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Mendeley readers
Attention Score in Context
| Title |
Correction to: Genome-wide discovery and characterization of maize long non-coding RNAs
|
|---|---|
| Published in |
Genome Biology, August 2018
|
| DOI | 10.1186/s13059-018-1508-z |
| Pubmed ID | |
| Authors |
Lin Li, Steven R. Eichten, Rena Shimizu, Katherine Petsch, Cheng-Ting Yeh, Wei Wu, Antony M. Chettoor, Scott A. Givan, Rex A. Cole, John E. Fowler, Matthew M. S. Evans, Michael J. Scanlon, Jianming Yu, Patrick S. Schnable, Marja C. P. Timmermans, Nathan M. Springer, Gary J. Muehlbauer |
| Abstract |
The original version [1] of this article unfortunately contained a mistake. The additive effects of the eQTLs of lncRNAs were flipped, meaning that the base allele in the contrast to derive the additive effects should have been B73, rather than Mo17, due to the original coding of biallele SNPs as "0s" and "1s". Going through the entire analysis procedure, it was determined that the mistake was made while tabulating the eQTL results from QTL Cartographer. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 10 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 3 | 30% |
| Unspecified | 2 | 20% |
| Student > Master | 1 | 10% |
| Student > Postgraduate | 1 | 10% |
| Student > Doctoral Student | 1 | 10% |
| Other | 0 | 0% |
| Unknown | 2 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 50% |
| Unspecified | 2 | 20% |
| Biochemistry, Genetics and Molecular Biology | 1 | 10% |
| Unknown | 2 | 20% |
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 24 August 2018.
All research outputs
#20,663,600
of 25,385,509 outputs
Outputs from Genome Biology
#4,271
of 4,468 outputs
Outputs of similar age
#266,386
of 342,525 outputs
Outputs of similar age from Genome Biology
#73
of 73 outputs
Altmetric has tracked 25,385,509 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,468 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 1st percentile – i.e., 1% 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 342,525 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 73 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.