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Mendeley readers
Attention Score in Context
| Title |
Use of high-density tiling microarrays to identify mutations globally and elucidate mechanisms of drug resistance in Plasmodium falciparum
|
|---|---|
| Published in |
Genome Biology, February 2009
|
| DOI | 10.1186/gb-2009-10-2-r21 |
| Pubmed ID | |
| Authors |
Neekesh V Dharia, Amar Bir Singh Sidhu, María Belén Cassera, Scott J Westenberger, Selina ER Bopp, Rich T Eastman, David Plouffe, Serge Batalov, Daniel J Park, Sarah K Volkman, Dyann F Wirth, Yingyao Zhou, David A Fidock, Elizabeth A Winzeler |
| Abstract |
The identification of genetic changes that confer drug resistance or other phenotypic changes in pathogens can help optimize treatment strategies, support the development of new therapeutic agents, and provide information about the likely function of genes. Elucidating mechanisms of phenotypic drug resistance can also assist in identifying the mode of action of uncharacterized but potent antimalarial compounds identified in high-throughput chemical screening campaigns against Plasmodium falciparum. |
Mendeley readers
The data shown below were compiled from readership statistics for 99 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 2 | 2% |
| Switzerland | 1 | 1% |
| Burkina Faso | 1 | 1% |
| Japan | 1 | 1% |
| United States | 1 | 1% |
| Unknown | 93 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 31 | 31% |
| Researcher | 24 | 24% |
| Student > Master | 9 | 9% |
| Professor | 7 | 7% |
| Professor > Associate Professor | 6 | 6% |
| Other | 15 | 15% |
| Unknown | 7 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 48 | 48% |
| Biochemistry, Genetics and Molecular Biology | 16 | 16% |
| Chemistry | 9 | 9% |
| Medicine and Dentistry | 6 | 6% |
| Veterinary Science and Veterinary Medicine | 2 | 2% |
| Other | 9 | 9% |
| Unknown | 9 | 9% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 01 March 2015.
All research outputs
#8,535,472
of 25,374,917 outputs
Outputs from Genome Biology
#3,489
of 4,467 outputs
Outputs of similar age
#54,955
of 189,056 outputs
Outputs of similar age from Genome Biology
#10
of 24 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,467 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.6. This one is in the 14th percentile – i.e., 14% 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 189,056 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 17th percentile – i.e., 17% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 24 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.