@article{Schneider.geneff2023,
author = "T. D. Schneider",
title = "{Generalizing the Isothermal Efficiency by Using Gaussian
Distributions}",
journal = "PLOS ONE",
pages = "1--17",
pmid = "https://pubmed.ncbi.nlm.nih.gov/36626367/",
pmcid = "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9831307/",
note = "
Preprint: \url{https://biorxiv.org/cgi/content/short/2022.12.12.520049v1},
My page on the paper: \url{https://alum.mit.edu/www/toms/papers/geneff/},
Official publication: \url{https://doi.org/10.1371/journal.pone.0279758}",
year = "2023"}

• Abstract:

  Unlike the Carnot heat engine efficiency published in 1824, an isothermal efficiency derived from thermodynamics and information theory can be applied to biological systems. The original approach by Pierce and Cutler in 1959 to derive the isothermal efficiency equation came from Shannon's channel capacity of 1949 and from Felker's 1952 determination of the minimum energy dissipation needed to gain a bit. In 1991 and 2010 Schneider showed how the isothermal efficiency equation can be applied to molecular machines and that this can be used to explain why several molecular machines are 70% efficient. Surprisingly, some macroscopic biological systems, such as whole ecosystems, are also 70% efficient but it is hard to see how this could be explained by a thermodynamic and molecular theory. The thesis of this paper is that the isothermal efficiency can be derived without using thermodynamics by starting from a set of independent Gaussian distributions. This novel derivation generalizes the isothermal efficiency equation for use at all levels of biology, from molecules to ecosystems.
• 
  

  Significance:

  This paper is important because it unleashes the power of information theory for analyzing systems across biology from microscopic interactions to entire ecosystems. It does so by untethering the concept of isothermal efficiency, which I developed previously, from thermodynamics and a molecular viewpoint. The method is to start from noise impacting on a system. By the central limit theorem, this leads to Gaussian distributions. Biological systems have many parts so they are high dimensional. Noisy high dimensional distributions are spherical and, following Shannon's 1949 paper and the paper by Pierce and Cutler 1959, that leads to the isothermal efficiency. This is a key paper because it allows biologists to measure and understand the isothermal efficiency, a fundamental biological parameter.
• Preprint 2022 Dec 14:
  • geneffbiorxiv.pdf from this website
  • lexa-inst.txt: delila instructions for the LexA figure Supplementary material
  • geneffbiorxiv.pdf from bioRxiv
  • archive.org

Background Papers

• Sequence Logos
  • logopaper: Sequence Logos: A New Way to Display Consensus Sequences
  • schneider1986: Information Content of Binding Sites
  • baseflip: Strong Minor Groove Base Conservation in Sequence Logos implies DNA Distortion or Base Flipping during Replication and Transcription Initiation
  • repan3: The P1 Phage Replication Protein RepA Contacts an Otherwise Inaccessible Thymine N3 Proton by DNA Distortion or Base Flipping
• Molecular Machines and Shannon spheres
  • ccmm: Theory of Molecular Machines. I. Channel Capacity of Molecular Machines
  • edmm: Theory of Molecular Machines. II. Energy Dissipation from Molecular Machines
  • nano2: Sequence Logos, Machine/Channel Capacity, Maxwell's Demon, and Molecular Computers: a Review of the Theory of Molecular Machines. Review
  • shannonbiologist: Claude Shannon: Biologist
  • brmit: A Brief Review of Molecular Information Theory
  • emmgeo: 70% efficiency of bistate molecular machines explained by information theory, high dimensional geometry and evolutionary convergence
  • lattice: Restriction enzymes use a 24 dimensional coding space to recognize 6 base long DNA sequences

Works that depend on this work

• code: Why is the Genetic Code Degenerate?

Permanent links Tinyurl for this page: http://tinyurl.com/geneff points to https://alum.mit.edu/www/toms/papers/geneff/ which points to the current web location.

Link to the glossary of terms

Schneider Lab
origin: 2019 Feb 11
updated: version = 1.07 of geneff.html 2023 Jul 21