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Analysis tools for the interplay between genome layout and regulation

Overview of attention for article published in BMC Bioinformatics, June 2016
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Title
Analysis tools for the interplay between genome layout and regulation
Published in
BMC Bioinformatics, June 2016
DOI 10.1186/s12859-016-1047-0
Pubmed ID
Authors

Costas Bouyioukos, Mohamed Elati, François Képès

Abstract

Genome layout and gene regulation appear to be interdependent. Understanding this interdependence is key to exploring the dynamic nature of chromosome conformation and to engineering functional genomes. Evidence for non-random genome layout, defined as the relative positioning of either co-functional or co-regulated genes, stems from two main approaches. Firstly, the analysis of contiguous genome segments across species, has highlighted the conservation of gene arrangement (synteny) along chromosomal regions. Secondly, the study of long-range interactions along a chromosome has emphasised regularities in the positioning of microbial genes that are co-regulated, co-expressed or evolutionarily correlated. While one-dimensional pattern analysis is a mature field, it is often powerless on biological datasets which tend to be incomplete, and partly incorrect. Moreover, there is a lack of comprehensive, user-friendly tools to systematically analyse, visualise, integrate and exploit regularities along genomes. Here we present the Genome REgulatory and Architecture Tools SCAN (GREAT:SCAN) software for the systematic study of the interplay between genome layout and gene expression regulation. SCAN is a collection of related and interconnected applications currently able to perform systematic analyses of genome regularities as well as to improve transcription factor binding sites (TFBS) and gene regulatory network predictions based on gene positional information. We demonstrate the capabilities of these tools by studying on one hand the regular patterns of genome layout in the major regulons of the bacterium Escherichia coli. On the other hand, we demonstrate the capabilities to improve TFBS prediction in microbes. Finally, we highlight, by visualisation of multivariate techniques, the interplay between position and sequence information for effective transcription regulation.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Mexico 1 6%
France 1 6%
Unknown 14 88%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 25%
Student > Ph. D. Student 4 25%
Researcher 4 25%
Student > Bachelor 2 13%
Student > Postgraduate 2 13%
Other 0 0%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 56%
Biochemistry, Genetics and Molecular Biology 5 31%
Computer Science 2 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 14 June 2016.
All research outputs
#14,265,823
of 22,876,619 outputs
Outputs from BMC Bioinformatics
#4,739
of 7,297 outputs
Outputs of similar age
#191,871
of 340,764 outputs
Outputs of similar age from BMC Bioinformatics
#59
of 90 outputs
Altmetric has tracked 22,876,619 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,297 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 30th percentile – i.e., 30% of its peers scored the same or lower than it.
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We're also able to compare this research output to 90 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.