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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Significance of bioinformatics in research of chronic obstructive pulmonary disease
|
|---|---|
| Published in |
Journal of Clinical Bioinformatics, December 2011
|
| DOI | 10.1186/2043-9113-1-35 |
| Pubmed ID | |
| Authors |
Hong Chen, Xiangdong Wang |
| Abstract |
Chronic obstructive pulmonary disease (COPD) is an inflammatory disease characterized by the progressive deterioration of pulmonary function and increasing airway obstruction, with high morality all over the world. The advent of high-throughput omics techniques provided an opportunity to gain insights into disease pathogenesis and process which contribute to the heterogeneity, and find target-specific and disease-specific therapies. As an interdispline, bioinformatics supplied vital information on integrative understanding of COPD. This review focused on application of bioinformatics in COPD study, including biomarkers searching and systems biology. We also presented the requirements and challenges in implementing bioinformatics to COPD research and interpreted these results as clinical physicians. |
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 % |
|---|---|---|
| Germany | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Japan | 1 | 3% |
| India | 1 | 3% |
| Unknown | 33 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 20% |
| Student > Master | 5 | 14% |
| Student > Ph. D. Student | 5 | 14% |
| Professor > Associate Professor | 4 | 11% |
| Student > Bachelor | 3 | 9% |
| Other | 4 | 11% |
| Unknown | 7 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 10 | 29% |
| Biochemistry, Genetics and Molecular Biology | 5 | 14% |
| Medicine and Dentistry | 5 | 14% |
| Computer Science | 2 | 6% |
| Engineering | 2 | 6% |
| Other | 4 | 11% |
| Unknown | 7 | 20% |
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 21 December 2011.
All research outputs
#17,285,668
of 25,373,627 outputs
Outputs from Journal of Clinical Bioinformatics
#33
of 61 outputs
Outputs of similar age
#171,877
of 248,898 outputs
Outputs of similar age from Journal of Clinical Bioinformatics
#4
of 9 outputs
Altmetric has tracked 25,373,627 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 61 research outputs from this source. They receive a mean Attention Score of 3.1. This one is in the 31st percentile – i.e., 31% 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 248,898 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 9 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.