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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Ordinary Differential Equation Models for Adoptive Immunotherapy
|
|---|---|
| Published in |
Bulletin of Mathematical Biology, April 2017
|
| DOI | 10.1007/s11538-017-0263-8 |
| Pubmed ID | |
| Authors |
Anne Talkington, Claudia Dantoin, Rick Durrett |
| Abstract |
Modified T cells that have been engineered to recognize the CD19 surface marker have recently been shown to be very successful at treating acute lymphocytic leukemias. Here, we explore four previous approaches that have used ordinary differential equations to model this type of therapy, compare their properties, and modify the models to address their deficiencies. Although the four models treat the workings of the immune system in slightly different ways, they all predict that adoptive immunotherapy can be successful to move a patient from the large tumor fixed point to an equilibrium with little or no tumor. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 4 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 50% |
| Members of the public | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 36 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 13 | 36% |
| Researcher | 7 | 19% |
| Student > Doctoral Student | 4 | 11% |
| Professor > Associate Professor | 3 | 8% |
| Student > Bachelor | 2 | 6% |
| Other | 2 | 6% |
| Unknown | 5 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 22% |
| Mathematics | 7 | 19% |
| Engineering | 4 | 11% |
| Biochemistry, Genetics and Molecular Biology | 3 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 2 | 6% |
| Other | 3 | 8% |
| Unknown | 9 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 06 August 2018.
All research outputs
#14,057,029
of 22,962,258 outputs
Outputs from Bulletin of Mathematical Biology
#590
of 1,102 outputs
Outputs of similar age
#167,696
of 309,562 outputs
Outputs of similar age from Bulletin of Mathematical Biology
#8
of 31 outputs
Altmetric has tracked 22,962,258 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,102 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 43rd percentile – i.e., 43% 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 309,562 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.