| Title |
Normalization and integration of large-scale metabolomics data using support vector regression
|
|---|---|
| Published in |
Metabolomics, March 2016
|
| DOI | 10.1007/s11306-016-1026-5 |
| Authors |
Xiaotao Shen, Xiaoyun Gong, Yuping Cai, Yuan Guo, Jia Tu, Hao Li, Tao Zhang, Jialin Wang, Fuzhong Xue, Zheng-Jiang Zhu |
X Demographics
The data shown below were collected from the profiles of 6 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 | 1 | 17% |
| Unknown | 5 | 83% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 50% |
| Scientists | 2 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 178 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | <1% |
| South Africa | 1 | <1% |
| India | 1 | <1% |
| China | 1 | <1% |
| Spain | 1 | <1% |
| Unknown | 173 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 51 | 29% |
| Researcher | 36 | 20% |
| Student > Master | 19 | 11% |
| Student > Bachelor | 10 | 6% |
| Student > Doctoral Student | 8 | 4% |
| Other | 19 | 11% |
| Unknown | 35 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 36 | 20% |
| Biochemistry, Genetics and Molecular Biology | 28 | 16% |
| Chemistry | 25 | 14% |
| Pharmacology, Toxicology and Pharmaceutical Science | 9 | 5% |
| Medicine and Dentistry | 8 | 4% |
| Other | 29 | 16% |
| Unknown | 43 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 14 September 2016.
All research outputs
#7,165,128
of 22,858,915 outputs
Outputs from Metabolomics
#446
of 1,295 outputs
Outputs of similar age
#102,297
of 300,768 outputs
Outputs of similar age from Metabolomics
#16
of 47 outputs
Altmetric has tracked 22,858,915 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 1,295 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 65% 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 300,768 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 65% of its contemporaries.
We're also able to compare this research output to 47 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 65% of its contemporaries.