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Functional information

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Information content of biological systems

The concept of functional information is an attempt to rigorously define the information content of biological systems. The concept was originated by a group led by Jack W. Szostak in 2003.[1]

Definition

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They define functional information as follows:[2] [3]

  • the concept of degree of function is introduced, where the degree of function E x {\displaystyle E_{x}} {\displaystyle E_{x}} is a non-negative objective measure of the capability of system E {\displaystyle E} {\displaystyle E} to do the physical function x {\displaystyle x} {\displaystyle x}.
  • the fraction of possible configurations of the system that can achieve at least a particular level of function θ {\displaystyle \theta } {\displaystyle \theta } in regard to the physical function x {\displaystyle x} {\displaystyle x} is defined to be F ( E x θ ) {\displaystyle F(E_{x}\geq \theta )} {\displaystyle F(E_{x}\geq \theta )}
  • the functional information relative to a given level of function E x = θ {\displaystyle E_{x}=\theta } {\displaystyle E_{x}=\theta } is defined as I ( E x θ ) = l o g 2 F ( E x θ ) {\displaystyle I(E_{x}\geq \theta )=-log_{2}F(E_{x}\geq \theta )} {\displaystyle I(E_{x}\geq \theta )=-log_{2}F(E_{x}\geq \theta )}

This leads to two conclusions:

  • because all possible configurations can achieve zero or more functionality, that is to say F ( E x 0 ) = 1 {\displaystyle F(E_{x}\geq 0)=1} {\displaystyle F(E_{x}\geq 0)=1}, the minimum possible functional information for a system is l o g 2 1 {\displaystyle -log_{2}1} {\displaystyle -log_{2}1}, which is zero.
  • for the highest possible level of a degree of function of a system E x = θ m a x {\displaystyle E_{x}=\theta _{max}} {\displaystyle E_{x}=\theta _{max}}, there will be a well defined I ( E x = θ m a x ) = l o g 2 F ( E x = θ m a x ) {\displaystyle I(E_{x}=\theta _{max})=-log_{2}F(E_{x}=\theta _{max})} {\displaystyle I(E_{x}=\theta _{max})=-log_{2}F(E_{x}=\theta _{max})}

Note that functional information of a system E {\displaystyle E} {\displaystyle E} must always be defined relative to a specific function x {\displaystyle x} {\displaystyle x}, without a choice of which it has no meaning.

Proposed law of increasing functional information

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This section needs expansion. You can help by adding to it. (April 2025)

In 2025, a group of researchers proposed a law of increasing functional information, that asserts that a tendency to increase in functional information is an inherent property of the universe, encompassing both biological and non-biological systems.[4] [5] [6]

References

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  1. ^ Ball, Philip (2025年04月02日). "Why Everything in the Universe Turns More Complex". Quanta Magazine. Retrieved 2025年04月14日.
  2. ^ Hazen, Robert M.; Griffin, Patrick L.; Carothers, James M.; Szostak, Jack W. (2007年05月15日). "Functional information and the emergence of biocomplexity". Proceedings of the National Academy of Sciences. 104 (suppl_1): 8574–8581. doi:10.1073/pnas.0701744104 . PMC 1876432 . PMID 17494745.
  3. ^ Adami, Christoph; C G, Nitash (2022年05月23日). "Emergence of functional information from multivariate correlations". Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. 380 (2227) 20210250. arXiv:2109.07933 . doi:10.1098/rsta.2021.0250. PMID 35599555.
  4. ^ Wong, Michael L.; Cleland, Carol E.; Arend, Daniel; Bartlett, Stuart; Cleaves, H. James; Demarest, Heather; Prabhu, Anirudh; Lunine, Jonathan I.; Hazen, Robert M. (2023年10月24日). "On the roles of function and selection in evolving systems". Proceedings of the National Academy of Sciences. 120 (43) e2310223120. Bibcode:2023PNAS..12010223W. doi:10.1073/pnas.2310223120 . PMC 10614609 . PMID 37844243.
  5. ^ Pester, Patrick (2023年10月21日). "Scientists propose 'missing' law for the evolution of everything in the universe". Space.com. Retrieved 2025年04月14日.
  6. ^ Dunham, Will (October 16, 2023). "Scientists propose sweeping new law of nature, expanding on evolution". Reuters. Retrieved 2025年04月15日.

See also

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