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DPABI: Data Processing

Overview of attention for article published in Neuroinformatics, April 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#9 of 436)
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

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1 news outlet
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14 X users
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4 patents

Citations

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2545 Dimensions

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556 Mendeley
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Title
DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging
Published in
Neuroinformatics, April 2016
DOI 10.1007/s12021-016-9299-4
Pubmed ID
Authors

Chao-Gan Yan, Xin-Di Wang, Xi-Nian Zuo, Yu-Feng Zang

Abstract

Brain imaging efforts are being increasingly devoted to decode the functioning of the human brain. Among neuroimaging techniques, resting-state fMRI (R-fMRI) is currently expanding exponentially. Beyond the general neuroimaging analysis packages (e.g., SPM, AFNI and FSL), REST and DPARSF were developed to meet the increasing need of user-friendly toolboxes for R-fMRI data processing. To address recently identified methodological challenges of R-fMRI, we introduce the newly developed toolbox, DPABI, which was evolved from REST and DPARSF. DPABI incorporates recent research advances on head motion control and measurement standardization, thus allowing users to evaluate results using stringent control strategies. DPABI also emphasizes test-retest reliability and quality control of data processing. Furthermore, DPABI provides a user-friendly pipeline analysis toolkit for rat/monkey R-fMRI data analysis to reflect the rapid advances in animal imaging. In addition, DPABI includes preprocessing modules for task-based fMRI, voxel-based morphometry analysis, statistical analysis and results viewing. DPABI is designed to make data analysis require fewer manual operations, be less time-consuming, have a lower skill requirement, a smaller risk of inadvertent mistakes, and be more comparable across studies. We anticipate this open-source toolbox will assist novices and expert users alike and continue to support advancing R-fMRI methodology and its application to clinical translational studies.

X Demographics

X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 556 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Germany 1 <1%
Unknown 554 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 101 18%
Student > Master 82 15%
Researcher 64 12%
Student > Doctoral Student 40 7%
Student > Bachelor 37 7%
Other 71 13%
Unknown 161 29%
Readers by discipline Count As %
Neuroscience 122 22%
Psychology 104 19%
Medicine and Dentistry 37 7%
Computer Science 26 5%
Engineering 22 4%
Other 47 8%
Unknown 198 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 21. 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 18 July 2023.
All research outputs
#1,839,354
of 25,837,817 outputs
Outputs from Neuroinformatics
#9
of 436 outputs
Outputs of similar age
#29,847
of 319,503 outputs
Outputs of similar age from Neuroinformatics
#1
of 6 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 436 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 97% 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 319,503 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 90% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them