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Statistical analysis of dendritic spine distributions in rat hippocampal cultures

Overview of attention for article published in BMC Bioinformatics, October 2013
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Mentioned by

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2 tweeters

Citations

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24 Dimensions

Readers on

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69 Mendeley
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Title
Statistical analysis of dendritic spine distributions in rat hippocampal cultures
Published in
BMC Bioinformatics, October 2013
DOI 10.1186/1471-2105-14-287
Pubmed ID
Authors

Aruna Jammalamadaka, Sourav Banerjee, Bangalore S Manjunath, Kenneth S Kosik

Abstract

Dendritic spines serve as key computational structures in brain plasticity. Much remains to be learned about their spatial and temporal distribution among neurons. Our aim in this study was to perform exploratory analyses based on the population distributions of dendritic spines with regard to their morphological characteristics and period of growth in dissociated hippocampal neurons. We fit a log-linear model to the contingency table of spine features such as spine type and distance from the soma to first determine which features were important in modeling the spines, as well as the relationships between such features. A multinomial logistic regression was then used to predict the spine types using the features suggested by the log-linear model, along with neighboring spine information. Finally, an important variant of Ripley's K-function applicable to linear networks was used to study the spatial distribution of spines along dendrites.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 69 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%
Netherlands 1 1%
Italy 1 1%
Japan 1 1%
United States 1 1%
Unknown 63 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 23%
Researcher 14 20%
Student > Master 9 13%
Student > Bachelor 5 7%
Student > Doctoral Student 5 7%
Other 14 20%
Unknown 6 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 32%
Neuroscience 11 16%
Engineering 9 13%
Computer Science 8 12%
Mathematics 3 4%
Other 9 13%
Unknown 7 10%

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 09 October 2013.
All research outputs
#7,431,308
of 12,378,406 outputs
Outputs from BMC Bioinformatics
#2,967
of 4,542 outputs
Outputs of similar age
#80,061
of 164,663 outputs
Outputs of similar age from BMC Bioinformatics
#50
of 79 outputs
Altmetric has tracked 12,378,406 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,542 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 30th percentile – i.e., 30% 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 164,663 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one is in the 34th percentile – i.e., 34% of its contemporaries scored the same or lower than it.