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Phylogenomics resolves the timing and pattern of insect evolution

Overview of attention for article published in Science, November 2014
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Citations

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2097 Dimensions

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1844 Mendeley
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3 CiteULike
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Title
Phylogenomics resolves the timing and pattern of insect evolution
Published in
Science, November 2014
DOI 10.1126/science.1257570
Pubmed ID
Authors

Bernhard Misof, Shanlin Liu, Karen Meusemann, Ralph S Peters, Alexander Donath, Christoph Mayer, Paul B Frandsen, Jessica Ware, Tomáš Flouri, Rolf G Beutel, Oliver Niehuis, Malte Petersen, Fernando Izquierdo-Carrasco, Torsten Wappler, Jes Rust, Andre J Aberer, Ulrike Aspöck, Horst Aspöck, Daniela Bartel, Alexander Blanke, Simon Berger, Alexander Böhm, Thomas R Buckley, Brett Calcott, Junqing Chen, Frank Friedrich, Makiko Fukui, Mari Fujita, Carola Greve, Peter Grobe, Shengchang Gu, Ying Huang, Lars S Jermiin, Akito Y Kawahara, Lars Krogmann, Martin Kubiak, Robert Lanfear, Harald Letsch, Yiyuan Li, Zhenyu Li, Jiguang Li, Haorong Lu, Ryuichiro Machida, Yuta Mashimo, Pashalia Kapli, Duane D McKenna, Guanliang Meng, Yasutaka Nakagaki, José Luis Navarrete-Heredia, Michael Ott, Yanxiang Ou, Günther Pass, Lars Podsiadlowski, Hans Pohl, Björn M von Reumont, Kai Schütte, Kaoru Sekiya, Shota Shimizu, Adam Slipinski, Alexandros Stamatakis, Wenhui Song, Xu Su, Nikolaus U Szucsich, Meihua Tan, Xuemei Tan, Min Tang, Jingbo Tang, Gerald Timelthaler, Shigekazu Tomizuka, Michelle Trautwein, Xiaoli Tong, Toshiki Uchifune, Manfred G Walzl, Brian M Wiegmann, Jeanne Wilbrandt, Benjamin Wipfler, Thomas K F Wong, Qiong Wu, Gengxiong Wu, Yinlong Xie, Shenzhou Yang, Qing Yang, David K Yeates, Kazunori Yoshizawa, Qing Zhang, Rui Zhang, Wenwei Zhang, Yunhui Zhang, Jing Zhao, Chengran Zhou, Lili Zhou, Tanja Ziesmann, Shijie Zou, Yingrui Li, Xun Xu, Yong Zhang, Huanming Yang, Jian Wang, Jun Wang, Karl M Kjer, Xin Zhou

Abstract

Insects are the most speciose group of animals, but the phylogenetic relationships of many major lineages remain unresolved. We inferred the phylogeny of insects from 1478 protein-coding genes. Phylogenomic analyses of nucleotide and amino acid sequences, with site-specific nucleotide or domain-specific amino acid substitution models, produced statistically robust and congruent results resolving previously controversial phylogenetic relations hips. We dated the origin of insects to the Early Ordovician [~479 million years ago (Ma)], of insect flight to the Early Devonian (~406 Ma), of major extant lineages to the Mississippian (~345 Ma), and the major diversification of holometabolous insects to the Early Cretaceous. Our phylogenomic study provides a comprehensive reliable scaffold for future comparative analyses of evolutionary innovations among insects.

X Demographics

X Demographics

The data shown below were collected from the profiles of 398 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 1,844 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 28 2%
Brazil 20 1%
Germany 19 1%
Canada 6 <1%
France 5 <1%
United Kingdom 5 <1%
Japan 4 <1%
Sweden 3 <1%
South Africa 2 <1%
Other 22 1%
Unknown 1730 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 355 19%
Researcher 322 17%
Student > Bachelor 234 13%
Student > Master 233 13%
Professor > Associate Professor 89 5%
Other 312 17%
Unknown 299 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 1002 54%
Biochemistry, Genetics and Molecular Biology 232 13%
Environmental Science 91 5%
Earth and Planetary Sciences 25 1%
Computer Science 21 1%
Other 116 6%
Unknown 357 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 747. 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 31 January 2024.
All research outputs
#26,971
of 25,736,439 outputs
Outputs from Science
#1,206
of 83,267 outputs
Outputs of similar age
#173
of 277,179 outputs
Outputs of similar age from Science
#11
of 876 outputs
Altmetric has tracked 25,736,439 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 83,267 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 65.9. This one has done particularly well, scoring higher than 98% 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 277,179 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 99% of its contemporaries.
We're also able to compare this research output to 876 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 98% of its contemporaries.