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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Chapter 10: Mining Genome-Wide Genetic Markers
|
|---|---|
| Published in |
PLoS Computational Biology, December 2012
|
| DOI | 10.1371/journal.pcbi.1002828 |
| Pubmed ID | |
| Authors |
Xiang Zhang, Shunping Huang, Zhaojun Zhang, Wei Wang |
| Abstract |
Genome-wide association study (GWAS) aims to discover genetic factors underlying phenotypic traits. The large number of genetic factors poses both computational and statistical challenges. Various computational approaches have been developed for large scale GWAS. In this chapter, we will discuss several widely used computational approaches in GWAS. The following topics will be covered: (1) An introduction to the background of GWAS. (2) The existing computational approaches that are widely used in GWAS. This will cover single-locus, epistasis detection, and machine learning methods that have been recently developed in biology, statistic, and computer science communities. This part will be the main focus of this chapter. (3) The limitations of current approaches and future directions. |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Comoros | 1 | 13% |
| Germany | 1 | 13% |
| Brazil | 1 | 13% |
| France | 1 | 13% |
| Canada | 1 | 13% |
| United States | 1 | 13% |
| Unknown | 2 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 5 | 63% |
| Members of the public | 2 | 25% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 186 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 4 | 2% |
| Germany | 3 | 2% |
| United States | 3 | 2% |
| Brazil | 2 | 1% |
| France | 1 | <1% |
| Sweden | 1 | <1% |
| United Kingdom | 1 | <1% |
| Hungary | 1 | <1% |
| China | 1 | <1% |
| Other | 3 | 2% |
| Unknown | 166 | 89% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 51 | 27% |
| Student > Ph. D. Student | 49 | 26% |
| Student > Master | 24 | 13% |
| Professor > Associate Professor | 13 | 7% |
| Other | 10 | 5% |
| Other | 29 | 16% |
| Unknown | 10 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 78 | 42% |
| Biochemistry, Genetics and Molecular Biology | 31 | 17% |
| Computer Science | 22 | 12% |
| Medicine and Dentistry | 12 | 6% |
| Chemistry | 4 | 2% |
| Other | 18 | 10% |
| Unknown | 21 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. 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 11 February 2018.
All research outputs
#5,375,977
of 25,864,668 outputs
Outputs from PLoS Computational Biology
#4,042
of 9,061 outputs
Outputs of similar age
#51,733
of 291,157 outputs
Outputs of similar age from PLoS Computational Biology
#41
of 120 outputs
Altmetric has tracked 25,864,668 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,061 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.3. This one has gotten more attention than average, scoring higher than 55% 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 291,157 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 81% of its contemporaries.
We're also able to compare this research output to 120 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.