ReviewImmunological reviews2018
iReceptor: A platform for querying and analyzing antibody/B-cell and T-cell receptor repertoire data across federated repositories.
Review in Immunological reviews, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 112 papers, 1 of them a synthesis that pooled it.
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
112 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Anchor Clustering for million-scale immune repertoire sequencing data.BMC bioinformatics · 2024Pooled it
- What Do Generative Models Learn About Adaptive Immune Receptor Repertoires? A Benchmark Study.bioRxiv : the preprint server for biology · 2026Article
- T-cell receptor alpha to beta chains binding prediction.Briefings in bioinformatics · 2026Article
- Mitigating negative data bias to enhance TCR-epitope binding and residue interaction prediction.Briefings in bioinformatics · 2026Article
- Modeling TCR-Epitope Recognition Specificity: What We Should Learn to Succeed.Immunological reviews · 2026Review
- Revised Adaptive Immune Receptor Data in the Immune Epitope Database.bioRxiv : the preprint server for biology · 2026Article
- ANARCII enables alignment-free antigen receptor numbering using a generalised language model.Communications biology · 2026Article
- High-throughput, quantitative approach to peptide epitope discovery.Medical & biological engineering & computing · 2026Article
- AI-Driven BCR Modeling for Precision Immunology.International journal of molecular sciences · 2026Review
- Immune Ageing Clocks: A Methods-Oriented Review of Tasks, Modalities, Models, and Recalibration.Cells · 2026Review
- Decoding adaptive immunity: advanced strategies in T and B cell repertoire analysis.Journal of translational medicine · 2026Review
- Identification of a type 1 diabetes-associated T cell receptor repertoire signature from the human peripheral blood.Science advances · 2026Article
- TCRcloud: a global visualization tool for T-cell and B-cell receptor transcripts.Journal of translational medicine · 2026Article
- Article
- TCR representation learning with protein language models: a comprehensive review.International immunology · 2026Review
- TCRdb 2.0: an updated T-cell receptor sequence database.Nucleic acids research · 2026Article
- Immunogenetics and TCR expression patterns together predict future T1D onset from multi-omic datasets.Frontiers in genetics · 2026Article
- Nucleotide context models outperform protein language models for predicting antibody affinity maturation.PLoS computational biology · 2025Article
- Machine learning in AIRR diagnostics: Advances and applications.Immunoinformatics (Amsterdam, Netherlands) · 2025Article
- Nucleotide context models outperform protein language models for predicting antibody affinity maturation.bioRxiv : the preprint server for biology · 2025Article
52 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
Abstract
Next-generation sequencing allows the characterization of the adaptive immune receptor repertoire (AIRR) in exquisite detail. These large-scale AIRR-seq data sets have rapidly become critical to vaccine development, understanding the immune response in autoimmune and infectious disease, and monitoring novel therapeutics against cancer. However, at present there is no easy way to compare these AIRR-seq data sets across studies and institutions. The ability to combine and compare information for different disease conditions will greatly enhance the value of AIRR-seq data for improving biomedical research and patient care. The iReceptor Data Integration Platform (gateway.ireceptor.org) provides one implementation of the AIRR Data Commons envisioned by the AIRR Community (airr-community.org), an initiative that is developing protocols to facilitate sharing and comparing AIRR-seq data. The iReceptor Scientific Gateway links distributed (federated) AIRR-seq repositories, allowing sequence searches or metadata queries across multiple studies at multiple institutions, returning sets of sequences fulfilling specific criteria. We present a review of the development of iReceptor, and how it fits in with the general trend toward sharing genomic and health data, and the development of standards for describing and reporting AIRR-seq data. Researchers interested in integrating their repositories of AIRR-seq data into the iReceptor Platform are invited to contact support@ireceptor.org.
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.