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Attention Score in Context
| Title |
dbMDEGA: a database for meta-analysis of differentially expressed genes in autism spectrum disorder
|
|---|---|
| Published in |
BMC Bioinformatics, November 2017
|
| DOI | 10.1186/s12859-017-1915-2 |
| Pubmed ID | |
| Authors |
Shuyun Zhang, Libin Deng, Qiyue Jia, Shaoting Huang, Junwang Gu, Fankun Zhou, Meng Gao, Xinyi Sun, Chang Feng, Guangqin Fan |
| Abstract |
Autism spectrum disorders (ASD) are hereditary, heterogeneous and biologically complex neurodevelopmental disorders. Individual studies on gene expression in ASD cannot provide clear consensus conclusions. Therefore, a systematic review to synthesize the current findings from brain tissues and a search tool to share the meta-analysis results are urgently needed. Here, we conducted a meta-analysis of brain gene expression profiles in the current reported human ASD expression datasets (with 84 frozen male cortex samples, 17 female cortex samples, 32 cerebellum samples and 4 formalin fixed samples) and knock-out mouse ASD model expression datasets (with 80 collective brain samples). Then, we applied R language software and developed an interactive shared and updated database (dbMDEGA) displaying the results of meta-analysis of data from ASD studies regarding differentially expressed genes (DEGs) in the brain. This database, dbMDEGA ( https://dbmdega.shinyapps.io/dbMDEGA/ ), is a publicly available web-portal for manual annotation and visualization of DEGs in the brain from data from ASD studies. This database uniquely presents meta-analysis values and homologous forest plots of DEGs in brain tissues. Gene entries are annotated with meta-values, statistical values and forest plots of DEGs in brain samples. This database aims to provide searchable meta-analysis results based on the current reported brain gene expression datasets of ASD to help detect candidate genes underlying this disorder. This new analytical tool may provide valuable assistance in the discovery of DEGs and the elucidation of the molecular pathogenicity of ASD. This database model may be replicated to study other disorders. |
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 % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 54 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 15% |
| Researcher | 7 | 13% |
| Student > Bachelor | 6 | 11% |
| Student > Ph. D. Student | 6 | 11% |
| Student > Postgraduate | 5 | 9% |
| Other | 6 | 11% |
| Unknown | 16 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 7 | 13% |
| Nursing and Health Professions | 4 | 7% |
| Medicine and Dentistry | 4 | 7% |
| Neuroscience | 4 | 7% |
| Psychology | 4 | 7% |
| Other | 11 | 20% |
| Unknown | 20 | 37% |
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 17 November 2017.
All research outputs
#20,452,930
of 23,008,860 outputs
Outputs from BMC Bioinformatics
#6,890
of 7,315 outputs
Outputs of similar age
#257,112
of 294,546 outputs
Outputs of similar age from BMC Bioinformatics
#135
of 159 outputs
Altmetric has tracked 23,008,860 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,315 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 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 159 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.