Measures of Degeneracy and Redundancy in Biological Networks.¶
Tononi, G., Sporns, O., & Edelman, G. M. (1999). Measures of Degeneracy and Redundancy in Biological Networks. Proceedings of the National Academy of Sciences, 96(6), 3257-3262.
Cited by¶
1 citation across 1 artifact.
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Primes¶
- Functional Redundancy (Degeneracy)
- Tononi, Sporns, and Edelman (1999) provide the information-theoretic measure that distinguishes degeneracy (high mutual information between subsets and the whole, but low among subsets themselves) from pure redundancy, arguing degeneracy is a universal biological property underlying both robustness and evolvability — degenerate systems can explore phenotypic variation without loss of function because multiple structural variants map to the same functional phenotype.
This sourceProvides the information-theoretic measure distinguishing degeneracy (high mutual information between subsets and the whole, low among subsets) from pure redundancy; directly supports the biology paragraph's claim of an information-theoretic degeneracy/redundancy distinction.
Supported in partVerified against the work's full text
Tononi, Sporns and Edelman build mutual-information measures that separate degeneracy from redundancy; they link degeneracy to robustness and adaptability, but do not call it universal or argue evolvability in detail.
“we develop here functional measures of the degeneracy and redundancy of a system with respect to a set of outputs. These measures help to distinguish the concept of degeneracy from that of redundancy”
- Tononi, Sporns, and Edelman (1999) provide the information-theoretic measure that distinguishes degeneracy (high mutual information between subsets and the whole, but low among subsets themselves) from pure redundancy, arguing degeneracy is a universal biological property underlying both robustness and evolvability — degenerate systems can explore phenotypic variation without loss of function because multiple structural variants map to the same functional phenotype.
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