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Mendeley readers
Attention Score in Context
| Title |
rdml: A Mathematica package for parsing and importing Real-Time qPCR data
|
|---|---|
| Published in |
BMC Research Notes, June 2017
|
| DOI | 10.1186/s13104-017-2533-9 |
| Pubmed ID | |
| Authors |
Ramiro Magno, Isabel Duarte, Raquel P. Andrade, Isabel Palmeirim |
| Abstract |
The purpose and objective of the research presented is to provide a package for easy importing of Real-Time PCR data markup language (RDML) data to Mathematica. Real-Time qPCR is the most widely used experimental method for the accurate quantification of gene expression. To enable the straightforward archiving and sharing of qPCR data and its associated experimental information, an XML-based data standard was developed-the Real-Time PCR data markup language (RDML)-devised by the RDML consortium. Here, we present rdml, a package to parse and import RDML data into Mathematica, allowing the quick loading and extraction of relevant data, thus promoting the re-analysis, meta-analysis or experimental re-validation of gene expression data deposited in RDML format. |
Mendeley readers
The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 6 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 33% |
| Student > Bachelor | 1 | 17% |
| Researcher | 1 | 17% |
| Other | 1 | 17% |
| Unknown | 1 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 3 | 50% |
| Biochemistry, Genetics and Molecular Biology | 1 | 17% |
| Medicine and Dentistry | 1 | 17% |
| Unknown | 1 | 17% |
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 25 October 2023.
All research outputs
#8,237,225
of 24,676,547 outputs
Outputs from BMC Research Notes
#1,347
of 4,442 outputs
Outputs of similar age
#123,334
of 322,205 outputs
Outputs of similar age from BMC Research Notes
#32
of 99 outputs
Altmetric has tracked 24,676,547 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,442 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has gotten more attention than average, scoring higher than 63% 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 322,205 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 53% of its contemporaries.
We're also able to compare this research output to 99 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.