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X Demographics
Mendeley readers
Attention Score in Context
| Title |
New genes drive the evolution of gene interaction networks in the human and mouse genomes
|
|---|---|
| Published in |
Genome Biology, October 2015
|
| DOI | 10.1186/s13059-015-0772-4 |
| Pubmed ID | |
| Authors |
Wenyu Zhang, Patrick Landback, Andrea R. Gschwend, Bairong Shen, Manyuan Long |
| Abstract |
The origin of new genes with novel functions creates genetic and phenotypic diversity in organisms. To acquire functional roles, new genes must integrate into ancestral gene-gene interaction (GGI) networks. The mechanisms by which new genes are integrated into ancestral networks, and their evolutionary significance, are yet to be characterized. Herein, we present a study investigating the rates and patterns of new gene-driven evolution of GGI networks in the human and mouse genomes. We examine the network topological and functional evolution of new genes that originated at various stages in the human and mouse lineages by constructing and analyzing three different GGI datasets. We find a large number of new genes integrated into GGI networks throughout vertebrate evolution. These genes experienced a gradual integration process into GGI networks, starting on the network periphery and gradually becoming highly connected hubs, and acquiring pleiotropic and essential functions. We identify a few human lineage-specific hub genes that have evolved brain development-related functions. Finally, we explore the possible underlying mechanisms driving the GGI network evolution and the observed patterns of new gene integration process. Our results unveil a remarkable network topological integration process of new genes: over 5000 new genes were integrated into the ancestral GGI networks of human and mouse; new genes gradually acquire increasing number of gene partners; some human-specific genes evolved into hub structure with critical phenotypic effects. Our data cast new conceptual insights into the evolution of genetic networks. |
X Demographics
The data shown below were collected from the profiles of 21 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | 19% |
| Spain | 3 | 14% |
| Ireland | 2 | 10% |
| Finland | 2 | 10% |
| United Kingdom | 2 | 10% |
| Taiwan | 1 | 5% |
| Germany | 1 | 5% |
| France | 1 | 5% |
| Belgium | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 4 | 19% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 11 | 52% |
| Scientists | 8 | 38% |
| Science communicators (journalists, bloggers, editors) | 1 | 5% |
| Practitioners (doctors, other healthcare professionals) | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 108 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 3% |
| Germany | 2 | 2% |
| Switzerland | 1 | <1% |
| Norway | 1 | <1% |
| France | 1 | <1% |
| United Kingdom | 1 | <1% |
| India | 1 | <1% |
| Unknown | 98 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 25 | 23% |
| Student > Ph. D. Student | 23 | 21% |
| Student > Bachelor | 12 | 11% |
| Student > Master | 12 | 11% |
| Student > Doctoral Student | 6 | 6% |
| Other | 9 | 8% |
| Unknown | 21 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 44 | 41% |
| Biochemistry, Genetics and Molecular Biology | 26 | 24% |
| Computer Science | 7 | 6% |
| Mathematics | 3 | 3% |
| Medicine and Dentistry | 2 | 2% |
| Other | 5 | 5% |
| Unknown | 21 | 19% |
Attention Score in Context
This research output has an Altmetric Attention Score of 16. 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 27 October 2023.
All research outputs
#2,260,246
of 25,621,213 outputs
Outputs from Genome Biology
#1,860
of 4,495 outputs
Outputs of similar age
#30,317
of 287,433 outputs
Outputs of similar age from Genome Biology
#39
of 84 outputs
Altmetric has tracked 25,621,213 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,495 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one has gotten more attention than average, scoring higher than 58% 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 287,433 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 89% of its contemporaries.
We're also able to compare this research output to 84 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.