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Inference of the Xenopus tropicalis embryonic regulatory network and spatial gene expression patterns

Overview of attention for article published in BMC Systems Biology, January 2014
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Title
Inference of the Xenopus tropicalis embryonic regulatory network and spatial gene expression patterns
Published in
BMC Systems Biology, January 2014
DOI 10.1186/1752-0509-8-3
Pubmed ID
Authors

Zhenzhen Zheng, Scott Christley, William T Chiu, Ira L Blitz, Xiaohui Xie, Ken WY Cho, Qing Nie

Abstract

During embryogenesis, signaling molecules produced by one cell population direct gene regulatory changes in neighboring cells and influence their developmental fates and spatial organization. One of the earliest events in the development of the vertebrate embryo is the establishment of three germ layers, consisting of the ectoderm, mesoderm and endoderm. Attempts to measure gene expression in vivo in different germ layers and cell types are typically complicated by the heterogeneity of cell types within biological samples (i.e., embryos), as the responses of individual cell types are intermingled into an aggregate observation of heterogeneous cell types. Here, we propose a novel method to elucidate gene regulatory circuits from these aggregate measurements in embryos of the frog Xenopus tropicalis using gene network inference algorithms and then test the ability of the inferred networks to predict spatial gene expression patterns.

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X Demographics

The data shown below were collected from the profiles of 2 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 6%
Netherlands 1 3%
United Kingdom 1 3%
Unknown 27 87%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 32%
Researcher 5 16%
Student > Bachelor 3 10%
Professor > Associate Professor 3 10%
Student > Master 3 10%
Other 3 10%
Unknown 4 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 42%
Physics and Astronomy 3 10%
Computer Science 3 10%
Biochemistry, Genetics and Molecular Biology 2 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 5 16%
Unknown 4 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 09 January 2014.
All research outputs
#17,709,056
of 22,739,983 outputs
Outputs from BMC Systems Biology
#770
of 1,142 outputs
Outputs of similar age
#220,159
of 304,743 outputs
Outputs of similar age from BMC Systems Biology
#38
of 57 outputs
Altmetric has tracked 22,739,983 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
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 304,743 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 57 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.