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X Demographics
Mendeley readers
Attention Score in Context
| Title |
ImmunExplorer (IMEX): a software framework for diversity and clonality analyses of immunoglobulins and T cell receptors on the basis of IMGT/HighV-QUEST preprocessed NGS data
|
|---|---|
| Published in |
BMC Bioinformatics, August 2015
|
| DOI | 10.1186/s12859-015-0687-9 |
| Pubmed ID | |
| Authors |
Susanne Schaller, Johannes Weinberger, Raul Jimenez-Heredia, Martin Danzer, Rainer Oberbauer, Christian Gabriel, Stephan M. Winkler |
| Abstract |
Today's modern research of B and T cell antigen receptors (the immunoglobulins (IG) or antibodies and T cell receptors (TR)) forms the basis for detailed analyses of the human adaptive immune system. For instance, insights in the state of the adaptive immune system provide information that is essentially important in monitoring transplantation processes and the regulation of immune suppressiva. In this context, algorithms and tools are necessary for analyzing the IG and TR diversity on nucleotide as well as on amino acid sequence level, identifying highly proliferated clonotypes, determining the diversity of the cell repertoire found in a sample, comparing different states of the human immune system, and visualizing all relevant information. We here present IMEX, a software framework for the detailed characterization and visualization of the state of human IG and TR repertoires. IMEX offers a broad range of algorithms for statistical analysis of IG and TR data, CDR and V-(D)-J analysis, diversity analysis by calculating the distribution of IG and TR, calculating primer efficiency, and comparing multiple data sets. We use a mathematical model that is able to describe the number of unique clonotypes in a sample taking into account the true number of unique sequences and read errors; we heuristically optimize the parameters of this model. IMEX uses IMGT/HighV-QUEST analysis outputs and includes methods for splitting and merging to enable the submission to this portal and to combine the outputs results, respectively. All calculation results can be visualized and exported. IMEX is an user-friendly and flexible framework for performing clonality experiments based on CDR and V-(D)-J rearranged regions, diversity analysis, primer efficiency, and various different visualization experiments. Using IMEX, various immunological reactions and alterations can be investigated in detail. IMEX is freely available for Windows and Unix platforms at http://bioinformatics.fh-hagenberg.at/immunexplorer/ . |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 25% |
| Unknown | 3 | 75% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Italy | 1 | 2% |
| Unknown | 61 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 21 | 33% |
| Student > Ph. D. Student | 12 | 19% |
| Other | 6 | 10% |
| Professor | 6 | 10% |
| Student > Master | 4 | 6% |
| Other | 9 | 14% |
| Unknown | 5 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 19 | 30% |
| Biochemistry, Genetics and Molecular Biology | 10 | 16% |
| Immunology and Microbiology | 10 | 16% |
| Medicine and Dentistry | 5 | 8% |
| Computer Science | 3 | 5% |
| Other | 6 | 10% |
| Unknown | 10 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 03 February 2016.
All research outputs
#12,738,978
of 22,821,814 outputs
Outputs from BMC Bioinformatics
#3,625
of 7,286 outputs
Outputs of similar age
#113,986
of 264,494 outputs
Outputs of similar age from BMC Bioinformatics
#52
of 117 outputs
Altmetric has tracked 22,821,814 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,286 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 48th percentile – i.e., 48% 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 264,494 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.
We're also able to compare this research output to 117 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 54% of its contemporaries.