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X Demographics
Mendeley readers
Attention Score in Context
| Title |
DNA and RNA analyses in detection of genetic predisposition to cancer
|
|---|---|
| Published in |
Hereditary Cancer in Clinical Practice, December 2012
|
| DOI | 10.1186/1897-4287-10-17 |
| Pubmed ID | |
| Authors |
Grzegorz Kurzawski, Dagmara Dymerska, Pablo Serrano-Fernández, Joanna Trubicka, Bartłomiej Masojć, Anna Jakubowska, Rodney J Scott |
| Abstract |
During the past decade many new molecular methods for DNA and RNA analysis have emerged. The most popular thus far have been SSCP, HET, CMC, DGGE, RFLP or ASA, which have now been replaced by methods that are more cost effective and less time consuming. Real-time amplification techniques and particularly those with the capacity of multiplexing have become commonly used in laboratory practice. Novel screening methods enable the very rapid examination of large patients series. Use of liquid handling robotics applied to the isolation of DNA or RNA, the normalisation of sample concentration, and standardization of target amplification by PCR have also contributed to a reduced risk of sample contamination and have resulted in laboratory analysis being easier and faster.The aim of this study is the introduction of a few modern techniques, most commonly used in detection of genetic predisposition to cancer. |
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 % |
|---|---|---|
| France | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 24 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 21% |
| Student > Bachelor | 4 | 17% |
| Student > Master | 4 | 17% |
| Student > Ph. D. Student | 4 | 17% |
| Student > Doctoral Student | 1 | 4% |
| Other | 3 | 13% |
| Unknown | 3 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 8 | 33% |
| Engineering | 3 | 13% |
| Biochemistry, Genetics and Molecular Biology | 3 | 13% |
| Medicine and Dentistry | 3 | 13% |
| Environmental Science | 1 | 4% |
| Other | 1 | 4% |
| Unknown | 5 | 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 04 December 2012.
All research outputs
#22,759,802
of 25,374,917 outputs
Outputs from Hereditary Cancer in Clinical Practice
#215
of 260 outputs
Outputs of similar age
#256,140
of 286,230 outputs
Outputs of similar age from Hereditary Cancer in Clinical Practice
#5
of 6 outputs
Altmetric has tracked 25,374,917 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 260 research outputs from this source. They receive a mean Attention Score of 4.8. 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 286,230 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 6 others from the same source and published within six weeks on either side of this one.