IMGT®, the international ImMunoGeneTics information system®, has advanced its comprehensive platform for the analysis of immunoglobulin (IG) and T-cell receptor (TR) genes through the development of new automated and scalable tools. This article presents major updates aligned with IMGT’s three axes of research. Axis I introduces dynamic resources such as IMGT/GeneTables, IMGT/AssemblyComparison, IMGT/CDRLengths, IMGT/MultiGenomeViewer, enabling real-time access to annotated genomic data, and IMGT/StatAssembly to assess quality of IG/TR loci in assemblies. Axis II enhances repertoire analysis with a redesigned IMGT/GeneFrequency tool and new customization features in IMGT/V-QUEST, supporting flexible exploration of IG and TR gene expression. Axis III improves the accurate prediction of peptide–MHC thanks to IMGT/RobustpMHC. Additionally, the IMGT knowledge graph and its therapeutic extension, IMGT/mAb-KG, provide semantically structured access to >100 million immunogenetic triplets, integrating IMGT databases and linking IMGT content to external biomedical resources. These developments promote standardization, interoperability, and integrative analysis across immunogenetics and clinical applications, reinforcing IMGT’s (accessible at https://www.imgt.org) role as a core reference in the era of FAIR data and personalized medicine.

Dynamic changes in protein glycosylation impact human health and disease progression. However, current resources that capture disease and phenotype information focus primarily on the macromolecules within the central dogma of molecular biology (DNA, RNA, proteins). To gain a better understanding of organisms, there is a need to capture the functional impact of glycans and glycosylation on biological processes. A workshop titled “Functional impact of glycans and their curation” was held in conjunction with the 16th Annual International Biocuration Conference to discuss ongoing worldwide activities related to glycan function curation. This workshop brought together subject matter experts, tool developers, and biocurators from over 20 projects and bioinformatics resources. Participants discussed four key topics for each of their resources: (i) how they curate glycan function-related data from publications and other sources, (ii) what type of data they would like to acquire, (iii) what data they currently have, and (iv) what standards they use. Their answers contributed input that provided a comprehensive overview of state-of-the-art glycan function curation and annotations. This report summarizes the outcome of discussions, including potential solutions and areas where curators, data wranglers, and text mining experts can collaborate to address current gaps in glycan and glycosylation annotations, leveraging each other’s work to improve their respective resources and encourage impactful data sharing among resources. Database URL: https://wiki.glygen.org/Glycan_Function_Workshop_2023

IMGT®, the international ImMunoGeneTics information system®, has advanced its comprehensive platform for the analysis of immunoglobulin (IG) and T cell receptor (TR) genes through the development of new automated and scalable tools. This article presents major updates aligned with IMGT’s three axes of research. Axis I introduces dynamic resources such as IMGT/GeneTables, IMGT/AssemblyComparison, and IMGT/StatAssembly, enabling real-time access to annotated genomic data and quality assessment of assemblies. Axis II enhances repertoire analysis with a redesigned IMGT/GeneFrequency tool and new customization features in IMGT/V-QUEST, supporting flexible exploration of IG and TR gene expression. Axis III improves the accurate prediction of peptide-MHC thanks to IMGT/RobustpMHC. Additionally, the IMGT Knowledge Graph (IMGT-KG) and its therapeutic extension, IMGT/mAb-KG, provide semantically structured access to more than 100 million immunogenetic triplets, integrating IMGT databases and linking IMGT content to external biomedical resources. These developments promote standardization, interoperability, and integrative analysis across immunogenetics and clinical applications, reinforcing IMGT’s role as a core reference in the era of FAIR data and personalized medicine.

Monoclonal antibodies (mAbs) and fusion proteins for immune applications (FPIA) play a crucial role in treating autoimmune diseases and cancers by targeting cell-surface proteins and triggering multiple immune mechanisms. These functions are mediated by the crystallizable fragment (Fc) region of mAbs and fusion proteins, whose interaction with Fc gamma receptors (FcγRs) can be modulated through Fc amino acid (AA) engineering. To aid research in this area, we developed the IMGT/FcVariantsExplorer tool (https://www.imgt.org/fcvariantsexplorer/) to identify engineered AA changes or variants within the Fc region in mAb and fusion proteins sequences from IMGT/2Dstructure-DB, the AA sequence database of IMGT®, the international ImMunoGeneTics information system®. We used the IMGT® nomenclature of engineered Fc variants involved in antibody effector properties and formats, applying a standardized classification in five categories: 'Effector,' 'Half-life,' 'Physicochemical properties,' 'Structure,' and 'Hybrid.' We analyzed sequences from 1,107 mAbs and fusion proteins, identifying 483 entries with Fc AA changes, resulting in 211 unique Fc variants in the dataset. We also used web scraping to retrieve associated biological data from literature. All data have been integrated into IMGT/mAb-DB, with links to sequences in IMGT/2Dstructure-DB, enabling users to query Fc variants by their 'Category' or 'Effect.' This curated dataset reveals key trends in antibody engineering.

IMGT® est, à ce jour, la référence internationale dans le domaine de l’immunoinformatique intégrant les connaissances immunogénétiques du gène à la protéine. Il propose ainsi l’accès à sept bases de données relationnelles, de 17 outils d'analyse et de très nombreuses ressources en pages web. Compte tenu de la complexité et de la nature connectée des entités immunogénétiques, un besoin d’intégrer les différentes bases de données d’IMGT afin de répondre à des questions biologiques complexes impliquant différentes bases de données, mais également pour découvrir de nouvelles connaissances ou des connaissances insoupçonnées. Les graphes de connaissance (GC) sont des modèles ontologiques qui décrivent les entités d'intérêt dans un domaine et les relations entre elles. Ils permettent l’intégration et la fédération des connaissances de diverses sources de données. Aujourd'hui, ces graphes sont les clés pour obtenir un Web structuré avec données et connaissances interopérables, réutilisables et accessibles, concept nommé FAIR.Cette thèse a permis la mise en place d’IMGT-KG, le premier GC FAIR en immunogénétique intégrant cinq bases de données d’IMGT : celle de séquences nucléotidiques, de gène, des structures 2D et 3D et celle dédiée aux anticorps monoclonaux thérapeutiques (mAbs). En plus ce GC est lié à d’autres référentiels du domaine biomédical tel que NCIT, NCBITaxon, PharmgKB, IEDB etc. Par la suite, ce GC a été exploité afin de mettre en place des applications de machine learning comme la génération d’hypothèses scientifiques dans le domaine des mAbs afin de réutiliser des mAbs dans nouvelles indications cliniques. Ces hypothèses devront être validées in vitro ou in vivo par les spécialistes.