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Mendeley readers
Attention Score in Context
| Chapter title |
Analysis of the Distribution Profiles of Circulating MicroRNAs by Asymmetrical Flow Field Flow Fractionation.
|
|---|---|
| Chapter number | 15 |
| Book title |
MicroRNA Profiling
|
| Published in |
Methods in molecular biology, January 2017
|
| DOI | 10.1007/978-1-4939-6524-3_15 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6522-9, 978-1-4939-6524-3
|
| Authors |
Kenneth Flack, Luis A. Jimenez, Wenwan Zhong, Flack, Kenneth, Jimenez, Luis A, Zhong, Wenwan |
| Editors |
Sweta Rani |
| Abstract |
MicroRNAs (miRNAs) are stably present in circulatory systems. They are bound to various carriers like proteins, lipoprotein particles, and exosomes. Investigating the process of miRNA distribution among these carriers will help improve our understanding of their functions in the extracellular environment and their potential relationship with diseases. Here, we describe how to obtain the distribution profiles of circulating miRNAs by separation of different miRNA carriers in human serum with asymmetrical flow field flow fractionation (AF4), and detection of the miRNAs in the eluted fractions that enrich particular types of carriers with RT-qPCR. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 19 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 26% |
| Student > Doctoral Student | 3 | 16% |
| Student > Master | 2 | 11% |
| Researcher | 2 | 11% |
| Professor | 2 | 11% |
| Other | 5 | 26% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 26% |
| Chemistry | 4 | 21% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 11% |
| Engineering | 2 | 11% |
| Immunology and Microbiology | 2 | 11% |
| Other | 4 | 21% |
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 01 December 2016.
All research outputs
#17,826,759
of 22,901,818 outputs
Outputs from Methods in molecular biology
#7,246
of 13,134 outputs
Outputs of similar age
#293,467
of 420,455 outputs
Outputs of similar age from Methods in molecular biology
#637
of 1,074 outputs
Altmetric has tracked 22,901,818 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,134 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 39th percentile – i.e., 39% 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 420,455 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,074 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.