The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Mendeley readers
Attention Score in Context
| Title |
D-MaPs - DNA-microarray projects: web-based software for multi-platform microarray analysis
|
|---|---|
| Published in |
Genetics and Molecular Biology, September 2009
|
| DOI | 10.1590/s1415-47572009000300030 |
| Pubmed ID | |
| Authors |
Marcelo F. Carazzolle, Taís S. Herig, Ana C. Deckmann, Gonçalo A.G. Pereira |
| Abstract |
The web application D-Maps provides a user-friendly interface to researchers performing studies based on microarrays. The program was developed to manage and process one- or two-color microarray data obtained from several platforms (currently, GeneTAC, ScanArray, CodeLink, NimbleGen and Affymetrix). Despite the availability of many algorithms and many software programs designed to perform microarray analysis on the internet, these usually require sophisticated knowledge of mathematics, statistics and computation. D-maps was developed to overcome the requirement of high performance computers or programming experience. D-Maps performs raw data processing, normalization and statistical analysis, allowing access to the analyzed data in text or graphical format. An original feature presented by D-Maps is GEO (Gene Expression Omnibus) submission format service. The D-MaPs application was already used for analysis of oligonucleotide microarrays and PCR-spotted arrays (one- and two-color, laser and light scanner). In conclusion, D-Maps is a valuable tool for microarray research community, especially in the case of groups without a bioinformatic core. |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 2 | 9% |
| Colombia | 1 | 5% |
| Unknown | 19 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 6 | 27% |
| Researcher | 4 | 18% |
| Student > Ph. D. Student | 4 | 18% |
| Professor | 2 | 9% |
| Professor > Associate Professor | 2 | 9% |
| Other | 3 | 14% |
| Unknown | 1 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 36% |
| Engineering | 4 | 18% |
| Biochemistry, Genetics and Molecular Biology | 3 | 14% |
| Unspecified | 1 | 5% |
| Environmental Science | 1 | 5% |
| Other | 3 | 14% |
| Unknown | 2 | 9% |
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 October 2014.
All research outputs
#22,758,309
of 25,373,627 outputs
Outputs from Genetics and Molecular Biology
#647
of 771 outputs
Outputs of similar age
#98,220
of 102,312 outputs
Outputs of similar age from Genetics and Molecular Biology
#2
of 2 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 771 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.