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Publications

  • NNAlign_MA; MHC peptidome deconvolution for accurate MHC binding motif characterization and improved T cell epitope predictions.
  • STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq data
  • Projecting single-cell transcriptomics data onto a reference T cell atlas to interpret immune responses
  • STACAS: Sub-Type Anchor Correction for Alignment in Seurat to integrate single-cell RNA-seq data
  • Immunoinformatics: Predicting Peptide–MHC Binding
  • UCell: robust and scalable single-cell gene signature scoring
  • Interpretation of T cell states from single-cell transcriptomics data using reference atlases
  • Low Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • An automated benchmarking platform for MHC class II binding prediction methods
  • Improved methods for predicting peptide binding affinity to MHC class II molecules
  • Footprints of antigen processing boost MHC class II natural ligand binding predictions
  • NetH2pan: A Computational Tool to Guide MHC Peptide Prediction on Murine Tumors
  • MS-Rescue: A Computational Pipeline to Increase the Quality and Yield of Immunopeptidomics Experiments
  • IEDB-AR: immune epitope database—analysis resource in 2019
  • Bioinformatics Tools for the Prediction of T-Cell Epitopes.
  • Footprints of antigen processing boost MHC class II natural ligand predictions.
  • Computational Tools for the Identification and Interpretation of Sequence Motifs in Immunopeptidomes.
  • Predicting HLA CD4 immunogenicity in human populations
  • Gapped sequence alignment using artificial neural networks: application to the MHC class I system.
  • Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification.
  • NetMHCpan-3.0; improved prediction of binding to MHC class I molecules integrating information from multiple receptor and peptide length datasets.
  • Breaking confinement: unconventional peptide presentation by major histocompatibility (MHC) class I allele HLA-A*02:01.
  • NNAlign: a platform to construct and evaluate artificial neural network models of receptor–ligand interactions
  • GibbsCluster: unsupervised clustering and alignment of peptide sequences
  • Machine learning reveals a non-canonical mode of peptide binding to MHC class II molecules
  • NetMHCpan-4.0: Improved Peptide–MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data
  • Computational Tools for the Identification and Interpretation of Sequence Motifs in Immunopeptidomes
  • Gapped sequence alignment using artificial neural networks: Application to the MHC class i system
  • In Silico Prediction of Human Pathogenicity in the γ-Proteobacteria
  • Characterizing the binding motifs of 11 common human HLA-DP and HLA-DQ molecules using NNAlign
  • Quantifying Significance of MHC II Residues
  • NNAlign: A Web-Based Prediction Method Allowing Non-Expert End-User Discovery of Sequence Motifs in Quantitative Peptide Data
  • Using Electronic Patient Records to Discover Disease Correlations and Stratify Patient Cohorts
  • Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach.
  • Accurate pan-specific prediction of peptide-MHC class II binding affinity with improved binding core identification
  • SPICA: Swiss portal for immune cell analysis
  • scGate: marker-based purification of cell types from heterogeneous single-cell RNA-seq datasets
  • Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Orthogonal Gene Engineering Enables CD8+ T Cells to Control Tumors through a Novel PD-1+ TOX-indifferent Synthetic Effector State
  • Orthogonal Gene Engineering Enables CD8+ T Cells to Control Tumors through a Novel PD-1+TOX-indifferent Synthetic Effector State
  • NFAT5 induction by the tumor microenvironment enforces CD8 T cell exhaustion
  • Dissecting the treatment-naive ecosystem of human melanoma brain metastasis
  • A CD4+ T cell reference map delineates subtype-specific adaptation during acute and chronic viral infections
  • Supplementary Table from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Data from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Table from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Figure from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Table from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Table from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Table from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Figure from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Figure from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Table from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Table from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Table from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Table from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Table from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Figure from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Figure from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Figure from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Data from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Figure from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Figure from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Figure from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Figure from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Supplementary Data from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Data from Low-Dose Radiotherapy Reverses Tumor Immune Desertification and Resistance to Immunotherapy
  • Data from NetH2pan: A Computational Tool to Guide MHC Peptide Prediction on Murine Tumors
  • Supplemental tables and figures from NetH2pan: A Computational Tool to Guide MHC Peptide Prediction on Murine Tumors
  • Orthogonal cytokine engineering enables novel synthetic effector states escaping canonical exhaustion in tumor-rejecting CD8+ T cells
  • Semi-supervised integration of single-cell transcriptomics data
  • Activation of the transcription factor NFAT5 in the tumor microenvironment enforces CD8+ T cell exhaustion
  • MS‐Rescue: A Computational Pipeline to Increase the Quality and Yield of Immunopeptidomics Experiments
  • Machine learning reveals a non‐canonical mode of peptide binding to MHC class II molecules
  • IL-10-expressing CAR T cells resist dysfunction and mediate durable clearance of solid tumors and metastases

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Co-workers & collaborators

Santiago Carmona

Switzerland

Santiago Carmona

Paul Gueguen

Paul Gueguen

Ariel Berenstein

Ariel Berenstein

Massimo Andreatta's public data