ArticleProceedings of the National Academy of Sciences of the United States of America2023
Turing, von Neumann, and the computational architecture of biological machines.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Building centaur responders: is emergency management ready for artificial intelligence?Disasters · 2026Article
- Chemputer and chemputation-A universal chemical compound synthesis machine.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- When prediction fails: a computational complexity view of stress.Frontiers in veterinary science · 2026Article
- Form and function in biological filaments: a physicist's review.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025Review
- Fundamental constraints to the logic of living systems.Interface focus · 2024Review
- Hyperdimensional computing: A fast, robust, and interpretable paradigm for biological data.PLoS computational biology · 2024Review
- AlphaFold3 takes a step toward decoding molecular behavior and biological computation.Nature structural & molecular biology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
In the mid-1930s, the English mathematician and logician Alan Turing invented an imaginary machine which could emulate the process of manipulating finite symbolic configurations by human computers. His machine launched the field of computer science and provided a foundation for the modern-day programmable computer. A decade later, building on Turing's machine, the American-Hungarian mathematician John von Neumann invented an imaginary self-reproducing machine capable of open-ended evolution. Through his machine, von Neumann answered one of the deepest questions in Biology: Why is it that all living organisms carry a self-description in the form of DNA? The story behind how two pioneers of computer science stumbled on the secret of life many years before the discovery of the DNA double helix is not well known, not even to biologists, and you will not find it in biology textbooks. Yet, the story is just as relevant today as it was eighty years ago: Turing and von Neumann left a blueprint for studying biological systems as if they were computing machines. This approach may hold the key to answering many remaining questions in Biology and could even lead to advances in computer science.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.