The DOI matches its Crossref record; 94 of the 96 references it cites were found in a registry or an index.
Observed Antibody Space: A Resource for Data Mining Next-Generation Sequencing of Antibody Repertoires
Open accessPublished version of a preprint
Abstract
Abs are immune system proteins that recognize noxious molecules for elimination. Their sequence diversity and binding versatility have made Abs the primary class of biopharmaceuticals. Recently, it has become possible to query their immense natural diversity using next-generation sequencing of Ig gene repertoires (Ig-seq). However, Ig-seq outputs are currently fragmented across repositories and tend to be presented as raw nucleotide reads, which means nontrivial effort is required to reuse the data for analysis. To address this issue, we have collected Ig-seq outputs from 55 studies, covering more than half a billion Ab sequences across diverse immune states, organisms (primarily human and mouse), and individuals. We have sorted, cleaned, annotated, translated, and numbered these sequences and make the data available via our Observed Antibody Space (OAS) resource at http://antibodymap.org The data within OAS will be regularly updated with newly released Ig-seq datasets. We believe OAS will facilitate data mining of immune repertoires for improved understanding of the immune system and development of better biotherapeutics.
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“The increasing number of structural [16], sequence [17] and experimental data [18–21] on antibodies being deposited in the public domain provides the necessary foundation for improving such data-driven methods.”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [17]
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“In this respect, the field currently benefits from a steady stream of new data from NGS of B-cell Receptors (BCRs, to be used as proxy for antibodies) [212, 213] and there is an increasing number of resources available for downloading such data [17], which are being used to analyze therapeutic antibodies [13].”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [17]
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Cited by
Sorted by citations
CoV-AbDab: the coronavirus antibody database
Raybould, M. I. J., Kovaltsuk, A., Marks, C., & Deane, C. M. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btaa739 · Cited by 383
Self-citationFive computational developability guidelines for therapeutic antibody profiling
Raybould, M. I. J., Marks, C., Krawczyk, K., Taddese, B., Nowak, J., Lewis, A. P., Bujotzek, A., Shi, J., & Deane, C. M. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1810576116 · Cited by 357
Self-citationFast, accurate antibody structure prediction from deep learning on massive set of natural antibodies
Ruffolo, J. A., Chu, L., Mahajan, S. P., & Gray, J. J. (2023) · Nature Communications · doi:10.1038/s41467-023-38063-x · Cited by 364
Olsen, T. H., Boyles, F., & Deane, C. M. (2022) · Protein Science · doi:10.1002/pro.4205 · Cited by 319
Self-citationImmuneBuilder: Deep-Learning models for predicting the structures of immune proteins
Abanades, B., Wong, W. K., Boyles, F., Georges, G. J., Bujotzek, A., & Deane, C. M. (2023) · Communications Biology · doi:10.1038/s42003-023-04927-7 · Cited by 323
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Metadata
- Authors
- Kovaltsuk, A., Leem, J., Kelm, S., Snowden, J., Deane, C. M., & Krawczyk, K.
- Affiliations
- University of Oxford (GB)
- UCB Pharma (United Kingdom) (GB)
- Corresponding author
- Deane, Charlotte M
- Krawczyk, Konrad
- ORCID
- Venue
- The Journal of Immunology
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-10
- Volume
- 201
- Issue
- 8
- Pages
- 2502-2509
- ISSN
- 0022-1767 (ISSN-L)
- 1550-6606
- OpenAlex
- W2950118240
- Cited by
- 247
- References
- 96
- Citations by year
- 2026: 34 · 2025: 46 · 2024: 48 · 2023: 33 · 2022: 33 · 2021: 21 · 2020: 17 · 2019: 12 · 2018: 3
- FWCI
- 9.15
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- The Journal of Immunology (publishedVersion, other-oa)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Directorate for Biological Sciences
- Biotechnology and Biological Sciences Research Council (1801486, BB/M011224, BB/M011224/1, M011224)
- UCB Pharma
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Monoclonal and Polyclonal Antibodies Research
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › vaccines and immunoinformatics approaches
- Keywords
- antibody repertoire, biologic therapy
- MeSH terms
- Animals, Antibodies, Antibody Diversity, Humans, Immunoglobulins, Immunotherapy, Databases, Genetic, Mice, Immunity, Humoral, Data Mining, Molecular Sequence Annotation, High-Throughput Nucleotide Sequencing
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