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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Comprehensive Mitochondrial Genome Analysis by Massively Parallel Sequencing.
|
|---|---|
| Chapter number | 1 |
| Book title |
Mitochondrial DNA
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3040-1_1 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3039-5, 978-1-4939-3040-1
|
| Authors |
Palculict, Meagan E, Zhang, Victor Wei, Wong, Lee-Jun, Wang, Jing, Meagan E. Palculict, Victor Wei Zhang, Lee-Jun Wong, Jing Wang |
| Abstract |
Next-generation sequencing (NGS) based on massively parallel sequencing (MPS) of the entire 16,569 bp mitochondrial genome generates thousands of reads for each nucleotide position. The high-throughput sequence data generated allow the detection of mitochondrial DNA (mtDNA) point mutations and deletions with the ability to accurately quantify the mtDNA point mutation heteroplasmy and to determine the deletion breakpoints. In addition, this method is particularly sensitive for the detection of low-level mtDNA large deletions and multiple deletions. It is by far the most powerful tool for molecular diagnosis of mtDNA disorders. |
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 % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 23 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor > Associate Professor | 5 | 22% |
| Researcher | 4 | 17% |
| Student > Bachelor | 3 | 13% |
| Student > Doctoral Student | 2 | 9% |
| Other | 1 | 4% |
| Other | 3 | 13% |
| Unknown | 5 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 9 | 39% |
| Agricultural and Biological Sciences | 4 | 17% |
| Neuroscience | 2 | 9% |
| Veterinary Science and Veterinary Medicine | 1 | 4% |
| Medicine and Dentistry | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 5 | 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 07 September 2016.
All research outputs
#18,159,399
of 23,327,904 outputs
Outputs from Methods in molecular biology
#7,413
of 13,337 outputs
Outputs of similar age
#270,617
of 396,143 outputs
Outputs of similar age from Methods in molecular biology
#759
of 1,474 outputs
Altmetric has tracked 23,327,904 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 13,337 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 396,143 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,474 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.