ReviewFrontiers in immunology2017
How B-Cell Receptor Repertoire Sequencing Can Be Enriched with Structural Antibody Data.
Review in Frontiers in immunology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
25 citing papers in PubMed.
- Phased fragility and stability of non-genetic B cell states in the germinal center accelerate the genetic evolution of antibodies.Cell systems · 2026Article
- Deep generative modeling captures maturation-dependent pairing patterns in human antibodies.iScience · 2026Article
- Comparison of sequence- and structure-based antibody clustering approaches on simulated repertoire sequencing data.PLoS computational biology · 2025Article
- Computational detection of antigen-specific B cell receptors following immunization.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Detection of disease-specific signatures in B cell repertoires of lymphomas using machine learning.PLoS computational biology · 2024Article
- Article
- Structural modeling of antibody variable regions using deep learning-progress and perspectives on drug discovery.Frontiers in molecular biosciences · 2023Review
- Exploring the impact of clonal definition on B-cell diversity: implications for the analysis of immune repertoires.Frontiers in immunology · 2023Article
- Machine-designed biotherapeutics: opportunities, feasibility and advantages of deep learning in computational antibody discovery.Briefings in bioinformatics · 2022Review
- Deciphering the language of antibodies using self-supervised learning.Patterns (New York, N.Y.) · 2022Article
- Rapid On-Cell Selection of High-Performance Human Antibodies.ACS central science · 2022Article
- Advances in antibody discovery from human BCR repertoires.Frontiers in bioinformatics · 2022Review
- Epitope profiling using computational structural modelling demonstrated on coronavirus-binding antibodies.PLoS computational biology · 2021Article
- Public Baseline and shared response structures support the theory of antibody repertoire functional commonality.PLoS computational biology · 2021Article
- How repertoire data are changing antibody science.The Journal of biological chemistry · 2020Review
- Article
- Computational Model Reveals a Stochastic Mechanism behind Germinal Center Clonal Bursts.Cells · 2020Article
- Structural diversity of B-cell receptor repertoires along the B-cell differentiation axis in humans and mice.PLoS computational biology · 2020Article
- Maturation of the Human Immunoglobulin Heavy Chain Repertoire With Age.Frontiers in immunology · 2020Article
- Comparative Analysis of the CDR Loops of Antigen Receptors.Frontiers in immunology · 2019Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Next-generation sequencing of immunoglobulin gene repertoires (Ig-seq) allows the investigation of large-scale antibody dynamics at a sequence level. However, structural information, a crucial descriptor of antibody binding capability, is not collected in Ig-seq protocols. Developing systematic relationships between the antibody sequence information gathered from Ig-seq and low-throughput techniques such as X-ray crystallography could radically improve our understanding of antibodies. The mapping of Ig-seq datasets to known antibody structures can indicate structurally, and perhaps functionally, uncharted areas. Furthermore, contrasting naïve and antigenically challenged datasets using structural antibody descriptors should provide insights into antibody maturation. As the number of antibody structures steadily increases and more and more Ig-seq datasets become available, the opportunities that arise from combining the two types of information increase as well. Here, we review how these data types enrich one another and show potential for advancing our knowledge of the immune system and improving antibody engineering.
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