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X Demographics
Mendeley readers
Attention Score in Context
| Title |
T-ALL and thymocytes: a message of noncoding RNAs
|
|---|---|
| Published in |
Journal of Hematology & Oncology, March 2017
|
| DOI | 10.1186/s13045-017-0432-0 |
| Pubmed ID | |
| Authors |
Annelynn Wallaert, Kaat Durinck, Tom Taghon, Pieter Van Vlierberghe, Frank Speleman |
| Abstract |
In the last decade, the role for noncoding RNAs in disease was clearly established, starting with microRNAs and later expanded towards long noncoding RNAs. This was also the case for T cell acute lymphoblastic leukemia, which is a malignant blood disorder arising from oncogenic events during normal T cell development in the thymus. By studying the transcriptomic profile of protein-coding genes, several oncogenic events leading to T cell acute lymphoblastic leukemia (T-ALL) could be identified. In recent years, it became apparent that several of these oncogenes function via microRNAs and long noncoding RNAs. In this review, we give a detailed overview of the studies that describe the noncoding RNAome in T-ALL oncogenesis and normal T cell development. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Belgium | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 1 | 2% |
| Unknown | 56 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 23% |
| Student > Master | 9 | 16% |
| Researcher | 8 | 14% |
| Student > Doctoral Student | 6 | 11% |
| Student > Bachelor | 4 | 7% |
| Other | 8 | 14% |
| Unknown | 9 | 16% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 29 | 51% |
| Medicine and Dentistry | 5 | 9% |
| Agricultural and Biological Sciences | 4 | 7% |
| Immunology and Microbiology | 2 | 4% |
| Neuroscience | 2 | 4% |
| Other | 4 | 7% |
| Unknown | 11 | 19% |
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 14 March 2018.
All research outputs
#17,883,247
of 22,959,818 outputs
Outputs from Journal of Hematology & Oncology
#873
of 1,194 outputs
Outputs of similar age
#221,370
of 307,998 outputs
Outputs of similar age from Journal of Hematology & Oncology
#34
of 43 outputs
Altmetric has tracked 22,959,818 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,194 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.0. This one is in the 22nd percentile – i.e., 22% 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 307,998 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.