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An efficient algorithm to explore liquid association on a genome-wide scale

Overview of attention for article published in BMC Bioinformatics, November 2014
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  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

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Title
An efficient algorithm to explore liquid association on a genome-wide scale
Published in
BMC Bioinformatics, November 2014
DOI 10.1186/s12859-014-0371-5
Pubmed ID
Authors

Tina Gunderson, Yen-Yi Ho

Abstract

BackgroundThe growing wealth of public available gene expression data has made the systemic studies of how genes interact in a cell become more feasible. Liquid association (LA) describes the extent to which coexpression of two genes may vary based on the expression level of a third gene (the controller gene). However, genome-wide application has been difficult and resource-intensive. We propose a new screening algorithm for more efficient processing of LA estimation on a genome-wide scale and apply its use to a Saccharomyces cerevisiae data set.ResultsOn a test subset of the data, the fast screening algorithm achieved >99.8% agreement with the exhaustive search of LA values, while reduced run time by 81¿93 %. Using a well-known yeast cell-cycle data set with 6,178 genes, we identified triplet combinations with significantly large LA values. In an exploratory gene set enrichment analysis, the top terms for the controller genes in these triplets with large LA values are involved in some of the most fundamental processes in yeast such as energy regulation, transportation, and sporulation.ConclusionIn summary, in this paper we propose a novel, efficient algorithm to explore LA on a genome-wide scale and identified triplets of interest in cell cycle pathways using the proposed method in a yeast data set. A software package named fastLiquidAssociation for implementing the algorithm is available through http://www.bioconductor.org.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 7%
Unknown 14 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 33%
Researcher 4 27%
Other 2 13%
Student > Master 1 7%
Student > Bachelor 1 7%
Other 2 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 5 33%
Agricultural and Biological Sciences 4 27%
Computer Science 4 27%
Mathematics 1 7%
Physics and Astronomy 1 7%
Other 0 0%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 03 September 2015.
All research outputs
#7,477,223
of 23,498,099 outputs
Outputs from BMC Bioinformatics
#2,916
of 7,400 outputs
Outputs of similar age
#104,562
of 365,793 outputs
Outputs of similar age from BMC Bioinformatics
#51
of 135 outputs
Altmetric has tracked 23,498,099 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 59% 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 365,793 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 70% of its contemporaries.
We're also able to compare this research output to 135 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 62% of its contemporaries.