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Constraint Based Modeling Going Multicellular

Overview of attention for article published in Frontiers in Molecular Biosciences, February 2016
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Title
Constraint Based Modeling Going Multicellular
Published in
Frontiers in Molecular Biosciences, February 2016
DOI 10.3389/fmolb.2016.00003
Pubmed ID
Authors

Patricia do Rosario Martins Conde, Thomas Sauter, Thomas Pfau

Abstract

Constraint based modeling has seen applications in many microorganisms. For example, there are now established methods to determine potential genetic modifications and external interventions to increase the efficiency of microbial strains in chemical production pipelines. In addition, multiple models of multicellular organisms have been created including plants and humans. While initially the focus here was on modeling individual cell types of the multicellular organism, this focus recently started to switch. Models of microbial communities, as well as multi-tissue models of higher organisms have been constructed. These models thereby can include different parts of a plant, like root, stem, or different tissue types in the same organ. Such models can elucidate details of the interplay between symbiotic organisms, as well as the concerted efforts of multiple tissues and can be applied to analyse the effects of drugs or mutations on a more systemic level. In this review we give an overview of the recent development of multi-tissue models using constraint based techniques and the methods employed when investigating these models. We further highlight advances in combining constraint based models with dynamic and regulatory information and give an overview of these types of hybrid or multi-level approaches.

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 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Hungary 1 <1%
Germany 1 <1%
Chile 1 <1%
France 1 <1%
Israel 1 <1%
United Kingdom 1 <1%
United States 1 <1%
Unknown 98 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 27 26%
Researcher 24 23%
Student > Master 14 13%
Student > Bachelor 6 6%
Student > Doctoral Student 4 4%
Other 12 11%
Unknown 18 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 26 25%
Agricultural and Biological Sciences 26 25%
Computer Science 11 10%
Engineering 5 5%
Mathematics 3 3%
Other 10 10%
Unknown 24 23%
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 10 February 2016.
All research outputs
#18,438,457
of 22,844,985 outputs
Outputs from Frontiers in Molecular Biosciences
#1,956
of 3,792 outputs
Outputs of similar age
#290,267
of 400,522 outputs
Outputs of similar age from Frontiers in Molecular Biosciences
#10
of 12 outputs
Altmetric has tracked 22,844,985 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,792 research outputs from this source. They receive a mean Attention Score of 3.3. This one is in the 33rd percentile – i.e., 33% 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 400,522 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 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.