Três subsets de sequência de complexidade e sua relevância para informação biopolimérica

segunda-feira, maio 31, 2010

Theor Biol Med Model. 2005; 2: 29.
Published online 2005 August 11. doi: 10.1186/1742-4682-2-29.
PMCID: PMC1208958

Copyright © 2005 Abel and Trevors; licensee BioMed Central Ltd.

Three subsets of sequence complexity and their relevance to biopolymeric information

David L Abel1 and Jack T Trevors2

1Director, The Gene Emergence Project, The Origin-of-Life Foundation, Inc., 113 Hedgewood Dr., Greenbelt, MD 20770-1610 USA

2Professor, Department of Environmental Biology, University of Guelph, Rm 3220 Bovey Building, Guelph, Ontario, N1G 2W1, Canada

Corresponding author.

David L Abel:; Jack T Trevors:

Received May 23, 2005; Accepted August 11, 2005.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Genetic algorithms instruct sophisticated biological organization. Three qualitative kinds of sequence complexity exist: random (RSC), ordered (OSC), and functional (FSC). FSC alone provides algorithmic instruction. Random and Ordered Sequence Complexities lie at opposite ends of the same bi-directional sequence complexity vector. Randomness in sequence space is defined by a lack of Kolmogorov algorithmic compressibility. A sequence is compressible because it contains redundant order and patterns. Law-like cause-and-effect determinism produces highly compressible order. Such forced ordering precludes both information retention and freedom of selection so critical to algorithmic programming and control. Functional Sequence Complexity requires this added programming dimension of uncoerced selection at successive decision nodes in the string. Shannon information theory measures the relative degrees of RSC and OSC. Shannon information theory cannot measure FSC. FSC is invariably associated with all forms of complex biofunction, including biochemical pathways, cycles, positive and negative feedback regulation, and homeostatic metabolism. The algorithmic programming of FSC, not merely its aperiodicity, accounts for biological organization. No empirical evidence exists of either RSC of OSC ever having produced a single instance of sophisticated biological organization. Organization invariably manifests FSC rather than successive random events (RSC) or low-informational self-ordering phenomena (OSC).

Keywords: Self-organization, self-assembly, self-ordering, self-replication, genetic code origin, genetic information, self-catalysis.




Prestem muita, bastante atenção neste conceito -- Functional sequence complexity.

Ele vai dar muito o que falar em biologia evolutiva.