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Bioremediation in marine ecosystems: a computational study combining ecological modeling and flux balance analysis

Overview of attention for article published in Frontiers in Genetics, September 2014
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (77th percentile)

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Title
Bioremediation in marine ecosystems: a computational study combining ecological modeling and flux balance analysis
Published in
Frontiers in Genetics, September 2014
DOI 10.3389/fgene.2014.00319
Pubmed ID
Authors

Marianna Taffi, Nicola Paoletti, Claudio Angione, Sandra Pucciarelli, Mauro Marini, Pietro Liò

Abstract

The pressure to search effective bioremediation methodologies for contaminated ecosystems has led to the large-scale identification of microbial species and metabolic degradation pathways. However, minor attention has been paid to the study of bioremediation in marine food webs and to the definition of integrated strategies for reducing bioaccumulation in species. We propose a novel computational framework for analysing the multiscale effects of bioremediation at the ecosystem level, based on coupling food web bioaccumulation models and metabolic models of degrading bacteria. The combination of techniques from synthetic biology and ecological network analysis allows the specification of arbitrary scenarios of contaminant removal and the evaluation of strategies based on natural or synthetic microbial strains. In this study, we derive a bioaccumulation model of polychlorinated biphenyls (PCBs) in the Adriatic food web, and we extend a metabolic reconstruction of Pseudomonas putida KT2440 (iJN746) with the aerobic pathway of PCBs degradation. We assess the effectiveness of different bioremediation scenarios in reducing PCBs concentration in species and we study indices of species centrality to measure their importance in the contaminant diffusion via feeding links. The analysis of the Adriatic sea case study suggests that our framework could represent a practical tool in the design of effective remediation strategies, providing at the same time insights into the ecological role of microbial communities within food webs.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users 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 66 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 2%
France 1 2%
Brazil 1 2%
United Kingdom 1 2%
United States 1 2%
Unknown 61 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 23%
Researcher 11 17%
Student > Postgraduate 7 11%
Student > Bachelor 6 9%
Student > Master 4 6%
Other 8 12%
Unknown 15 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 30%
Biochemistry, Genetics and Molecular Biology 8 12%
Environmental Science 4 6%
Computer Science 4 6%
Mathematics 2 3%
Other 5 8%
Unknown 23 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 12 September 2016.
All research outputs
#5,560,476
of 22,763,032 outputs
Outputs from Frontiers in Genetics
#1,587
of 11,758 outputs
Outputs of similar age
#56,002
of 243,384 outputs
Outputs of similar age from Frontiers in Genetics
#27
of 119 outputs
Altmetric has tracked 22,763,032 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,758 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done well, scoring higher than 86% 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 243,384 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 119 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 77% of its contemporaries.