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Mendeley readers
Attention Score in Context
| Title |
Array-based techniques for fingerprinting medicinal herbs
|
|---|---|
| Published in |
Chinese Medicine, May 2011
|
| DOI | 10.1186/1749-8546-6-18 |
| Pubmed ID | |
| Authors |
Linhai Niu, Nitin Mantri, Chun Guang Li, Charlie Xue, Edwin Pang |
| Abstract |
Poor quality control of medicinal herbs has led to instances of toxicity, poisoning and even deaths. The fundamental step in quality control of herbal medicine is accurate identification of herbs. Array-based techniques have recently been adapted to authenticate or identify herbal plants. This article reviews the current array-based techniques, eg oligonucleotides microarrays, gene-based probe microarrays, Suppression Subtractive Hybridization (SSH)-based arrays, Diversity Array Technology (DArT) and Subtracted Diversity Array (SDA). We further compare these techniques according to important parameters such as markers, polymorphism rates, restriction enzymes and sample type. The applicability of the array-based methods for fingerprinting depends on the availability of genomics and genetics of the species to be fingerprinted. For the species with few genome sequence information but high polymorphism rates, SDA techniques are particularly recommended because they require less labour and lower material cost. |
Mendeley readers
The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Indonesia | 1 | 3% |
| Unknown | 39 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 8 | 20% |
| Student > Ph. D. Student | 7 | 18% |
| Researcher | 6 | 15% |
| Student > Master | 4 | 10% |
| Student > Postgraduate | 3 | 8% |
| Other | 5 | 13% |
| Unknown | 7 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 33% |
| Biochemistry, Genetics and Molecular Biology | 9 | 23% |
| Medicine and Dentistry | 5 | 13% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 8% |
| Immunology and Microbiology | 1 | 3% |
| Other | 3 | 8% |
| Unknown | 6 | 15% |
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 18 August 2011.
All research outputs
#22,759,802
of 25,374,917 outputs
Outputs from Chinese Medicine
#517
of 660 outputs
Outputs of similar age
#115,367
of 123,560 outputs
Outputs of similar age from Chinese Medicine
#8
of 11 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 660 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. 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 123,560 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 11 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.