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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Nonnegative principal component analysis for mass spectral serum profiles and biomarker discovery
|
|---|---|
| Published in |
BMC Bioinformatics, January 2010
|
| DOI | 10.1186/1471-2105-11-s1-s1 |
| Pubmed ID | |
| Authors |
Henry Han |
| Abstract |
As a novel cancer diagnostic paradigm, mass spectroscopic serum proteomic pattern diagnostics was reported superior to the conventional serologic cancer biomarkers. However, its clinical use is not fully validated yet. An important factor to prevent this young technology to become a mainstream cancer diagnostic paradigm is that robustly identifying cancer molecular patterns from high-dimensional protein expression data is still a challenge in machine learning and oncology research. As a well-established dimension reduction technique, PCA is widely integrated in pattern recognition analysis to discover cancer molecular patterns. However, its global feature selection mechanism prevents it from capturing local features. This may lead to difficulty in achieving high-performance proteomic pattern discovery, because only features interpreting global data behavior are used to train a learning machine. |
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 % |
|---|---|---|
| United States | 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 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 3% |
| Turkey | 1 | 3% |
| India | 1 | 3% |
| Belgium | 1 | 3% |
| Unknown | 28 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 25% |
| Student > Doctoral Student | 5 | 16% |
| Student > Ph. D. Student | 5 | 16% |
| Student > Bachelor | 2 | 6% |
| Student > Master | 2 | 6% |
| Other | 3 | 9% |
| Unknown | 7 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 25% |
| Computer Science | 4 | 13% |
| Biochemistry, Genetics and Molecular Biology | 2 | 6% |
| Mathematics | 2 | 6% |
| Engineering | 2 | 6% |
| Other | 6 | 19% |
| Unknown | 8 | 25% |
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 06 December 2014.
All research outputs
#15,311,799
of 22,772,779 outputs
Outputs from BMC Bioinformatics
#5,373
of 7,276 outputs
Outputs of similar age
#134,180
of 164,184 outputs
Outputs of similar age from BMC Bioinformatics
#35
of 58 outputs
Altmetric has tracked 22,772,779 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,276 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 18th percentile – i.e., 18% 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 164,184 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 58 others from the same source and published within six weeks on either side of this one. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.