↓ Skip to main content

NexGenEx-Tom: a gene expression platform to investigate the functionalities of the tomato genome

Overview of attention for article published in BMC Plant Biology, January 2015
Altmetric Badge

About this Attention Score

  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • Good Attention Score compared to outputs of the same age and source (76th percentile)

Mentioned by

twitter
6 X users

Citations

dimensions_citation
16 Dimensions

Readers on

mendeley
46 Mendeley
citeulike
3 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
NexGenEx-Tom: a gene expression platform to investigate the functionalities of the tomato genome
Published in
BMC Plant Biology, January 2015
DOI 10.1186/s12870-014-0412-2
Pubmed ID
Authors

Hamed Bostan, Maria Chiusano

Abstract

Next Generation Sequencing technologies (NGS) unexpectedly pushed forward the capability of solving genome organization and of widely depicting gene expression. However, although the flourishing of tools to process the NGS data, versatile and user-friendly computational environments for integrative and comparative analyses of the results from the increasing amount of collections are still required. The gene expression of tomato tissues has been widely investigated in the years, thanks to both EST sequencing and different microarray platforms. However, the resulting collections are heterogeneous in terms of experimental approaches, genotypes and conditions, making the data far from representing a gene expression atlas for the species. Therefore, the recent release of NGS transcriptome collections from several tissues and stages from physiological conditions for specific tomato genotypes provides a relevant resource to be appropriately exploited to address key questions on gene expression patterns, such as those related to fruit ripening and development in tomato. The organization of the results from the processed collections in web accessible environments, enriched with tools for their exploration, may represent a precious opportunity for the scientific research in tomato and a reference example for similar efforts.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Greece 1 2%
France 1 2%
Unknown 43 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 35%
Student > Doctoral Student 7 15%
Student > Ph. D. Student 7 15%
Student > Bachelor 2 4%
Professor > Associate Professor 2 4%
Other 4 9%
Unknown 8 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 59%
Computer Science 3 7%
Engineering 3 7%
Biochemistry, Genetics and Molecular Biology 2 4%
Medicine and Dentistry 1 2%
Other 1 2%
Unknown 9 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 April 2015.
All research outputs
#7,284,512
of 23,881,329 outputs
Outputs from BMC Plant Biology
#566
of 3,322 outputs
Outputs of similar age
#97,248
of 358,086 outputs
Outputs of similar age from BMC Plant Biology
#27
of 112 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 3,322 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done well, scoring higher than 83% 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 358,086 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.
We're also able to compare this research output to 112 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 76% of its contemporaries.