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Probabilistic Inference with Polymerizing Biochemical Circuits
Probabilistic inference—the process of estimating the values of unobserved variables in probabilistic models—has been used to describe various cognitive phenomena related to learning and memory. While the study of biological realizations of inference has focused on animal nervous systems, single-cel...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140500/ https://www.ncbi.nlm.nih.gov/pubmed/35626513 http://dx.doi.org/10.3390/e24050629 |
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author | Katz, Yarden Fontana, Walter |
author_facet | Katz, Yarden Fontana, Walter |
author_sort | Katz, Yarden |
collection | PubMed |
description | Probabilistic inference—the process of estimating the values of unobserved variables in probabilistic models—has been used to describe various cognitive phenomena related to learning and memory. While the study of biological realizations of inference has focused on animal nervous systems, single-celled organisms also show complex and potentially “predictive” behaviors in changing environments. Yet, it is unclear how the biochemical machinery found in cells might perform inference. Here, we show how inference in a simple Markov model can be approximately realized, in real-time, using polymerizing biochemical circuits. Our approach relies on assembling linear polymers that record the history of environmental changes, where the polymerization process produces molecular complexes that reflect posterior probabilities. We discuss the implications of realizing inference using biochemistry, and the potential of polymerization as a form of biological information-processing. |
format | Online Article Text |
id | pubmed-9140500 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-91405002022-05-28 Probabilistic Inference with Polymerizing Biochemical Circuits Katz, Yarden Fontana, Walter Entropy (Basel) Article Probabilistic inference—the process of estimating the values of unobserved variables in probabilistic models—has been used to describe various cognitive phenomena related to learning and memory. While the study of biological realizations of inference has focused on animal nervous systems, single-celled organisms also show complex and potentially “predictive” behaviors in changing environments. Yet, it is unclear how the biochemical machinery found in cells might perform inference. Here, we show how inference in a simple Markov model can be approximately realized, in real-time, using polymerizing biochemical circuits. Our approach relies on assembling linear polymers that record the history of environmental changes, where the polymerization process produces molecular complexes that reflect posterior probabilities. We discuss the implications of realizing inference using biochemistry, and the potential of polymerization as a form of biological information-processing. MDPI 2022-04-29 /pmc/articles/PMC9140500/ /pubmed/35626513 http://dx.doi.org/10.3390/e24050629 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Katz, Yarden Fontana, Walter Probabilistic Inference with Polymerizing Biochemical Circuits |
title | Probabilistic Inference with Polymerizing Biochemical Circuits |
title_full | Probabilistic Inference with Polymerizing Biochemical Circuits |
title_fullStr | Probabilistic Inference with Polymerizing Biochemical Circuits |
title_full_unstemmed | Probabilistic Inference with Polymerizing Biochemical Circuits |
title_short | Probabilistic Inference with Polymerizing Biochemical Circuits |
title_sort | probabilistic inference with polymerizing biochemical circuits |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9140500/ https://www.ncbi.nlm.nih.gov/pubmed/35626513 http://dx.doi.org/10.3390/e24050629 |
work_keys_str_mv | AT katzyarden probabilisticinferencewithpolymerizingbiochemicalcircuits AT fontanawalter probabilisticinferencewithpolymerizingbiochemicalcircuits |