ArticleFrontiers in immunology2023
tidytcells: standardizer for TR/MH nomenclature.
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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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.
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Who cites it
8 citing papers in PubMed.
- Unsupervised identification of low-frequency antigen-specific TCRs using distance-based anomaly scoring.Briefings in bioinformatics · 2026Article
- Systematic analysis of CDR contacts and pairing constraints between T cell receptor αβ chains.Bioinformatics (Oxford, England) · 2026Article
- DTCR: generating realistic, diverse, and epitope-specific T cell receptor sequences via a discrete diffusion model.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
- IMGTAntibodies (Basel, Switzerland) · 2026Review
- Evolution of the tuberculin skin test reveals generalisable Mtb-reactive T cell metaclones.Nature communications · 2026Article
- Conditional generation of real antigen-specific T cell receptor sequences.Nature machine intelligence · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
T cell receptors (TR) underpin the diversity and specificity of T cell activity. As such, TR repertoire data is valuable both as an adaptive immune biomarker, and as a way to identify candidate therapeutic TR. Analysis of TR repertoires relies heavily on computational analysis, and therefore it is of vital importance that the data is standardized and computer-readable. However in practice, the usage of different abbreviations and non-standard nomenclature in different datasets makes this data pre-processing non-trivial. tidytcells is a lightweight, platform-independent Python package that provides easy-to-use standardization tools specifically designed for TR nomenclature. The software is open-sourced under the MIT license and is available to install from the Python Package Index (PyPI). At the time of publishing, tidytcells is on version 2.0.0.
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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.