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Achieving diverse and monoallelic olfactory receptor selection through dual-objective optimization design

Overview of attention for article published in Proceedings of the National Academy of Sciences of the United States of America, May 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
24 news outlets
blogs
3 blogs
twitter
11 tweeters
wikipedia
1 Wikipedia page
googleplus
3 Google+ users

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
46 Mendeley
citeulike
1 CiteULike
Title
Achieving diverse and monoallelic olfactory receptor selection through dual-objective optimization design
Published in
Proceedings of the National Academy of Sciences of the United States of America, May 2016
DOI 10.1073/pnas.1601722113
Pubmed ID
Authors

Xiao-Jun Tian, Hang Zhang, Jens Sannerud, Jianhua Xing

Abstract

Multiple-objective optimization is common in biological systems. In the mammalian olfactory system, each sensory neuron stochastically expresses only one out of up to thousands of olfactory receptor (OR) gene alleles; at the organism level, the types of expressed ORs need to be maximized. Existing models focus only on monoallele activation, and cannot explain recent observations in mutants, especially the reduced global diversity of expressed ORs in G9a/GLP knockouts. In this work we integrated existing information on OR expression, and constructed a comprehensive model that has all its components based on physical interactions. Analyzing the model reveals an evolutionarily optimized three-layer regulation mechanism, which includes zonal segregation, epigenetic barrier crossing coupled to a negative feedback loop that mechanistically differs from previous theoretical proposals, and a previously unidentified enhancer competition step. This model not only recapitulates monoallelic OR expression, but also elucidates how the olfactory system maximizes and maintains the diversity of OR expression, and has multiple predictions validated by existing experimental results. Through making an analogy to a physical system with thermally activated barrier crossing and comparative reverse engineering analyses, the study reveals that the olfactory receptor selection system is optimally designed, and particularly underscores cooperativity and synergy as a general design principle for multiobjective optimization in biology.

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters 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 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 4%
United Kingdom 1 2%
Unknown 43 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 35%
Researcher 12 26%
Student > Doctoral Student 4 9%
Professor > Associate Professor 3 7%
Professor 2 4%
Other 5 11%
Unknown 4 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 33%
Neuroscience 9 20%
Physics and Astronomy 7 15%
Biochemistry, Genetics and Molecular Biology 6 13%
Psychology 2 4%
Other 4 9%
Unknown 3 7%

Attention Score in Context

This research output has an Altmetric Attention Score of 217. 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 17 June 2017.
All research outputs
#69,251
of 14,573,111 outputs
Outputs from Proceedings of the National Academy of Sciences of the United States of America
#1,679
of 82,813 outputs
Outputs of similar age
#1,281
of 234,183 outputs
Outputs of similar age from Proceedings of the National Academy of Sciences of the United States of America
#32
of 929 outputs
Altmetric has tracked 14,573,111 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 82,813 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.0. This one has done particularly well, scoring higher than 98% 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 234,183 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 929 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.