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Mendeley readers
Attention Score in Context
| Chapter title |
Transposable Elements and Their Identification
|
|---|---|
| Chapter number | 12 |
| Book title |
Evolutionary Genomics
|
| Published in |
Methods in molecular biology, February 2012
|
| DOI | 10.1007/978-1-61779-582-4_12 |
| Pubmed ID | |
| Book ISBNs |
978-1-61779-581-7, 978-1-61779-582-4
|
| Authors |
Wojciech MakaÅowski, Amit Pande, Valer Gotea, Izabela MakaÅowska, Wojciech Makałowski, Izabela Makałowska |
| Editors |
Maria Anisimova |
| Abstract |
Most genomes are populated by thousands of sequences that originated from mobile elements. On the one hand, these sequences present a real challenge in the process of genome analysis and annotation. On the other hand, there are very interesting biological subjects involved in many cellular processes. Here, we present an overview of transposable elements (TEs) biodiversity and their impact on genomic evolution. Finally, we discuss different approaches to the TEs detection and analyses. |
Mendeley readers
The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 3 | 4% |
| Sweden | 1 | 1% |
| Canada | 1 | 1% |
| United States | 1 | 1% |
| Poland | 1 | 1% |
| Unknown | 63 | 90% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 17 | 24% |
| Researcher | 14 | 20% |
| Student > Master | 6 | 9% |
| Student > Bachelor | 6 | 9% |
| Student > Doctoral Student | 5 | 7% |
| Other | 11 | 16% |
| Unknown | 11 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 33 | 47% |
| Biochemistry, Genetics and Molecular Biology | 14 | 20% |
| Medicine and Dentistry | 3 | 4% |
| Environmental Science | 2 | 3% |
| Computer Science | 2 | 3% |
| Other | 5 | 7% |
| Unknown | 11 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 12. 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 December 2014.
All research outputs
#2,449,871
of 22,709,015 outputs
Outputs from Methods in molecular biology
#451
of 13,077 outputs
Outputs of similar age
#20,499
of 247,695 outputs
Outputs of similar age from Methods in molecular biology
#32
of 459 outputs
Altmetric has tracked 22,709,015 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,077 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 96% 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 247,695 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 459 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.