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X Demographics
Mendeley readers
Attention Score in Context
| Title |
The characteristic direction: a geometrical approach to identify differentially expressed genes
|
|---|---|
| Published in |
BMC Bioinformatics, March 2014
|
| DOI | 10.1186/1471-2105-15-79 |
| Pubmed ID | |
| Authors |
Neil R Clark, Kevin S Hu, Axel S Feldmann, Yan Kou, Edward Y Chen, Qiaonan Duan, Avi Ma’ayan |
| Abstract |
Identifying differentially expressed genes (DEG) is a fundamental step in studies that perform genome wide expression profiling. Typically, DEG are identified by univariate approaches such as Significance Analysis of Microarrays (SAM) or Linear Models for Microarray Data (LIMMA) for processing cDNA microarrays, and differential gene expression analysis based on the negative binomial distribution (DESeq) or Empirical analysis of Digital Gene Expression data in R (edgeR) for RNA-seq profiling. |
X Demographics
The data shown below were collected from the profiles of 23 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 9 | 39% |
| France | 3 | 13% |
| Norway | 1 | 4% |
| Mexico | 1 | 4% |
| Japan | 1 | 4% |
| Sweden | 1 | 4% |
| India | 1 | 4% |
| Unknown | 6 | 26% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 13 | 57% |
| Scientists | 10 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 369 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 13 | 4% |
| United Kingdom | 3 | <1% |
| France | 3 | <1% |
| Netherlands | 2 | <1% |
| Portugal | 2 | <1% |
| Austria | 1 | <1% |
| Australia | 1 | <1% |
| Italy | 1 | <1% |
| Germany | 1 | <1% |
| Other | 7 | 2% |
| Unknown | 335 | 91% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 94 | 25% |
| Student > Ph. D. Student | 93 | 25% |
| Student > Master | 35 | 9% |
| Student > Bachelor | 28 | 8% |
| Student > Postgraduate | 19 | 5% |
| Other | 56 | 15% |
| Unknown | 44 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 130 | 35% |
| Biochemistry, Genetics and Molecular Biology | 68 | 18% |
| Computer Science | 32 | 9% |
| Medicine and Dentistry | 31 | 8% |
| Engineering | 11 | 3% |
| Other | 44 | 12% |
| Unknown | 53 | 14% |
Attention Score in Context
This research output has an Altmetric Attention Score of 24. 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 16 December 2020.
All research outputs
#1,431,128
of 23,873,054 outputs
Outputs from BMC Bioinformatics
#224
of 7,482 outputs
Outputs of similar age
#14,669
of 226,718 outputs
Outputs of similar age from BMC Bioinformatics
#6
of 97 outputs
Altmetric has tracked 23,873,054 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,482 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 97% 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 226,718 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 97 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.