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The RecA protein as a model molecule for molecular systematic studies of bacteria: Comparison of trees of RecAs and 16S rRNAs from the same species

Overview of attention for article published in Journal of Molecular Evolution, December 1995
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

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14 X users
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1 Facebook page
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2 Wikipedia pages

Citations

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121 Mendeley
Title
The RecA protein as a model molecule for molecular systematic studies of bacteria: Comparison of trees of RecAs and 16S rRNAs from the same species
Published in
Journal of Molecular Evolution, December 1995
DOI 10.1007/bf00173192
Pubmed ID
Authors

Jonathan A. Eisen

Abstract

The evolution of the RecA protein was analyzed using molecular phylogenetic techniques. Phylogenetic trees of all currently available complete RecA proteins were inferred using multiple maximum parsimony and distance matrix methods. Comparison and analysis of the trees reveal that the inferred relationships among these proteins are highly robust. The RecA trees show consistent subdivisions corresponding to many of the major bacterial groups found in trees of other molecules including the alpha, beta, gamma, delta, epsilon proteobacteria, cyanobacteria, high-GC gram-positives, and the Deinococcus-Thermus group. However, there are interesting differences between the RecA trees and these other trees. For example, in all the RecA trees the proteins from gram-positive species are not monophyletic. In addition, the RecAs of the cyanobacteria consistently group with those of the high-GC gram-positives. To evaluate possible causes and implications of these and other differences phylogenetic trees were generated for small-subunit rRNA sequences from the same (or closely related) species as represented in the RecA analysis. The trees of the two molecules using these equivalent species-sets are highly congruent and have similar resolving power for close, medium, and deep branches in the history of bacteria. The implications of the particular similarities and differences between the trees are discussed. Some of the features that make RecA useful for molecular systematics and for studies of protein evolution are also discussed.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 121 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 2%
Germany 2 2%
Canada 2 2%
Australia 1 <1%
Sweden 1 <1%
South Africa 1 <1%
Malaysia 1 <1%
Tunisia 1 <1%
Indonesia 1 <1%
Other 2 2%
Unknown 106 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 28%
Researcher 19 16%
Student > Master 13 11%
Professor > Associate Professor 11 9%
Student > Bachelor 7 6%
Other 19 16%
Unknown 18 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 63 52%
Biochemistry, Genetics and Molecular Biology 18 15%
Environmental Science 6 5%
Computer Science 3 2%
Earth and Planetary Sciences 3 2%
Other 9 7%
Unknown 19 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10. 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 10 April 2023.
All research outputs
#3,623,052
of 25,452,734 outputs
Outputs from Journal of Molecular Evolution
#155
of 1,480 outputs
Outputs of similar age
#3,600
of 79,940 outputs
Outputs of similar age from Journal of Molecular Evolution
#3
of 27 outputs
Altmetric has tracked 25,452,734 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,480 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.9. This one has done well, scoring higher than 89% 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 79,940 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 95% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.