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QTL/microarray approach using pathway information

Overview of attention for article published in Algorithms for Molecular Biology, January 2012
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (60th percentile)

Mentioned by

twitter
6 tweeters

Citations

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14 Dimensions

Readers on

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9 Mendeley
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Title
QTL/microarray approach using pathway information
Published in
Algorithms for Molecular Biology, January 2012
DOI 10.1186/1748-7188-7-1
Pubmed ID
Authors

Hirokazu Matsuda, Yukio Taniguchi, Hiroaki Iwaisaki

Abstract

A combined quantitative trait loci (QTL) and microarray-based approach is commonly used to find differentially expressed genes which are then identified based on the known function of a gene in the biological process governing the trait of interest. However, a low cutoff value in individual gene analyses may result in many genes with moderate but meaningful changes in expression being missed.

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 11%
Unknown 8 89%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 56%
Student > Doctoral Student 2 22%
Student > Ph. D. Student 2 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 100%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 02 August 2012.
All research outputs
#6,461,786
of 12,434,464 outputs
Outputs from Algorithms for Molecular Biology
#65
of 181 outputs
Outputs of similar age
#86,359
of 220,458 outputs
Outputs of similar age from Algorithms for Molecular Biology
#2
of 3 outputs
Altmetric has tracked 12,434,464 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 181 research outputs from this source. They receive a mean Attention Score of 2.9. This one has gotten more attention than average, scoring higher than 62% 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 220,458 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.