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A systems approach to identifying correlated gene targets for the loss of colour pigmentation in plants

Overview of attention for article published in BMC Bioinformatics, August 2011
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1 tweeter

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Title
A systems approach to identifying correlated gene targets for the loss of colour pigmentation in plants
Published in
BMC Bioinformatics, August 2011
DOI 10.1186/1471-2105-12-343
Pubmed ID
Authors

Sangaalofa T Clark, Wynand S Verwoerd

Abstract

The numerous diverse metabolic pathways by which plant compounds can be produced make it difficult to predict how colour pigmentation is lost for different tissues and plants. This study employs mathematical and in silico methods to identify correlated gene targets for the loss of colour pigmentation in plants from a whole cell perspective based on the full metabolic network of Arabidopsis. This involves extracting a self-contained flavonoid subnetwork from the AraCyc database and calculating feasible metabolic routes or elementary modes (EMs) for it. Those EMs leading to anthocyanin compounds are taken to constitute the anthocyanin biosynthetic pathway (ABP) and their interplay with the rest of the EMs is used to study the minimal cut sets (MCSs), which are different combinations of reactions to block for eliminating colour pigmentation. By relating the reactions to their corresponding genes, the MCSs are used to explore the phenotypic roles of the ABP genes, their relevance to the ABP and the impact their eliminations would have on other processes in the cell.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 33 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 30%
Student > Ph. D. Student 7 21%
Student > Master 6 18%
Professor > Associate Professor 3 9%
Student > Doctoral Student 1 3%
Other 1 3%
Unknown 5 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 67%
Biochemistry, Genetics and Molecular Biology 4 12%
Computer Science 2 6%
Unknown 5 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 October 2011.
All research outputs
#7,762,549
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#3,177
of 4,576 outputs
Outputs of similar age
#58,798
of 97,007 outputs
Outputs of similar age from BMC Bioinformatics
#27
of 34 outputs
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So far Altmetric has tracked 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
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We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.