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Phylogenomics databases for facilitating functional genomics in rice

Overview of attention for article published in Rice, July 2015
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Title
Phylogenomics databases for facilitating functional genomics in rice
Published in
Rice, July 2015
DOI 10.1186/s12284-015-0060-7
Pubmed ID
Authors

Ki-Hong Jung, Peijian Cao, Rita Sharma, Rashmi Jain, Pamela C Ronald

Abstract

The completion of whole genome sequence of rice (Oryza sativa) has significantly accelerated functional genomics studies. Prior to the release of the sequence, only a few genes were assigned a function each year. Since sequencing was completed in 2005, the rate has exponentially increased. As of 2014, 1,021 genes have been described and added to the collection at The Overview of functionally characterized Genes in Rice online database (OGRO). Despite this progress, that number is still very low compared with the total number of genes estimated in the rice genome. One limitation to progress is the presence of functional redundancy among members of the same rice gene family, which covers 51.6 % of all non-transposable element-encoding genes. There remain a significant portion or rice genes that are not functionally redundant, as reflected in the recovery of loss-of-function mutants. To more accurately analyze functional redundancy in the rice genome, we have developed a phylogenomics databases for six large gene families in rice, including those for glycosyltransferases, glycoside hydrolases, kinases, transcription factors, transporters, and cytochrome P450 monooxygenases. In this review, we introduce key features and applications of these databases. We expect that they will serve as a very useful guide in the post-genomics era of research.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Indonesia 1 3%
France 1 3%
India 1 3%
Benin 1 3%
Mexico 1 3%
Unknown 27 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 31%
Student > Ph. D. Student 7 22%
Student > Master 3 9%
Student > Doctoral Student 2 6%
Student > Bachelor 2 6%
Other 3 9%
Unknown 5 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 56%
Biochemistry, Genetics and Molecular Biology 7 22%
Economics, Econometrics and Finance 1 3%
Unknown 6 19%
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 25 August 2015.
All research outputs
#15,340,815
of 22,818,766 outputs
Outputs from Rice
#174
of 385 outputs
Outputs of similar age
#153,726
of 263,145 outputs
Outputs of similar age from Rice
#3
of 6 outputs
Altmetric has tracked 22,818,766 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 385 research outputs from this source. They receive a mean Attention Score of 3.8. This one is in the 41st percentile – i.e., 41% 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 263,145 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.