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Three subsets of sequence complexity and their relevance to biopolymeric information

Overview of attention for article published in Theoretical Biology and Medical Modelling, August 2005
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#26 of 287)
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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1 blog
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2 X users
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2 Facebook pages

Citations

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27 Dimensions

Readers on

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41 Mendeley
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1 CiteULike
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Title
Three subsets of sequence complexity and their relevance to biopolymeric information
Published in
Theoretical Biology and Medical Modelling, August 2005
DOI 10.1186/1742-4682-2-29
Pubmed ID
Authors

David L Abel, Jack T Trevors

Abstract

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).

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 4 10%
Mexico 2 5%
Israel 1 2%
Unknown 34 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 29%
Student > Ph. D. Student 7 17%
Student > Doctoral Student 5 12%
Other 3 7%
Professor > Associate Professor 2 5%
Other 6 15%
Unknown 6 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 37%
Chemistry 5 12%
Physics and Astronomy 2 5%
Social Sciences 2 5%
Computer Science 2 5%
Other 9 22%
Unknown 6 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 07 January 2022.
All research outputs
#2,214,530
of 22,831,537 outputs
Outputs from Theoretical Biology and Medical Modelling
#26
of 287 outputs
Outputs of similar age
#3,605
of 57,558 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#1
of 6 outputs
Altmetric has tracked 22,831,537 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 287 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 57,558 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them