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X Demographics
Mendeley readers
Attention Score in Context
| Title |
QueTAL: a suite of tools to classify and compare TAL effectors functionally and phylogenetically
|
|---|---|
| Published in |
Frontiers in Plant Science, August 2015
|
| DOI | 10.3389/fpls.2015.00545 |
| Pubmed ID | |
| Authors |
Alvaro L. Pérez-Quintero, Léo Lamy, Jonathan L. Gordon, Aline Escalon, Sébastien Cunnac, Boris Szurek, Lionel Gagnevin |
| Abstract |
Transcription Activator-Like (TAL) effectors from Xanthomonas plant pathogenic bacteria can bind to the promoter region of plant genes and induce their expression. DNA-binding specificity is governed by a central domain made of nearly identical repeats, each determining the recognition of one base pair via two amino acid residues (a.k.a. Repeat Variable Di-residue, or RVD). Knowing how TAL effectors differ from each other within and between strains would be useful to infer functional and evolutionary relationships, but their repetitive nature precludes reliable use of traditional alignment methods. The suite QueTAL was therefore developed to offer tailored tools for comparison of TAL effector genes. The program DisTAL considers each repeat as a unit, transforms a TAL effector sequence into a sequence of coded repeats and makes pair-wise alignments between these coded sequences to construct trees. The program FuncTAL is aimed at finding TAL effectors with similar DNA-binding capabilities. It calculates correlations between position weight matrices of potential target DNA sequence predicted from the RVD sequence, and builds trees based on these correlations. The programs accurately represented phylogenetic and functional relationships between TAL effectors using either simulated or literature-curated data. When using the programs on a large set of TAL effector sequences, the DisTAL tree largely reflected the expected species phylogeny. In contrast, FuncTAL showed that TAL effectors with similar binding capabilities can be found between phylogenetically distant taxa. This suite will help users to rapidly analyse any TAL effector genes of interest and compare them to other available TAL genes and should improve our understanding of TAL effectors evolution. It is available at http://bioinfo-web.mpl.ird.fr/cgi-bin2/quetal/quetal.cgi. |
X Demographics
The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 36% |
| France | 1 | 7% |
| India | 1 | 7% |
| Netherlands | 1 | 7% |
| United Kingdom | 1 | 7% |
| Unknown | 5 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 64% |
| Scientists | 4 | 29% |
| Science communicators (journalists, bloggers, editors) | 1 | 7% |
Mendeley readers
The data shown below were compiled from readership statistics for 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 2 | 4% |
| Germany | 1 | 2% |
| Brazil | 1 | 2% |
| Unknown | 48 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 17% |
| Student > Master | 8 | 15% |
| Student > Bachelor | 7 | 13% |
| Researcher | 7 | 13% |
| Student > Doctoral Student | 3 | 6% |
| Other | 5 | 10% |
| Unknown | 13 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 26 | 50% |
| Biochemistry, Genetics and Molecular Biology | 5 | 10% |
| Engineering | 2 | 4% |
| Computer Science | 1 | 2% |
| Unspecified | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 17 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 21 July 2016.
All research outputs
#4,431,657
of 22,818,766 outputs
Outputs from Frontiers in Plant Science
#2,297
of 20,118 outputs
Outputs of similar age
#55,980
of 263,982 outputs
Outputs of similar age from Frontiers in Plant Science
#17
of 285 outputs
Altmetric has tracked 22,818,766 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 20,118 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 88% 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 263,982 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 78% of its contemporaries.
We're also able to compare this research output to 285 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.