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Evolutionary Genomics

Overview of attention for book
Cover of 'Evolutionary Genomics'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Tangled Trees: The Challenge of Inferring Species Trees from Coalescent and Noncoalescent Genes
  3. Altmetric Badge
    Chapter 2 Modeling Gene Family Evolution and Reconciling Phylogenetic Discord
  4. Altmetric Badge
    Chapter 3 Genome-wide comparative analysis of phylogenetic trees: the prokaryotic forest of life.
  5. Altmetric Badge
    Chapter 4 Philosophy and Evolution: Minding the Gap Between Evolutionary Patterns and Tree-Like Patterns
  6. Altmetric Badge
    Chapter 5 Selection on the Protein-Coding Genome
  7. Altmetric Badge
    Chapter 6 Methods to Detect Selection on Noncoding DNA
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    Chapter 7 The Origin and Evolution of New Genes
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    Chapter 8 Evolution of protein domain architectures.
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    Chapter 9 Estimating recombination rates from genetic variation in humans.
  11. Altmetric Badge
    Chapter 10 Evolution of Viral Genomes: Interplay Between Selection, Recombination, and Other Forces
  12. Altmetric Badge
    Chapter 11 Association Mapping and Disease: Evolutionary Perspectives
  13. Altmetric Badge
    Chapter 12 Ancestral Population Genomics
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    Chapter 13 Nonredundant Representation of Ancestral Recombinations Graphs
  15. Altmetric Badge
    Chapter 14 Using Genomic Tools to Study Regulatory Evolution
  16. Altmetric Badge
    Chapter 15 Characterization and Evolutionary Analysis of Protein–Protein Interaction Networks
  17. Altmetric Badge
    Chapter 16 Statistical methods in metabolomics.
  18. Altmetric Badge
    Chapter 17 Introduction to the Analysis of Environmental Sequences: Metagenomics with MEGAN
  19. Altmetric Badge
    Chapter 18 Analyzing epigenome data in context of genome evolution and human diseases.
  20. Altmetric Badge
    Chapter 19 Genetical Genomics for Evolutionary Studies
  21. Altmetric Badge
    Chapter 20 Genomics Data Resources: Frameworks and Standards
  22. Altmetric Badge
    Chapter 21 Sharing programming resources between bio* projects through remote procedure call and native call stack strategies.
  23. Altmetric Badge
    Chapter 22 Scalable computing for evolutionary genomics.
Attention for Chapter 3: Genome-wide comparative analysis of phylogenetic trees: the prokaryotic forest of life.
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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 (85th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

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25 Mendeley
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Chapter title
Genome-wide comparative analysis of phylogenetic trees: the prokaryotic forest of life.
Chapter number 3
Book title
Evolutionary Genomics
Published in
Methods in molecular biology, March 2012
DOI 10.1007/978-1-61779-585-5_3
Pubmed ID
Book ISBNs
978-1-61779-584-8, 978-1-61779-585-5
Authors

Puigbò P, Wolf YI, Koonin EV, Pere Puigbò, Yuri I. Wolf, Eugene V. Koonin, Puigbò, Pere, Wolf, Yuri I., Koonin, Eugene V.

Abstract

Genome-wide comparison of phylogenetic trees is becoming an increasingly common approach in evolutionary genomics, and a variety of approaches for such comparison have been developed. In this article, we present several methods for comparative analysis of large numbers of phylogenetic trees. To compare phylogenetic trees taking into account the bootstrap support for each internal branch, the Boot-Split Distance (BSD) method is introduced as an extension of the previously developed Split Distance method for tree comparison. The BSD method implements the straightforward idea that comparison of phylogenetic trees can be made more robust by treating tree splits differentially depending on the bootstrap support. Approaches are also introduced for detecting tree-like and net-like evolutionary trends in the phylogenetic Forest of Life (FOL), i.e., the entirety of the phylogenetic trees for conserved genes of prokaryotes. The principal method employed for this purpose includes mapping quartets of species onto trees to calculate the support of each quartet topology and so to quantify the tree and net contributions to the distances between species. We describe the application of these methods to analyze the FOL and the results obtained with these methods. These results support the concept of the Tree of Life (TOL) as a central evolutionary trend in the FOL as opposed to the traditional view of the TOL as a "species tree."

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 25 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 1 4%
Unknown 24 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 44%
Student > Master 3 12%
Student > Bachelor 2 8%
Professor 2 8%
Student > Ph. D. Student 1 4%
Other 1 4%
Unknown 5 20%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 44%
Biochemistry, Genetics and Molecular Biology 4 16%
Environmental Science 1 4%
Mathematics 1 4%
Immunology and Microbiology 1 4%
Other 0 0%
Unknown 7 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 08 December 2014.
All research outputs
#3,269,905
of 22,772,779 outputs
Outputs from Methods in molecular biology
#800
of 13,090 outputs
Outputs of similar age
#20,965
of 156,658 outputs
Outputs of similar age from Methods in molecular biology
#6
of 66 outputs
Altmetric has tracked 22,772,779 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,090 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 93% 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 156,658 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 66 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 90% of its contemporaries.