An information theory approach to homeostasis

_{Denyse O'Leary

September 27, 2017

Cell biology, Information, Intelligent Design}

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A prevailing view among physiologists is that homeostasis evolves to protect organisms from damaging variation in physiological factors. Here, we propose that homeostasis also evolves to minimize noise in physiological channels. Fluctuations in physiological factors constitute inescapable noise that corrupts the transfer of information through physiological systems. We apply information theory to homeostasis to develop two related ideas. First, homeostatic regulation creates quiet physiological backgrounds for the transmission of all kinds of physiological information. Second, the performance of any homeostatic system influences information processing in other homeostatic systems. This dependence implies that multiple homeostatic systems, embedded within individual organisms, should show strongly nonadditive effects. Paper. (public access) – H. Arthur Woods, J. Keaton Wilson, An information hypothesis for the evolution of homeostasis
More.

Those guys should be cautious about information theory. It isn’t really support for “it all somehow just happens randomly via the magic of natural selection.”

See also: Homeostasis: Life’s balancing act as a challenge to unguided evolution

Comments

Here, we propose that homeostasis also evolves to minimize noise in physiological channels.
Noise working diligently to reduce, filter, and control noise. How very helpful!
In electronics, analogous devices are called band-pass filters, notch filters, or high-or low-pass filters.
If only engineers could apply Darwin's wisdom, they wouldn't have need to come up with such contraptions! LocalMinimum

A January 2018 paper? Transcriptomics to Metabolomics: A Network Perspective for Big Data Chapter · January 2018?with?54 Reads DOI: 10.4018/978-1-5225-2607-0.ch008 A lot of omics data is generated in a recent decade which flooded the internet with transcriptomic, genomics, proteomics and metabolomics data. A number of software, tools, and web-servers have developed to analyze the big data omics. This review integrates the various methods that have been employed over the years to interpret the gene regulatory and metabolic networks. It illustrates random networks, scale-free networks, small world network, bipartite networks and other topological analysis which fits in biological networks. Transcriptome to metabolome network is of interest because of key enzymes identification and regulatory hub genes prediction. It also provides an insight into the understanding of omics technologies, generation of data and impact of in-silico analysis on the scientific community. https://www.igi-global.com/chapter/transcriptomics-to-metabolomics/182947 https://www.researchgate.net/publication/318215440_Transcriptomics_to_Metabolomics_A_Network_Perspective_for_Big_Data Dionisio

NETWORK BIOLOGY: UNDERSTANDING THE CELL'S FUNCTIONAL ORGANIZATION Old paper with gazillion citations by newer papers: https://www.researchgate.net/publication/8910145_Network_Biology_Understanding_The_Cell's_Functional_Organization Dionisio

A related paper on biological complexity: Complexity in biology: Exceeding the limits of reductionism and determinism using complexity theory EMBO Reports, volume 9, issue 1, pp 10-14, DOI: 10.1038/sj.embor.7401147 Fulvio Mazzocchi (National Research Council) https://academic.microsoft.com/#/detail/1876117392?FORM=DACADP Dionisio

Here's another paper on biology complexity: A framework for understanding the characteristics of complexity in biology DOI: 10.1186/s40594-016-0047-y Full text PDF available. https://www.researchgate.net/publication/306020245_A_framework_for_understanding_the_characteristics_of_complexity_in_biology Dionisio

ScienceDirect link to the given (paywall) paper, showing 19 newer papers that cite it: http://www.sciencedirect.com/science/article/pii/S016953 Researchgate link to the paper also showing the 19 citations and a button to download the full text (PDF): https://www.researchgate.net/publication/233772593_An_information_hypothesis_for_the_evolution_of_homeostasis Here's a link to the (free) full text (PDF): https://www.researchgate.net/profile/Jerome_Wilson7/publication/233772593_An_information_hypothesis_for_the_evolution_of_homeostasis/links/55edaf1b08aedecb68fb0a81/An-information-hypothesis-for-the-evolution-of-homeostasis. Here's another related paper: https://www.researchgate.net/publication/285545004_A_physiologist's_view_of_homeostasis Dionisio

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