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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Engineering Antibodies for the Treatment of Infectious Diseases
|
|---|---|
| Chapter number | 10 |
| Book title |
Recombinant Antibodies for Infectious Diseases
|
| Published in |
Advances in experimental medicine and biology, January 2017
|
| DOI | 10.1007/978-3-319-72077-7_10 |
| Pubmed ID | |
| Book ISBNs |
978-3-31-972076-0, 978-3-31-972077-7
|
| Authors |
Fan, Gaowei, Li, Jinming |
| Abstract |
Historically, serum therapy was previously used to combat infectious pathogens. However, serum sickness and anaphylaxis limited its broad application. The advancement of antibody engineering technologies has made it feasible to generate monoclonal antibodies. There are divergent methods for antibody engineering and optimization. In this chapter, we summarized the latest developments in engineering antibodies for infectious diseases. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Canada | 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 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 20 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 5 | 25% |
| Student > Ph. D. Student | 3 | 15% |
| Student > Doctoral Student | 3 | 15% |
| Researcher | 2 | 10% |
| Student > Master | 2 | 10% |
| Other | 2 | 10% |
| Unknown | 3 | 15% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 5 | 25% |
| Immunology and Microbiology | 3 | 15% |
| Medicine and Dentistry | 2 | 10% |
| Unspecified | 1 | 5% |
| Computer Science | 1 | 5% |
| Other | 4 | 20% |
| Unknown | 4 | 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 10 September 2018.
All research outputs
#15,505,836
of 23,043,346 outputs
Outputs from Advances in experimental medicine and biology
#2,518
of 4,971 outputs
Outputs of similar age
#257,527
of 421,409 outputs
Outputs of similar age from Advances in experimental medicine and biology
#235
of 490 outputs
Altmetric has tracked 23,043,346 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,971 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 37th percentile – i.e., 37% 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 421,409 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 490 others from the same source and published within six weeks on either side of this one. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.