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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Expression of Exogenous Genes in Murine Primary B Cells and B Cell Lines Using Retroviral Vectors
|
|---|---|
| Chapter number | 3 |
| Book title |
B Cell Receptor Signaling
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7474-0_3 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7473-3, 978-1-4939-7474-0
|
| Authors |
Zhiyong Yang, Christopher D. C. Allen |
| Abstract |
B cells, after activation, can undergo class-switch recombination and somatic hypermutation of their immunoglobulin genes, and can differentiate into memory cells and plasma cells. Expressing genes in altered versions in primary B cells and B cell lines is an important approach to understanding how B cell receptor signaling leads to B cell activation and differentiation. Recombinant retrovirus-based transduction is the most efficient method to deliver exogenous genes for expression in B cells. In this chapter, we describe streamlined protocols for using recombinant retroviral vectors to transduce both murine primary B cells and B cell lines. |
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 % |
|---|---|---|
| Unknown | 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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 13 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 23% |
| Student > Ph. D. Student | 2 | 15% |
| Professor | 1 | 8% |
| Student > Master | 1 | 8% |
| Unknown | 6 | 46% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 2 | 15% |
| Medicine and Dentistry | 2 | 15% |
| Immunology and Microbiology | 2 | 15% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 8% |
| Unknown | 6 | 46% |
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 02 February 2018.
All research outputs
#15,490,822
of 23,020,670 outputs
Outputs from Methods in molecular biology
#5,388
of 13,166 outputs
Outputs of similar age
#269,787
of 442,354 outputs
Outputs of similar age from Methods in molecular biology
#596
of 1,498 outputs
Altmetric has tracked 23,020,670 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 13,166 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 44th percentile – i.e., 44% 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 442,354 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1,498 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.