[HTML][HTML] Can we predict T cell specificity with digital biology and machine learning?
Recent advances in machine learning and experimental biology have offered breakthrough
solutions to problems such as protein structure prediction that were long thought to be …
solutions to problems such as protein structure prediction that were long thought to be …
Can AlphaFold's breakthrough in protein structure help decode the fundamental principles of adaptive cellular immunity?
T cells are essential immune cells responsible for identifying and eliminating pathogens.
Through interactions between their T-cell antigen receptors (TCRs) and antigens presented …
Through interactions between their T-cell antigen receptors (TCRs) and antigens presented …
[HTML][HTML] A common allele of HLA is associated with asymptomatic SARS-CoV-2 infection
DG Augusto, LD Murdolo, DSM Chatzileontiadou… - Nature, 2023 - nature.com
Studies have demonstrated that at least 20% of individuals infected with SARS-CoV-2
remain asymptomatic,,–. Although most global efforts have focused on severe illness in …
remain asymptomatic,,–. Although most global efforts have focused on severe illness in …
Structural and physical features that distinguish tumor-controlling from inactive cancer neoepitopes
JM Custodio, CM Ayres, TJ Rosales… - Proceedings of the …, 2023 - National Acad Sciences
Neoepitopes arising from amino acid substitutions due to single nucleotide polymorphisms
are targets of T cell immune responses to cancer and are of significant interest in the …
are targets of T cell immune responses to cancer and are of significant interest in the …
A transfer-learning approach to predict antigen immunogenicity and T-cell receptor specificity
Antigen immunogenicity and the specificity of binding of T-cell receptors to antigens are key
properties underlying effective immune responses. Here we propose diffRBM, an approach …
properties underlying effective immune responses. Here we propose diffRBM, an approach …
Human T cells recognize HLA-DP–bound peptides in two orientations
S Klobuch, JJ Lim, P van Balen… - Proceedings of the …, 2022 - National Acad Sciences
Human leukocyte antigen (HLA) molecules present small peptide antigens to T cells,
thereby allowing them to recognize pathogen-infected and cancer cells. A central dogma …
thereby allowing them to recognize pathogen-infected and cancer cells. A central dogma …
[HTML][HTML] HLA-A*11:01-restricted CD8+ T cell immunity against influenza A and influenza B viruses in Indigenous and non-Indigenous people
HLA-A* 11: 01 is one of the most prevalent human leukocyte antigens (HLAs), especially in
East Asian and Oceanian populations. It is also highly expressed in Indigenous people who …
East Asian and Oceanian populations. It is also highly expressed in Indigenous people who …
[HTML][HTML] HLA3DB: comprehensive annotation of peptide/HLA complexes enables blind structure prediction of T cell epitopes
The class I proteins of the major histocompatibility complex (MHC-I) display epitopic
peptides derived from endogenous proteins on the cell surface for immune surveillance …
peptides derived from endogenous proteins on the cell surface for immune surveillance …
[HTML][HTML] Improvement in neoantigen prediction via integration of RNA sequencing data for variant calling
BQT Nguyen, TPD Tran, HT Nguyen… - Frontiers in …, 2023 - frontiersin.org
Introduction Neoantigen-based immunotherapy has emerged as a promising strategy for
improving the life expectancy of cancer patients. This therapeutic approach heavily relies on …
improving the life expectancy of cancer patients. This therapeutic approach heavily relies on …
DeepMHCI: an anchor position-aware deep interaction model for accurate MHC-I peptide binding affinity prediction
Motivation Computationally predicting major histocompatibility complex class I (MHC-I)
peptide binding affinity is an important problem in immunological bioinformatics, which is …
peptide binding affinity is an important problem in immunological bioinformatics, which is …