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Attention Score in Context
| Title |
Gene expression profiling of ovarian carcinomas and prognostic analysis of outcome
|
|---|---|
| Published in |
Journal of Ovarian Research, July 2015
|
| DOI | 10.1186/s13048-015-0176-9 |
| Pubmed ID | |
| Authors |
Sheng-Yun Cai, Tian Yang, Yu Chen, Jing-Wen Wang, Li Li, Ming-Juan Xu |
| Abstract |
Ovarian cancer (OCA), the fifth leading deaths cancer to women, is famous for its low survival rate in epithelial ovarian cancer cases, which is very complicated and hard to be diagnosed from asymptomatic nature in the early stage. Thus, it is urgent to develop an effective genetic prognostic strategy. Current study using the Database for Annotation, Visualization and Integrated Discovery tool for the generation and analysis of quantitative gene expression profiles; all the annotated gene and biochemical pathway membership realized according to shared categorical data from Pathway and Kyoto Encyclopedia of Genes and Genomes; correlation networks based on current gene screening actualize by Weighted correlation network analysis to identify therapeutic targets gene and candidate bio-markers. 3095 differentially expressed genes were collected from genome expression profiles of OCA patients (n = 53, 35 advanced, 8 early and 10 normal). By pathway enrichment, most genes showed contribution to cell cycle and chromosome maintenance.1073 differentially expression genes involved in the 4 dominant network modules are further generated for prognostic pattern establish, we divided a dataset with random OCA cases (n = 80) into 3 groups efficiently (p = 0.0323, 95 % CIs in Kaplan-Meier). Finally, 6 prognosis related genes were selected out by COX regression analysis, TFCP2L1 related to cancer-stem cell, probably contributes to chemotherapy efficiency. Our study presents an integrated original model of the differentially expression genes related to ovarian cancer progressing, providing the identification of genes relevant for its pathological physiology which can potentially be new clinical markers. |
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 % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 29 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 6 | 21% |
| Professor | 4 | 14% |
| Researcher | 4 | 14% |
| Student > Ph. D. Student | 4 | 14% |
| Other | 3 | 10% |
| Other | 2 | 7% |
| Unknown | 6 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 28% |
| Medicine and Dentistry | 7 | 24% |
| Biochemistry, Genetics and Molecular Biology | 5 | 17% |
| Nursing and Health Professions | 1 | 3% |
| Immunology and Microbiology | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 6 | 21% |
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 27 August 2016.
All research outputs
#17,766,929
of 22,818,766 outputs
Outputs from Journal of Ovarian Research
#279
of 587 outputs
Outputs of similar age
#176,500
of 262,895 outputs
Outputs of similar age from Journal of Ovarian Research
#8
of 13 outputs
Altmetric has tracked 22,818,766 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 587 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 46th percentile – i.e., 46% 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 262,895 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 13 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.