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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Gene Mutations as Emerging Biomarkers and Therapeutic Targets for Relapsed Acute Myeloid Leukemia
|
|---|---|
| Published in |
Frontiers in Pharmacology, December 2017
|
| DOI | 10.3389/fphar.2017.00897 |
| Pubmed ID | |
| Authors |
Habsah Aziz, Chow Y. Ping, Hamidah Alias, Nurul-Syakima Ab Mutalib, Rahman Jamal |
| Abstract |
It is believed that there are key differences in the genomic profile between adult and childhood acute myeloid leukemia (AML). Relapse is the significant contributor of mortality in patients with AML and remains as the leading cause of cancer death among children, posing great challenges in the treatment of AML. The knowledge about the genomic lesions in childhood AML is still premature as most genomic events defined in children were derived from adult cohorts. However, the emerging technologies of next generation sequencing have narrowed the gap of knowledge in the biology of AML by the detection of gene mutations for each sub-type which have led to the improvement in terms of prognostication as well as the use of targeted therapies. In this review, we describe the recent understanding of the genomic landscape including the prevalence of mutation, prognostic impact, and targeted therapies that will provide an insight into the pathogenesis of AML relapse in both adult and childhood cases. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 35 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 9 | 26% |
| Student > Bachelor | 5 | 14% |
| Student > Ph. D. Student | 3 | 9% |
| Student > Doctoral Student | 2 | 6% |
| Other | 2 | 6% |
| Other | 7 | 20% |
| Unknown | 7 | 20% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 31% |
| Biochemistry, Genetics and Molecular Biology | 8 | 23% |
| Immunology and Microbiology | 3 | 9% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 6% |
| Unspecified | 1 | 3% |
| Other | 3 | 9% |
| Unknown | 7 | 20% |
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 December 2017.
All research outputs
#20,454,971
of 23,011,300 outputs
Outputs from Frontiers in Pharmacology
#10,218
of 16,316 outputs
Outputs of similar age
#375,144
of 440,043 outputs
Outputs of similar age from Frontiers in Pharmacology
#157
of 259 outputs
Altmetric has tracked 23,011,300 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 16,316 research outputs from this source. They receive a mean Attention Score of 5.0. 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 440,043 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 259 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.