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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Borrelia burgdorferi Transcriptome Analysis by RNA-Sequencing
|
|---|---|
| Chapter number | 11 |
| Book title |
Borrelia burgdorferi
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7383-5_11 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7382-8, 978-1-4939-7383-5
|
| Authors |
M Lybecker, KC Henderson |
| Abstract |
Next-Generation Sequencing (NGS) has revolutionized transcriptomics studies in the last decade. Transcriptome analysis experiments using NGS-based RNA-sequencing have several advantages over DNA microarray analysis. Novel unannotated transcripts and transcriptional start sites can be identified. Differential gene expression can be determined on novel and annotated transcripts simultaneously, whereas DNA microarray analysis can only quantify changes of known genes. In the protocol below we describe an Illumina compatible ligation-based method for generating stranded cDNA libraries for total RNA and small RNA transcriptomes in Borrelia burgdorferi. |
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 % |
|---|---|---|
| Canada | 1 | 33% |
| Unknown | 2 | 67% |
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 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 6 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 33% |
| Professor | 1 | 17% |
| Researcher | 1 | 17% |
| Student > Master | 1 | 17% |
| Unknown | 1 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Immunology and Microbiology | 2 | 33% |
| Biochemistry, Genetics and Molecular Biology | 1 | 17% |
| Agricultural and Biological Sciences | 1 | 17% |
| Computer Science | 1 | 17% |
| Unknown | 1 | 17% |
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 25 January 2020.
All research outputs
#15,815,423
of 25,483,400 outputs
Outputs from Methods in molecular biology
#4,505
of 14,221 outputs
Outputs of similar age
#248,398
of 450,166 outputs
Outputs of similar age from Methods in molecular biology
#410
of 1,486 outputs
Altmetric has tracked 25,483,400 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 14,221 research outputs from this source. They receive a mean Attention Score of 3.5. This one has gotten more attention than average, scoring higher than 66% 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 450,166 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,486 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 70% of its contemporaries.