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Yeast pheromone pathway modeling using Petri nets

Overview of attention for article published in BMC Bioinformatics, May 2014
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Citations

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Title
Yeast pheromone pathway modeling using Petri nets
Published in
BMC Bioinformatics, May 2014
DOI 10.1186/1471-2105-15-s7-s13
Pubmed ID
Authors

Abhishek Majumdar, Stephen D Scott, Jitender S Deogun, Steven Harris

Abstract

Our environment is composed of biological components of varying magnitude. The relationships between the different biological elements can be represented as a biological network. The process of mating in S. cerevisiae is initiated by secretion of pheromone by one of the cells. Our interest lies in one particular question: how does a cell dynamically adapt the pathway to continue mating under severe environmental changes or under mutation (which might result in the loss of functionality of some proteins known to participate in the pheromone pathway). Our work attempts to answer this question. To achieve this, we first propose a model to simulate the pheromone pathway using Petri nets. Petri nets are directed graphs that can be used for describing and modeling systems characterized as concurrent, asynchronous, distributed, parallel, non-deterministic, and/or stochastic. We then analyze our Petri net-based model of the pathway to investigate the following: 1) Given the model of the pheromone response pathway, under what conditions does the cell respond positively, i.e., mate? 2) What kinds of perturbations in the cell would result in changing a negative response to a positive one?

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

Geographical breakdown

Country Count As %
United Kingdom 1 7%
Unknown 13 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 36%
Student > Postgraduate 3 21%
Student > Ph. D. Student 2 14%
Professor > Associate Professor 2 14%
Professor 2 14%
Other 0 0%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 57%
Biochemistry, Genetics and Molecular Biology 2 14%
Computer Science 2 14%
Mathematics 1 7%
Medicine and Dentistry 1 7%
Other 0 0%
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 13 August 2014.
All research outputs
#14,783,222
of 22,759,618 outputs
Outputs from BMC Bioinformatics
#5,040
of 7,273 outputs
Outputs of similar age
#126,729
of 226,672 outputs
Outputs of similar age from BMC Bioinformatics
#91
of 153 outputs
Altmetric has tracked 22,759,618 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,273 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 26th percentile – i.e., 26% 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 226,672 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 153 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.