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Integrating Pathways of Parkinson's Disease in a Molecular Interaction Map

Overview of attention for article published in Molecular Neurobiology, July 2013
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#45 of 3,717)
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
6 news outlets
blogs
1 blog
twitter
10 X users

Citations

dimensions_citation
216 Dimensions

Readers on

mendeley
335 Mendeley
citeulike
2 CiteULike
Title
Integrating Pathways of Parkinson's Disease in a Molecular Interaction Map
Published in
Molecular Neurobiology, July 2013
DOI 10.1007/s12035-013-8489-4
Pubmed ID
Authors

Kazuhiro A. Fujita, Marek Ostaszewski, Yukiko Matsuoka, Samik Ghosh, Enrico Glaab, Christophe Trefois, Isaac Crespo, Thanneer M. Perumal, Wiktor Jurkowski, Paul M. A. Antony, Nico Diederich, Manuel Buttini, Akihiko Kodama, Venkata P. Satagopam, Serge Eifes, Antonio del Sol, Reinhard Schneider, Hiroaki Kitano, Rudi Balling

Abstract

Parkinson's disease (PD) is a major neurodegenerative chronic disease, most likely caused by a complex interplay of genetic and environmental factors. Information on various aspects of PD pathogenesis is rapidly increasing and needs to be efficiently organized, so that the resulting data is available for exploration and analysis. Here we introduce a computationally tractable, comprehensive molecular interaction map of PD. This map integrates pathways implicated in PD pathogenesis such as synaptic and mitochondrial dysfunction, impaired protein degradation, alpha-synuclein pathobiology and neuroinflammation. We also present bioinformatics tools for the analysis, enrichment and annotation of the map, allowing the research community to open new avenues in PD research. The PD map is accessible at http://minerva.uni.lu/pd_map .

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 335 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Luxembourg 5 1%
Spain 3 <1%
United Kingdom 3 <1%
Germany 2 <1%
Australia 1 <1%
Brazil 1 <1%
Colombia 1 <1%
Italy 1 <1%
United States 1 <1%
Other 1 <1%
Unknown 316 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 66 20%
Researcher 52 16%
Student > Master 43 13%
Student > Bachelor 42 13%
Other 19 6%
Other 53 16%
Unknown 60 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 74 22%
Biochemistry, Genetics and Molecular Biology 59 18%
Medicine and Dentistry 35 10%
Neuroscience 26 8%
Computer Science 20 6%
Other 51 15%
Unknown 70 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 53. 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 September 2022.
All research outputs
#754,383
of 24,416,081 outputs
Outputs from Molecular Neurobiology
#45
of 3,717 outputs
Outputs of similar age
#5,906
of 198,524 outputs
Outputs of similar age from Molecular Neurobiology
#2
of 28 outputs
Altmetric has tracked 24,416,081 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,717 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. 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 198,524 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 97% of its contemporaries.
We're also able to compare this research output to 28 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.