↓ Skip to main content

Digital gene expression approach over multiple RNA-Seq data sets to detect neoblast transcriptional changes in Schmidtea mediterranea

Overview of attention for article published in BMC Genomics, May 2015
Altmetric Badge

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 (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

blogs
1 blog
twitter
5 X users
facebook
1 Facebook page

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
56 Mendeley
citeulike
1 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Digital gene expression approach over multiple RNA-Seq data sets to detect neoblast transcriptional changes in Schmidtea mediterranea
Published in
BMC Genomics, May 2015
DOI 10.1186/s12864-015-1533-1
Pubmed ID
Authors

Gustavo Rodríguez-Esteban, Alejandro González-Sastre, José Ignacio Rojo-Laguna, Emili Saló, Josep F Abril

Abstract

The freshwater planarian Schmidtea mediterranea is recognised as a valuable model for research into adult stem cells and regeneration. With the advent of the high-throughput sequencing technologies, it has become feasible to undertake detailed transcriptional analysis of its unique stem cell population, the neoblasts. Nonetheless, a reliable reference for this type of studies is still lacking. Taking advantage of digital gene expression (DGE) sequencing technology we compare all the available transcriptomes for S. mediterranea and improve their annotation. These results are accessible via web for the community of researchers. Using the quantitative nature of DGE, we describe the transcriptional profile of neoblasts and present 42 new neoblast genes, including several cancer-related genes and transcription factors. Furthermore, we describe in detail the Smed-meis-like gene and the three Nuclear Factor Y subunits Smed-nf-YA, Smed-nf-YB-2 and Smed-nf-YC. DGE is a valuable tool for gene discovery, quantification and annotation. The application of DGE in S. mediterranea confirms the planarian stem cells or neoblasts as a complex population of pluripotent and multipotent cells regulated by a mixture of transcription factors and cancer-related genes.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 2 4%
United States 2 4%
Czechia 1 2%
Unknown 51 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 30%
Other 6 11%
Student > Bachelor 5 9%
Student > Master 5 9%
Student > Doctoral Student 4 7%
Other 12 21%
Unknown 7 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 21 38%
Agricultural and Biological Sciences 20 36%
Mathematics 2 4%
Environmental Science 1 2%
Economics, Econometrics and Finance 1 2%
Other 2 4%
Unknown 9 16%
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 14 February 2016.
All research outputs
#3,552,846
of 22,803,211 outputs
Outputs from BMC Genomics
#1,332
of 10,649 outputs
Outputs of similar age
#46,194
of 264,548 outputs
Outputs of similar age from BMC Genomics
#38
of 264 outputs
Altmetric has tracked 22,803,211 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 10,649 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 87% 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 264,548 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 82% of its contemporaries.
We're also able to compare this research output to 264 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.