ArticleeLife2023
The landscape of antibody binding affinity in SARS-CoV-2 Omicron BA.1 evolution.
Article in eLife, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
42 citing papers in PubMed, 69 citations in OpenAlex.
- From sites to structure to serology: a roadmap for structure-aware molecular evolution of antigenically evolving viruses.Journal of virology · 2026Review
- Amplicon/Protein Bead Display enables quantitativebioRxiv : the preprint server for biology · 2026Article
- Inference of fitness landscapes with heterogeneous patterns of epistasis across sites.bioRxiv : the preprint server for biology · 2026Article
- Epistasis and background dependence in the evolution of Omicron variants of the SARS-CoV-2 spike protein.Molecular biology and evolution · 2026Article
- Functional and antigenic constraints on the Nipah virus fusion protein.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Inference and Visualization of Complex Genotype-Phenotype Maps.Molecular biology and evolution · 2026Article
- Characterization of the heterogeneity in SARS-CoV-2 fitness dynamics via graph representation learning.PLoS computational biology · 2026Article
- Functional and antigenic constraints on the Nipah virus fusion protein.bioRxiv : the preprint server for biology · 2026Article
- Modelling the Variability in Immunity Build-Up and Waning Following RNA-Based Vaccination.Viruses · 2025Article
- Epistasis and background dependence in the evolution of Omicron variants of the SARS-CoV-2 Spike protein.bioRxiv : the preprint server for biology · 2025Article
- Distinguishing direct interactions from global epistasis using rank statistics.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- Inference and visualization of complex genotype-phenotype maps withbioRxiv : the preprint server for biology · 2025Article
- Learning sequence-function relationships with scalable, interpretable Gaussian processes.bioRxiv : the preprint server for biology · 2025Article
- Article
- Mechanistic modeling or machine learning for detecting variants of concern: Why not both?Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Predicting high-fitness viral protein variants with Bayesian active learning and biophysics.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Efficient Searches in Protein Sequence Space Through AI-Driven Iterative Learning.International journal of molecular sciences · 2025Article
- Generative prediction of real-world prevalent SARS-CoV-2 mutation with in silico virus evolution.Briefings in bioinformatics · 2025Article
- A systematic evaluation of the language-of-viral-escape model using multiple machine learning frameworks.Journal of the Royal Society, Interface · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
Abstract
The Omicron BA.1 variant of SARS-CoV-2 escapes convalescent sera and monoclonal antibodies that are effective against earlier strains of the virus. This immune evasion is largely a consequence of mutations in the BA.1 receptor binding domain (RBD), the major antigenic target of SARS-CoV-2. Previous studies have identified several key RBD mutations leading to escape from most antibodies. However, little is known about how these escape mutations interact with each other and with other mutations in the RBD. Here, we systematically map these interactions by measuring the binding affinity of all possible combinations of these 15 RBD mutations (2
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.