Genotype Phenotype Coupling
Springer US
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| Chapter title |
Single-Cell B-Cell Sequencing to Generate Natively Paired scFab Yeast Surface Display Libraries.
|
|---|---|
| Book title |
Genotype Phenotype Coupling
|
| Published in |
Methods in molecular biology, January 2023
|
| DOI | 10.1007/978-1-0716-3279-6_11 |
| Pubmed ID | |
| Book ISBNs |
978-1-07-163278-9, 978-1-07-163279-6
|
| Authors |
Pascual, Nathaniel, Belecciu, Theodore, Schmidt, Sam, Nakisa, Athar, Huang, Xuefei, Woldring, Daniel |
| Abstract |
The immune cell profiling capabilities of single-cell RNA sequencing (scRNA-seq) are powerful tools that can be applied to the design of theranostic monoclonal antibodies (mAbs). Using scRNA-seq to determine natively paired B-cell receptor (BCR) sequences of immunized mice as a starting point for design, this method outlines a simplified workflow to express single-chain antibody fragments (scFabs) on the surface of yeast for high-throughput characterization and further refinement with directed evolution experiments. While not extensively detailed in this chapter, this method easily accommodates the implementation of a growing body of in silico tools that improve affinity and stability among a range of other developability criteria (e.g., solubility and immunogenicity). |
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 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 1 | 100% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemical Engineering | 1 | 100% |
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 05 July 2023.
All research outputs
#16,298,350
of 24,010,679 outputs
Outputs from Methods in molecular biology
#5,651
of 13,545 outputs
Outputs of similar age
#246,653
of 440,311 outputs
Outputs of similar age from Methods in molecular biology
#245
of 624 outputs
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