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Pepper EST database: comprehensive in silico tool for analyzing the chili pepper (Capsicum annuum) transcriptome

Overview of attention for article published in BMC Plant Biology, October 2008
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)

Mentioned by

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1 patent

Citations

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52 Dimensions

Readers on

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79 Mendeley
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3 CiteULike
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1 Connotea
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Title
Pepper EST database: comprehensive in silico tool for analyzing the chili pepper (Capsicum annuum) transcriptome
Published in
BMC Plant Biology, October 2008
DOI 10.1186/1471-2229-8-101
Pubmed ID
Authors

Hyun-Jin Kim, Kwang-Hyun Baek, Seung-Won Lee, JungEun Kim, Bong-Woo Lee, Hye-Sun Cho, Woo Taek Kim, Doil Choi, Cheol-Goo Hur

Abstract

There is no dedicated database available for Expressed Sequence Tags (EST) of the chili pepper (Capsicum annuum), although the interest in a chili pepper EST database is increasing internationally due to the nutritional, economic, and pharmaceutical value of the plant. Recent advances in high-throughput sequencing of the ESTs of chili pepper cv. Bukang have produced hundreds of thousands of complementary DNA (cDNA) sequences. Therefore, a chili pepper EST database was designed and constructed to enable comprehensive analysis of chili pepper gene expression in response to biotic and abiotic stresses. We built the Pepper EST database to mine the complexity of chili pepper ESTs. The database was built on 122,582 sequenced ESTs and 116,412 refined ESTs from 21 pepper EST libraries. The ESTs were clustered and assembled into virtual consensus cDNAs and the cDNAs were assigned to metabolic pathway, Gene Ontology (GO), and MIPS Functional Catalogue (FunCat). The Pepper EST database is designed to provide a workbench for (i) identifying unigenes in pepper plants, (ii) analyzing expression patterns in different developmental tissues and under conditions of stress, and (iii) comparing the ESTs with those of other members of the Solanaceae family. The Pepper EST database is freely available at http://genepool.kribb.re.kr/pepper/. The Pepper EST database is expected to provide a high-quality resource, which will contribute to gaining a systemic understanding of plant diseases and facilitate genetics-based population studies. The database is also expected to contribute to analysis of gene synteny as part of the chili pepper sequencing project by mapping ESTs to the genome.

Mendeley readers

The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 3 4%
Spain 2 3%
Norway 1 1%
Brazil 1 1%
Indonesia 1 1%
South Africa 1 1%
Malaysia 1 1%
Japan 1 1%
United States 1 1%
Other 0 0%
Unknown 67 85%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 22%
Student > Master 12 15%
Researcher 11 14%
Professor > Associate Professor 9 11%
Student > Bachelor 7 9%
Other 14 18%
Unknown 9 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 47 59%
Biochemistry, Genetics and Molecular Biology 11 14%
Engineering 4 5%
Computer Science 3 4%
Medicine and Dentistry 1 1%
Other 1 1%
Unknown 12 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 26 August 2010.
All research outputs
#6,070,419
of 18,726,290 outputs
Outputs from BMC Plant Biology
#546
of 2,668 outputs
Outputs of similar age
#79,863
of 239,464 outputs
Outputs of similar age from BMC Plant Biology
#1
of 1 outputs
Altmetric has tracked 18,726,290 research outputs across all sources so far. This one is in the 46th percentile – i.e., 46% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,668 research outputs from this source. They receive a mean Attention Score of 3.1. This one has gotten more attention than average, scoring higher than 74% 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 239,464 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 60% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them