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X Demographics
Mendeley readers
Attention Score in Context
| 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. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 40% |
| France | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 60% |
| Scientists | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 27% |
| Student > Ph. D. Student | 4 | 18% |
| Student > Master | 2 | 9% |
| Other | 1 | 5% |
| Lecturer > Senior Lecturer | 1 | 5% |
| Other | 2 | 9% |
| Unknown | 6 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 6 | 27% |
| Biochemistry, Genetics and Molecular Biology | 5 | 23% |
| Computer Science | 2 | 9% |
| Arts and Humanities | 1 | 5% |
| Social Sciences | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 6 | 27% |
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
#14,431,072
of 23,577,654 outputs
Outputs from BMC Bioinformatics
#4,561
of 7,400 outputs
Outputs of similar age
#181,842
of 330,379 outputs
Outputs of similar age from BMC Bioinformatics
#57
of 108 outputs
Altmetric has tracked 23,577,654 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 7,400 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 35th percentile – i.e., 35% 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 330,379 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 108 others from the same source and published within six weeks on either side of this one. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.