| Title |
ATGC transcriptomics: a web-based application to integrate, explore and analyze de novo transcriptomic data
|
|---|---|
| Published in |
BMC Bioinformatics, February 2017
|
| DOI | 10.1186/s12859-017-1494-2 |
| Pubmed ID | |
| Authors |
Sergio Gonzalez, Bernardo Clavijo, Máximo Rivarola, Patricio Moreno, Paula Fernandez, Joaquín Dopazo, Norma Paniego |
| Abstract |
In the last years, applications based on massively parallelized RNA sequencing (RNA-seq) have become valuable approaches for studying non-model species, e.g., without a fully sequenced genome. RNA-seq is a useful tool for detecting novel transcripts and genetic variations and for evaluating differential gene expression by digital measurements. The large and complex datasets resulting from functional genomic experiments represent a challenge in data processing, management, and analysis. This problem is especially significant for small research groups working with non-model species. We developed a web-based application, called ATGC transcriptomics, with a flexible and adaptable interface that allows users to work with new generation sequencing (NGS) transcriptomic analysis results using an ontology-driven database. This new application simplifies data exploration, visualization, and integration for a better comprehension of the results. ATGC transcriptomics provides access to non-expert computer users and small research groups to a scalable storage option and simple data integration, including database administration and management. The software is freely available under the terms of GNU public license at http://atgcinta.sourceforge.net . |
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 % |
|---|---|---|
| Argentina | 1 | 20% |
| Spain | 1 | 20% |
| France | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 40% |
| Scientists | 2 | 40% |
| Practitioners (doctors, other healthcare professionals) | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Argentina | 1 | 3% |
| Unknown | 39 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 33% |
| Student > Ph. D. Student | 7 | 18% |
| Student > Doctoral Student | 6 | 15% |
| Student > Bachelor | 5 | 13% |
| Professor | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 5 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 16 | 40% |
| Biochemistry, Genetics and Molecular Biology | 7 | 18% |
| Nursing and Health Professions | 3 | 8% |
| Medicine and Dentistry | 3 | 8% |
| Computer Science | 2 | 5% |
| Other | 4 | 10% |
| Unknown | 5 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 09 March 2017.
All research outputs
#3,458,078
of 23,881,329 outputs
Outputs from BMC Bioinformatics
#1,231
of 7,454 outputs
Outputs of similar age
#63,751
of 313,088 outputs
Outputs of similar age from BMC Bioinformatics
#22
of 139 outputs
Altmetric has tracked 23,881,329 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,454 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done well, scoring higher than 83% 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 313,088 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 79% of its contemporaries.
We're also able to compare this research output to 139 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.