You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Genomic convergence and network analysis approach to identify candidate genes in Alzheimer's disease
|
|---|---|
| Published in |
BMC Genomics, March 2014
|
| DOI | 10.1186/1471-2164-15-199 |
| Pubmed ID | |
| Authors |
Puneet Talwar, Yumnam Silla, Sandeep Grover, Meenal Gupta, Rachna Agarwal, Suman Kushwaha, Ritushree Kukreti |
| Abstract |
Alzheimer's disease (AD) is one of the leading genetically complex and heterogeneous disorder that is influenced by both genetic and environmental factors. The underlying risk factors remain largely unclear for this heterogeneous disorder. In recent years, high throughput methodologies, such as genome-wide linkage analysis (GWL), genome-wide association (GWA) studies, and genome-wide expression profiling (GWE), have led to the identification of several candidate genes associated with AD. However, due to lack of consistency within their findings, an integrative approach is warranted. Here, we have designed a rank based gene prioritization approach involving convergent analysis of multi-dimensional data and protein-protein interaction (PPI) network modelling. |
X Demographics
The data shown below were collected from the profiles of 11 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 Kingdom | 3 | 27% |
| United States | 2 | 18% |
| Switzerland | 1 | 9% |
| Unknown | 5 | 45% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 73% |
| Scientists | 2 | 18% |
| Practitioners (doctors, other healthcare professionals) | 1 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 128 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Korea, Republic of | 1 | <1% |
| Sweden | 1 | <1% |
| Unknown | 126 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 32 | 25% |
| Researcher | 18 | 14% |
| Student > Master | 16 | 13% |
| Student > Bachelor | 13 | 10% |
| Professor > Associate Professor | 6 | 5% |
| Other | 18 | 14% |
| Unknown | 25 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 31 | 24% |
| Biochemistry, Genetics and Molecular Biology | 21 | 16% |
| Medicine and Dentistry | 15 | 12% |
| Computer Science | 9 | 7% |
| Neuroscience | 8 | 6% |
| Other | 13 | 10% |
| Unknown | 31 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 19 April 2022.
All research outputs
#5,949,230
of 23,577,654 outputs
Outputs from BMC Genomics
#2,432
of 10,787 outputs
Outputs of similar age
#54,106
of 222,615 outputs
Outputs of similar age from BMC Genomics
#21
of 147 outputs
Altmetric has tracked 23,577,654 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 10,787 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 77% 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 222,615 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 147 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.