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AceTree: a major update and case study in the long term maintenance of open-source scientific software

Overview of attention for article published in BMC Bioinformatics, April 2018
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  • Good Attention Score compared to outputs of the same age and source (70th percentile)

Mentioned by

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6 tweeters

Citations

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9 Dimensions

Readers on

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15 Mendeley
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Title
AceTree: a major update and case study in the long term maintenance of open-source scientific software
Published in
BMC Bioinformatics, April 2018
DOI 10.1186/s12859-018-2127-0
Pubmed ID
Authors

Braden Katzman, Doris Tang, Anthony Santella, Zhirong Bao

Abstract

AceTree, a software application first released in 2006, facilitates exploration, curation and editing of tracked C. elegans nuclei in 4-dimensional (4D) fluorescence microscopy datasets. Since its initial release, AceTree has been continuously used to interact with, edit and interpret C. elegans lineage data. In its 11 year lifetime, AceTree has been periodically updated to meet the technical and research demands of its community of users. This paper presents the newest iteration of AceTree which contains extensive updates, demonstrates the new applicability of AceTree in other developmental contexts, and presents its evolutionary software development paradigm as a viable model for maintaining scientific software. Large scale updates have been made to the user interface for an improved user experience. Tools have been grouped according to functionality and obsolete methods have been removed. Internal requirements have been changed that enable greater flexibility of use both in C. elegans contexts and in other model organisms. Additionally, the original 3-dimensional (3D) viewing window has been completely reimplemented. The new window provides a new suite of tools for data exploration. By responding to technical advancements and research demands, AceTree has remained a useful tool for scientific research for over a decade. The updates made to the codebase have extended AceTree's applicability beyond its initial use in C. elegans and enabled its usage with other model organisms. The evolution of AceTree demonstrates a viable model for maintaining scientific software over long periods of time.

Twitter Demographics

The data shown below were collected from the profiles of 6 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 33%
Student > Ph. D. Student 3 20%
Student > Master 2 13%
Student > Bachelor 1 7%
Professor > Associate Professor 1 7%
Other 0 0%
Unknown 3 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 27%
Agricultural and Biological Sciences 4 27%
Computer Science 2 13%
Neuroscience 1 7%
Design 1 7%
Other 0 0%
Unknown 3 20%

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 02 November 2018.
All research outputs
#7,763,553
of 13,813,295 outputs
Outputs from BMC Bioinformatics
#2,946
of 5,146 outputs
Outputs of similar age
#135,212
of 275,382 outputs
Outputs of similar age from BMC Bioinformatics
#7
of 27 outputs
Altmetric has tracked 13,813,295 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,146 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 39th percentile – i.e., 39% 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 275,382 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.