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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Analysis of Global Gene Expression Profiles
|
|---|---|
| Chapter number | 11 |
| Book title |
Multiple Myeloma
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7865-6_11 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7864-9, 978-1-4939-7865-6
|
| Authors |
Alboukadel Kassambara, Jerome Moreaux, Kassambara, Alboukadel, Moreaux, Jerome |
| Abstract |
DNA microarrays have considerably helped to improve the understanding of biological processes and diseases including multiple myeloma (MM). GEP analyses have been successful to classify MM, define risk, identify therapeutic targets, predict treatment response, and understand drug resistance.This generated large amounts of publicly available data that could benefit from easy-to-use bioinformatics resources to analyze them. Here we present easy-to-use and open-access bioinformatics tools to extract and visualize the most prominent information from GEP data. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 4 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 2 | 50% |
| Student > Bachelor | 1 | 25% |
| Professor > Associate Professor | 1 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 2 | 50% |
| Agricultural and Biological Sciences | 1 | 25% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 30 May 2018.
All research outputs
#14,877,136
of 23,081,466 outputs
Outputs from Methods in molecular biology
#4,685
of 13,205 outputs
Outputs of similar age
#252,980
of 442,614 outputs
Outputs of similar age from Methods in molecular biology
#499
of 1,499 outputs
Altmetric has tracked 23,081,466 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,205 research outputs from this source. They receive a mean Attention Score of 3.4. This one has gotten more attention than average, scoring higher than 64% 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 442,614 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,499 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 66% of its contemporaries.