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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Leveraging the new with the old: providing a framework for the integration of historic microarray studies with next generation sequencing
|
|---|---|
| Published in |
BMC Bioinformatics, October 2014
|
| DOI | 10.1186/1471-2105-15-s11-s3 |
| Pubmed ID | |
| Authors |
Michael A Bauer, Shweta S Chavan, Erich A Peterson, Christoph J Heuck, Donald J Johann |
| Abstract |
Next Generation Sequencing (NGS) methods are rapidly providing remarkable advances in our ability to study the molecular profiles of human cancers. However, the scientific discovery offered by NGS also includes challenges concerning the interpretation of large and non-trivial experimental results. This task is potentially further complicated when a multitude of molecular profiling modalities are available, with the goal of a more integrative and comprehensive analysis of the cancer biology. |
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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 15 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 27% |
| Student > Bachelor | 3 | 20% |
| Other | 2 | 13% |
| Student > Doctoral Student | 2 | 13% |
| Student > Ph. D. Student | 2 | 13% |
| Other | 2 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 27% |
| Computer Science | 3 | 20% |
| Agricultural and Biological Sciences | 1 | 7% |
| Biochemistry, Genetics and Molecular Biology | 1 | 7% |
| Mathematics | 1 | 7% |
| Other | 1 | 7% |
| Unknown | 4 | 27% |
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 29 October 2014.
All research outputs
#20,241,019
of 22,768,097 outputs
Outputs from BMC Bioinformatics
#6,845
of 7,273 outputs
Outputs of similar age
#216,605
of 259,770 outputs
Outputs of similar age from BMC Bioinformatics
#121
of 132 outputs
Altmetric has tracked 22,768,097 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 7,273 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. 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 259,770 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 132 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.