↓ Skip to main content

Reconciliation of Genome-Scale Metabolic Reconstructions for Comparative Systems Analysis

Overview of attention for article published in PLoS Computational Biology, March 2011
Altmetric Badge

Mentioned by

twitter
1 X user

Citations

dimensions_citation
107 Dimensions

Readers on

mendeley
243 Mendeley
citeulike
7 CiteULike
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Reconciliation of Genome-Scale Metabolic Reconstructions for Comparative Systems Analysis
Published in
PLoS Computational Biology, March 2011
DOI 10.1371/journal.pcbi.1001116
Pubmed ID
Authors

Matthew A. Oberhardt, Jacek Puchałka, Vítor A. P. Martins dos Santos, Jason A. Papin

Abstract

In the past decade, over 50 genome-scale metabolic reconstructions have been built for a variety of single- and multi- cellular organisms. These reconstructions have enabled a host of computational methods to be leveraged for systems-analysis of metabolism, leading to greater understanding of observed phenotypes. These methods have been sparsely applied to comparisons between multiple organisms, however, due mainly to the existence of differences between reconstructions that are inherited from the respective reconstruction processes of the organisms to be compared. To circumvent this obstacle, we developed a novel process, termed metabolic network reconciliation, whereby non-biological differences are removed from genome-scale reconstructions while keeping the reconstructions as true as possible to the underlying biological data on which they are based. This process was applied to two organisms of great importance to disease and biotechnological applications, Pseudomonas aeruginosa and Pseudomonas putida, respectively. The result is a pair of revised genome-scale reconstructions for these organisms that can be analyzed at a systems level with confidence that differences are indicative of true biological differences (to the degree that is currently known), rather than artifacts of the reconstruction process. The reconstructions were re-validated with various experimental data after reconciliation. With the reconciled and validated reconstructions, we performed a genome-wide comparison of metabolic flexibility between P. aeruginosa and P. putida that generated significant new insight into the underlying biology of these important organisms. Through this work, we provide a novel methodology for reconciling models, present new genome-scale reconstructions of P. aeruginosa and P. putida that can be directly compared at a network level, and perform a network-wide comparison of the two species. These reconstructions provide fresh insights into the metabolic similarities and differences between these important Pseudomonads, and pave the way towards full comparative analysis of genome-scale metabolic reconstructions of multiple species.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 243 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 14 6%
Germany 4 2%
Iran, Islamic Republic of 2 <1%
United Kingdom 2 <1%
Latvia 1 <1%
France 1 <1%
Brazil 1 <1%
Hong Kong 1 <1%
Hungary 1 <1%
Other 8 3%
Unknown 208 86%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 69 28%
Researcher 68 28%
Student > Master 19 8%
Professor > Associate Professor 16 7%
Student > Doctoral Student 14 6%
Other 38 16%
Unknown 19 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 119 49%
Biochemistry, Genetics and Molecular Biology 32 13%
Engineering 21 9%
Computer Science 19 8%
Chemical Engineering 5 2%
Other 18 7%
Unknown 29 12%
Attention Score in Context

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 09 November 2011.
All research outputs
#20,655,488
of 25,371,288 outputs
Outputs from PLoS Computational Biology
#8,207
of 8,958 outputs
Outputs of similar age
#106,384
of 120,786 outputs
Outputs of similar age from PLoS Computational Biology
#57
of 63 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,958 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one is in the 4th percentile – i.e., 4% of its peers scored the same or lower than it.
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 120,786 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 63 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.