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X Demographics
Mendeley readers
Attention Score in Context
| Title |
ARAM: an automated image analysis software to determine rosetting parameters and parasitaemia in Plasmodium samples
|
|---|---|
| Published in |
Malaria Journal, April 2016
|
| DOI | 10.1186/s12936-016-1243-4 |
| Pubmed ID | |
| Authors |
Patrick Wolfgang Kudella, Kirsten Moll, Mats Wahlgren, Achim Wixforth, Christoph Westerhausen |
| Abstract |
Rosetting is associated with severe malaria and a primary cause of death in Plasmodium falciparum infections. Detailed understanding of this adhesive phenomenon may enable the development of new therapies interfering with rosette formation. For this, it is crucial to determine parameters such as rosetting and parasitaemia of laboratory strains or patient isolates, a bottleneck in malaria research due to the time consuming and error prone manual analysis of specimens. Here, the automated, free, stand-alone analysis software automated rosetting analyzer for micrographs (ARAM) to determine rosetting rate, rosette size distribution as well as parasitaemia with a convenient graphical user interface is presented. Automated rosetting analyzer for micrographs is an executable with two operation modes for automated identification of objects on images. The default mode detects red blood cells and fluorescently labelled parasitized red blood cells by combining an intensity-gradient with a threshold filter. The second mode determines object location and size distribution from a single contrast method. The obtained results are compared with standardized manual analysis. Automated rosetting analyzer for micrographs calculates statistical confidence probabilities for rosetting rate and parasitaemia. Automated rosetting analyzer for micrographs analyses 25 cell objects per second reliably delivering identical results compared to manual analysis. For the first time rosette size distribution is determined in a precise and quantitative manner employing ARAM in combination with established inhibition tests. Additionally ARAM measures the essential observables parasitaemia, rosetting rate and size as well as location of all detected objects and provides confidence intervals for the determined observables. No other existing software solution offers this range of function. The second, non-malaria specific, analysis mode of ARAM offers the functionality to detect arbitrary objects. Automated rosetting analyzer for micrographs has the capability to push malaria research to a more quantitative and statistically significant level with increased reliability due to operator independence. As an installation file for Windows |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Science communicators (journalists, bloggers, editors) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 33% |
| Student > Master | 5 | 24% |
| Student > Bachelor | 4 | 19% |
| Researcher | 2 | 10% |
| Lecturer | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 1 | 5% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 24% |
| Biochemistry, Genetics and Molecular Biology | 5 | 24% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 10% |
| Physics and Astronomy | 2 | 10% |
| Agricultural and Biological Sciences | 1 | 5% |
| Other | 4 | 19% |
| Unknown | 2 | 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 06 May 2016.
All research outputs
#14,195,752
of 22,865,319 outputs
Outputs from Malaria Journal
#3,932
of 5,573 outputs
Outputs of similar age
#158,756
of 299,111 outputs
Outputs of similar age from Malaria Journal
#116
of 165 outputs
Altmetric has tracked 22,865,319 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 5,573 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one is in the 28th percentile – i.e., 28% 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 299,111 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 165 others from the same source and published within six weeks on either side of this one. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.