Bio computing

Using living organisms as logic gates or even as general computing devices. Viewed as a computational science this might be considered an especially quaint sub-field of Turing-Machine-hunting. OTOH, the ability to bake real computation into the structures of life suggests many obvious applications and surely non-obvious ones.

As distinct from doing computation using computers with algorithms modeled off living organisms - that is the field of biomimetic algorithms.

Projects like Microsoft’s Station B and Biological computation unit are angling for some market share in this field. There are many others.


Abramson, Charles I., and Michael Levin. 2021. β€œBehaviorist Approaches to Investigating Memory and Learning: A Primer for Synthetic Biology and Bioengineering.” Communicative & Integrative Biology 14 (1): 230–47.
Adamatzky, Andrew, and Theresa Schubert. 2014. β€œSlime Mold Microfluidic Logical Gates.” Materials Today 17 (2): 86–91.
Baer, R M, and H M Martinez. 1974. β€œAutomata and Biology.” Annual Review of Biophysics and Bioengineering 3 (1): 255–91.
Beniaguev, David, Idan Segev, and Michael London. 2021. β€œSingle Cortical Neurons as Deep Artificial Neural Networks.” Neuron 109 (17): 2727–2739.e3.
Bongard, Joshua, and Michael Levin. 2021. β€œLiving Things Are Not (20th Century) Machines: Updating Mechanism Metaphors in Light of the Modern Science of Machine Behavior.” Frontiers in Ecology and Evolution 9.
Bray. 1995. β€œProtein Molecules as Computational Elements in Living Cells.” Nature 376: 307–12.
Brette, Romain. 2012. β€œComputing with Neural Synchrony.” PLoS Comput Biol 8 (6): e1002561.
Chen, Zibo, James M. Linton, Ronghui Zhu, and Michael B. Elowitz. 2022. β€œA Synthetic Protein-Level Neural Network in Mammalian Cells.” bioRxiv.
Fields, Chris, and Michael Levin. 2020. β€œHow Do Living Systems Create Meaning?” Philosophies 5 (4): 36.
β€”β€”β€”. 2021. β€œMetabolic limits on classical information processing by biological cells.” Bio Systems 209 (November): 104513.
Gopalkrishnan, Manoj. 2015. β€œA Scheme for Molecular Computation of Maximum Likelihood Estimators for Log-Linear Models.” arXiv:1506.03172 [Cs, Math, q-Bio, Stat], June.
Klein, Brennan, Erik Hoel, Anshuman Swain, Ross Griebenow, and Michael Levin. 2021. β€œEvolution and Emergence: Higher Order Information Structure in Protein Interactomes Across the Tree of Life.” Integrative Biology 13 (12): 283–94.
Levin, Michael. 2019. β€œThe Computational Boundary of a β€˜Self’: Developmental Bioelectricity Drives Multicellularity and Scale-Free Cognition.” Frontiers in Psychology 10.
Levin, Michael, Fred Keijzer, Pamela Lyon, and Detlev Arendt. 2021. β€œUncovering Cognitive Similarities and Differences, Conservation and Innovation.” Philosophical Transactions of the Royal Society B: Biological Sciences 376 (1821): 20200458.
Levin, Rafael Yuste, Michael. n.d. β€œNew Clues about the Origins of Biological Intelligence.” Scientific American.
Liang, Yuchen, Chaitanya K. Ryali, Benjamin Hoover, Leopold Grinberg, Saket Navlakha, Mohammed J. Zaki, and Dmitry Krotov. 2021. β€œCan a Fruit Fly Learn Word Embeddings?” arXiv:2101.06887 [Cs, q-Bio, Stat], January.
Lyon, Pamela, Fred Keijzer, Detlev Arendt, and Michael Levin. 2021. β€œReframing Cognition: Getting down to Biological Basics.” Philosophical Transactions of the Royal Society B: Biological Sciences 376 (1820): 20190750.
Manicka, Santosh, and Michael Levin. 2022. β€œMinimal Developmental Computation: A Causal Network Approach to Understand Morphogenetic Pattern Formation.” Entropy 24 (1): 107.
McGee, Ryan Seamus, Olivia Kosterlitz, Artem Kaznatcheev, Benjamin Kerr, and Carl T. Bergstrom. 2022. β€œThe Cost of Information Acquisition by Natural Selection.” bioRxiv.
Orellana, Josue, Jordan Rodu, and Robert E. Kass. 2017. β€œPopulation Vectors Can Provide Near Optimal Integration of Information.” Neural Computation 29 (8): 2021–29.
Randazzo, Ettore, Alexander Mordvintsev, Eyvind Niklasson, Michael Levin, and Sam Greydanus. 2020. β€œSelf-Classifying MNIST Digits.” Distill 5 (8): e00027.002.
Scarle, Simon. 2009. β€œImplications of the Turing completeness of reaction-diffusion models, informed by GPGPU simulations on an XBox 360: cardiac arrhythmias, re-entry and the Halting problem.” Computational Biology and Chemistry 33 (4): 253–60.
Semenov, Sergey N., Lewis J. Kraft, Alar Ainla, Mengxia Zhao, Mostafa Baghbanzadeh, Victoria E. Campbell, Kyungtae Kang, Jerome M. Fox, and George M. Whitesides. 2016. β€œAutocatalytic, Bistable, Oscillatory Networks of Biologically Relevant Organic Reactions.” Nature 537 (7622): 656–60.
Straszak, Damian, and Nisheeth K. Vishnoi. 2016. β€œIRLS and Slime Mold: Equivalence and Convergence.” arXiv:1601.02712 [Cs, Math, Stat], January.
Vanchurin, Vitaly, Yuri I. Wolf, Mikhail Katsnelson, and Eugene V. Koonin. 2021. β€œTowards a Theory of Evolution as Multilevel Learning.” Cold Spring Harbor Laboratory.
Watson, Richard A., Michael Levin, and Christopher L. Buckley. 2022. β€œDesign for an Individual: Connectionist Approaches to the Evolutionary Transitions in Individuality.” Frontiers in Ecology and Evolution 10.
Watson, Richard A., Rob Mills, C. L. Buckley, Kostas Kouvaris, Adam Jackson, Simon T. Powers, Chris Cox, et al. 2016. β€œEvolutionary Connectionism: Algorithmic Principles Underlying the Evolution of Biological Organisation in Evo-Devo, Evo-Eco and Evolutionary Transitions.” Evolutionary Biology 43 (4): 553–81.
Wilkinson, Darren J. 2009. β€œStochastic Modelling for Quantitative Description of Heterogeneous Biological Systems.” Nature Reviews Genetics 10 (2): 122–33.

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