| Title |
Bottlenecks Caused by Software Gaps in miRNA and RNAi Research
|
|---|---|
| Published in |
Pharmaceutical Research, February 2012
|
| DOI | 10.1007/s11095-012-0712-x |
| Pubmed ID | |
| Authors |
Sean Ekins, Ron Shigeta, Barry A. Bunin |
| Abstract |
Understanding the regulation of gene expression is critical to many areas of biology while control via RNAs has found considerable interest as a tool for scientific discovery and potential therapeutic applications. For example whole genome RNA interference (RNAi) screens and whole proteome scans provide views of how the entire transcriptome or proteome responds to biological, chemical or environmental perturbations of a gene's activity. Small RNA (sRNA) or MicroRNA (miRNA) are known to regulate pathways and bind mRNA, while the function of miRNAs discovered in experimental studies is often unknown. In both cases, RNAi and miRNA require labor intensive studies to tease out their functions within gene networks. Available software to analyze relationships is currently an ad hoc and often a manual process that can take up to several hours to analyze a single candidate RNAi or miRNA. With experiments frequently highlighting tens to hundreds of candidates this represents a considerable bottleneck. We suggest there is a gap in miRNA and RNAi research caused by inadequate current software that could be improved. For example a new software application could be created that provides interactive, comprehensive target analysis that leverages past datasets to lead to statistically stronger analyses. |
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 % |
|---|---|---|
| France | 1 | 33% |
| United States | 1 | 33% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 12% |
| Unknown | 15 | 88% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 6 | 35% |
| Student > Ph. D. Student | 3 | 18% |
| Other | 2 | 12% |
| Student > Master | 2 | 12% |
| Student > Bachelor | 1 | 6% |
| Other | 2 | 12% |
| Unknown | 1 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 41% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 12% |
| Medicine and Dentistry | 2 | 12% |
| Biochemistry, Genetics and Molecular Biology | 1 | 6% |
| Economics, Econometrics and Finance | 1 | 6% |
| Other | 3 | 18% |
| Unknown | 1 | 6% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 07 April 2016.
All research outputs
#15,245,883
of 22,668,244 outputs
Outputs from Pharmaceutical Research
#2,232
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Outputs of similar age
#99,692
of 155,606 outputs
Outputs of similar age from Pharmaceutical Research
#24
of 31 outputs
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