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ImmunoInformatics
ISSN 2667-1190 · Elsevier · 60 articles in the index
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Journal Article
Active learning for improving out-of-distribution lab-in-the-loop experimental designAll code and data is available at
The accurate prediction of antibody-antigen binding is crucial for developing antibody-based therapeutics and advancing immunological research. Library-on-library approaches, where many antigens are probed against many antibodies, can identify specific interacting pairs. Machine learning models can…
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Journal Article
AMULETY: A Python package to embed adaptive immune receptor sequences
Large language models have been developed to capture relevant features of adaptive immune receptors, each with unique potential applications. However, the diversity in available models presents challenges in accessibility and usability for downstream applications. Here we present AMULETY (Adaptive…
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Journal Article
Is the vaccination-induced B cell receptor repertoire predictable?
Vaccines trigger an immune response that results in a population of memory cells that can quickly respond to subsequent antigen re-encounters. Most vaccines are designed to induce memory B cells with vaccine-specific B cell receptors (BCRs). Post-vaccination, clonal expansion of B cells results in…
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Journal Article
Building immunoglobulin and T cell receptor gene databases for the future
Genetic databases for immunoglobulin (IG) and T cell receptor (TR) genes have evolved from small catalogs to critical resources underpinning immunogenetic research. Accurate annotation enables the analysis of repertoire diversity, somatic hypermutation, clonal relationships, and lineage…
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Journal Article
Challenges for the immunoglobulin and T cell receptor gene nomenclatures in the modern genomics era
For over thirty years, an approach to the nomenclatures of human immunoglobulin (IG) and T cell receptor (TR) genes has operated successfully and has been widely supported by the research community. The principles behind the human nomenclatures were then applied to the development of nomenclatures…
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Journal Article
Challenges and future directions of AIRR-seq-based diagnostics
Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) is a promising diagnostic method across various clinical conditions, yet its widespread implementation faces several challenges. This perspective examines the current landscape of AIRR-seq diagnostics and outlines key obstacles and…
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Journal Article
Comparison of different substitution matrices for distance based T-cell receptor epitope predictions using tcrdist3
Various methods, differing in complexity, have been developed to predict T-cell receptor epitopes. tcrdist3, which implements an easy-to-interpret distance-based approach, has demonstrated performance comparable to the best feature-based methods. Here, a new substitution matrix for tcrdist3 is…
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Journal Article
Structural insights on the differentiation and reversion of conformational changes in SARS-CoV-2 spike protein models across variants occurring from December, 2019 to November, 2021
Conformational changes in the SARS-CoV-2 spike protein are critical for understanding viral evolution. In this study, we provide comparative structural and electrostatic analyses across variants, revealing both differentiation and reversion patterns not previously described in locked and activated…
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Journal Article
AnalyzAIRR: A user-friendly guided workflow for AIRR data analysis
The analysis of bulk adaptive immune receptor repertoires (AIRR) enables the understanding of immune responses in both normal and pathological conditions. However, the complexity of AIRR calls for advanced, specialized methods to extract meaningful biological insights. These sophisticated…
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Journal Article
DoggifAI: A transformer based approach for antibody caninisation
Antibody translation across species offers a compelling strategy to extend the vast and expensive investments in human therapeutic antibodies to veterinary oncology, with applications in both veterinary medicine and comparative oncology.While precise, low-immunogenic treatments are essential for…
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Journal Article
Where single-cell transcriptomics fails T cells: The misuse of unsupervised clustering for T-cell annotationThis perspective used publicly available data (DOI: 10.5281/zenodo.12569981; ).
The current state of single-cell transcriptomic interrogation typically consists of using an unsupervised clustering approach followed by expert opinion-based annotation. The underlying assumption is that this process will identify transcriptional differences between cellular subsets accurately…
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Journal Article
Machine learning in AIRR diagnostics: Advances and applications
Recent advancements in sequencing technologies have led to an exponential increase in adaptive immune receptor repertoire (AIRR) data. These receptors, crucial to the adaptive immune system, are believed to have strong potential for diagnostic applications. The immune repertoires represent a wealth…
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Journal Article
Building immune digital twins: An international and transdisciplinary community effort
Digital twins, initially developed for industrial applications, are set to make significant advancements in medicine and healthcare. They have demonstrated promising potential for drug development and personalised care, especially in cardiovascular diagnostics and insulin-dependent diabetes…
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Journal Article
IApred: A versatile open-source tool for predicting protein antigenicity across diverse pathogens
Accurate prediction of protein antigenicity is crucial for vaccine development, diagnostic test design, and therapeutic protein engineering. However, existing tools face limitations in accessibility, computational efficiency, and pathogen diversity. Here, we present IApred, an open-source intrinsic…
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Journal Article
The gremlin in the works: why T cell receptor researchers need to pay more attention to germline reference sequences
The rise of T cell receptor (TCR) sequencing technologies is driving both new understandings of the immune system and the development of novel clinical platforms. Such analyses rely on comparing recombined TCR sequences to unrearranged germline reference sequences during V(D)J annotation. In this…
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Journal Article
Deciphering the role of molecular mimicry in the etiopathogenesis of Autoimmune Hemolytic Anemia using an immunoinformatics approach.
Autoimmune hemolytic anemia (AIHA) is a chronic autoimmune disease characterized by the self-destruction of red blood cells (RBCs). For investigating the role molecular mimicry in the onset of AIHA manifestations, we identified the microbial epitopes as precipitating factors in the disease…
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Journal Article
Molecular mimicry impact of the COVID-19 pandemic: Sequence homology between SARS-CoV-2 and autoimmune diseases epitopes
Molecular mimicry is one mechanism by which an infectious agent may trigger an autoimmune disease in a human subject and occurs when foreign- and self-peptides contain similar epitopes that activate an autoimmune response in a susceptible individual. Here, we employ a scalable in-silico approach…
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Journal Article
Comparative analysis of SLA-1 and SLA-2 genetic diversity in exotic, hybrid, and local pig breeds of Cameroon in relation to adaptive immunity against African swine virus
African swine fever is a severe hemorrhagic swine disease that greatly affects smallholder pig farm productivity in low-income countries as well as some developed countries. Research has shown that the indigenous pigs and wild suids in Africa are either tolerant or resistant to the disease. Also…
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Journal Article
Do domain-specific protein language models outperform general models on immunology-related tasks?
Deciphering the antigen recognition capabilities by T-cell and B-cell receptors (antibodies) is essential for advancing our understanding of adaptive immune system responses. In recent years, the development of protein language models (PLMs) has facilitated the development of bioinformatic…
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Journal Article
T-cell receptor binding prediction: A machine learning revolution
Recent advancements in immune sequencing and experimental techniques are generating extensive T cell receptor (TCR) repertoire data, enabling the development of models to predict TCR binding specificity. Despite the computational challenges posed by the vast diversity of TCRs and epitopes…