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Attention Score in Context
| Title |
Transcript features alone enable accurate prediction and understanding of gene expression in S. cerevisiae
|
|---|---|
| Published in |
BMC Bioinformatics, October 2013
|
| DOI | 10.1186/1471-2105-14-s15-s1 |
| Pubmed ID | |
| Authors |
Hadas Zur, Tamir Tuller |
| Abstract |
Gene expression is a central process in all living organisms. Central questions in the field are related to the way the expression levels of genes are encoded in the transcripts and affect their evolution, and the potential to predict expression levels solely by transcript features. In this study we analyze S. cerevisiae, a model organism with the most abundant relevant cellular and genomic measurements, to evaluate the accuracy in which expression levels can be predicted by different parts of the transcript. To this end, we perform various types of regression analyses based on a total of 5323 features of the transcript. The main advantage of the proposed predictors over previous ones is related to the accurate and comprehensive definitions of the relevant transcript features, which are based on biophysical knowledge of the gene transcription and translation processes, their modeling and evolution. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| Israel | 1 | 2% |
| Netherlands | 1 | 2% |
| Unknown | 42 | 93% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 12 | 27% |
| Researcher | 7 | 16% |
| Student > Master | 5 | 11% |
| Student > Postgraduate | 4 | 9% |
| Professor | 3 | 7% |
| Other | 4 | 9% |
| Unknown | 10 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 20 | 44% |
| Biochemistry, Genetics and Molecular Biology | 9 | 20% |
| Computer Science | 3 | 7% |
| Mathematics | 1 | 2% |
| Medicine and Dentistry | 1 | 2% |
| Other | 1 | 2% |
| Unknown | 10 | 22% |
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 27 May 2014.
All research outputs
#20,230,558
of 22,756,196 outputs
Outputs from BMC Bioinformatics
#6,844
of 7,271 outputs
Outputs of similar age
#184,077
of 210,819 outputs
Outputs of similar age from BMC Bioinformatics
#101
of 107 outputs
Altmetric has tracked 22,756,196 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,271 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 1st percentile – i.e., 1% 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 210,819 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 107 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.