You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Identification of Long Noncoding RNAs Associated to Human Disease Susceptibility
|
|---|---|
| Chapter number | 10 |
| Book title |
Promoter Associated RNA
|
| Published in |
Methods in molecular biology, March 2017
|
| DOI | 10.1007/978-1-4939-6716-2_10 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-6714-8, 978-1-4939-6716-2
|
| Authors |
Magistri, Marco, Velmeshev, Dmitry, Marco Magistri, Dmitry Velmeshev |
| Editors |
Sara Napoli |
| Abstract |
Transcriptomic as well as in vivo studies have revealed the importance of several lncRNAs in many complex diseases including cancer, cardiovascular, and neurological disorders. In this protocol, we describe how to perform RNAseq data analysis to identify lncRNAs associated with disease states utilizing the open-source software CANEapp (application for Comprehensive automated Analysis of Next-generation sequencing Experiments). |
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 % |
|---|---|---|
| United States | 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 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 7 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 3 | 43% |
| Student > Postgraduate | 1 | 14% |
| Professor > Associate Professor | 1 | 14% |
| Student > Master | 1 | 14% |
| Unknown | 1 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 3 | 43% |
| Agricultural and Biological Sciences | 1 | 14% |
| Medicine and Dentistry | 1 | 14% |
| Neuroscience | 1 | 14% |
| Unknown | 1 | 14% |
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 30 March 2017.
All research outputs
#20,412,387
of 22,962,258 outputs
Outputs from Methods in molecular biology
#9,919
of 13,136 outputs
Outputs of similar age
#268,927
of 308,511 outputs
Outputs of similar age from Methods in molecular biology
#237
of 303 outputs
Altmetric has tracked 22,962,258 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 13,136 research outputs from this source. They receive a mean Attention Score of 3.4. 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 308,511 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 303 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.