., Kaplan, D. L., Levin, M., and Miller, E. L. (2015)
Biomedical Optics Express, 6(11): 4395-4416

Serotonergic regulation of melanocyte conversion: A bioelectrically regulated network for stochastic all-or-none hyperpigmentation
Lobikin, M., Lobo, D., Blackiston, D. J., Martyniuk, C. J., Tkachenko, E., and Levin, M. (2015)
Science Signaling, 8(397): ra99

Bioelectric memory: modeling resting potential bistability in amphibian embryos and mammalian cells
Law, R., and Levin, M. (2015)
Theoretical Biology and Medical Modelling, 12(1): 22

Target morphology and cell memory: a model of regenerative pattern formation
Bessonov, N., Levin, M., Morozova, N., Reinberg, N., Tosenberger, A., and Volpert, V. (2015)
Neural Regeneration Research, 10(12): 1901-1905

Inferring regulatory networks from experimental morphological phenotypes: a computational method reverse-engineers planarian regeneration
Lobo, D., and Levin, M. (2015)
PLoS Computational Biology, 11(6): e1004295

A conceptual model of morphogenesis and regeneration
Tosenberger, A., Bessonov, N., Levin, M., Reinberg, N., Volpert, V., and Morozova, N. (2015)
Acta Biotheoretica, 63(3): 283-294

Knowing one's place: a free energy approach to pattern regulation
Friston, K., Levin, M., Sengupta B., and Pezzulo, G. (2015)
Journal of the Royal Society Interface, 12(105): 20141383

On a model of pattern recognition based on cell memory
Bessonov, N., Levin, M., Morozova, N., Reinberg, N., Tosenberger, A., and Volpert, V. (2015)
PLoS One, 10(2): e0118091

Long-range gap junctional signaling controls oncogene-mediated tumorigenesis in Xenopus laevis embryos
Chernet, B. T., Fields, C., and Levin, M. (2015)
Frontiers in Physiology, 5: 519

Limbform: a functional ontology-based database of limb regeneration experiments
Lobo, D., Feldman, E. B., Shah, M., Malone, T. J., and Levin, M. (2014)
Bioinformatics, 30(24): 3598-3600

Bioelectrical mechanisms for programming growth and form: taming physiological networks for soft body robotics
Mustard, J., and Levin, M. (2014)
Soft Robotics, 1(3): 169-191

A bioinformatics expert system linking functional data to anatomical outcomes in limb regeneration
Lobo, D., Feldman, E. B., Shah, M., Malone, T., and Levin, M. (2014)
Regeneration, 1(2): 37-56

Design of a flexible component gathering algorithm for converting cell-based models to graph representations for use in evolutionary search
Budnikova, M., Habig, J. W., Cornia, N., Levin. M., Lobo, D., and Andersen, T. (2014)
BMC Bioinformatics, 15(1): 178

A linear-encoding model explains the variability of the target morphology in regeneration
Lobo, D., Solano, M., Bubenik, G. A., and Levin, M. (2014)
Journal of the Royal Society Interface, 11(92): 20130918

Towards a bioinformatics of patterning: a computational approach to understanding regulative morphogenesis
Lobo, D., Malone, T. J., and Levin, M. (2013)
Biology Open, 2(2): 156-169

Planform: an application and database of graph-encoded planarian regenerative experiments
Lobo, D., Malone, T. J., and Levin, M. (2013)
Bioinformatics, 29(8): 1098-1100

Modeling planarian regeneration: a primer for reverse-engineering the worm
Lobo, D., Beane, W., and Levin, M. (2012)
PLoS Computational Biology, 8(4): e1002481

Long-distance signals are required for morphogenesis of the regenerating Xenopus tadpole tail, as shown by femtosecond-laser ablation
Mondia, J. P., Levin, M., Omenetto, F. G., Orendorff, R. D., Branch, M. R., and Adams, D. S. (2011)
PLoS One, 6(9): e24953

The wisdom of the body: future techniques and approaches to morphogenetic fields in regenerative medicine, developmental biology, and cancer
Levin, M. (2011) ​​​​
Regenerative Medicine, 6(6): 667-673

Particle tracking model of electrophoretic morphogen movement reveals stochastic dynamics of embryonic gradient
Zhang, Y., and Levin, M. (2009)
Developmental Dynamics, 238(8): 1923-1935

Mathematical Model of Morphogen Electrophoresis through Gap Junctions
Esser, A. T., Smith, K. C., Weaver, J. C., and Levin, M. (2006)
Developmental Dynamics, 235(8): 2144-2159

Matrix-based GA representations in a model of evolving animal communication
Levin, M. (1999)
in L. Chambers (Ed.), The Practical Handbook of Genetic Algorithms: Complex Coding Systems, Vol. 3, CRC Press: Boca Raton FL, Chapter 5, pp. 103-117

Use of Genetic Algorithms to Solve Biomedical Problems
Levin, M. (1995)
M.D. Computing, 12(3): 193-198

The evolution of understanding: A genetic algorithm model of the evolution of animal communication
Levin, M. (1995)
BioSystems, 36(3): 167-178

Locating putative protein signal sequences
Levin, M. (1995)
in L. Chambers (Ed.), The Practical Handbook of Genetic Algorithms: New Frontiers, Vol. 2, CRC Press: Boca Raton FL, Chapter 2, pp. 53-66

A Julia set model of field-directed morphogenesis: developmental biology and artificial life
Levin, M. (1994)
Computer Applications in the Biosciences, 10(2): 85-103

Discontinuous and alternate q-system fractals
Levin, M. (1994)
Computers and Graphics, 18(6): 873-884