Related references
Note: Only part of the references are listed.ScanNeo: identifying indel-derived neoantigens using RNA-Seq data
Ting-You Wang et al.
BIOINFORMATICS (2019)
Deciphering CD4+ T cell specificity using novel MHC-TCR chimeric receptors
Jan Kisielow et al.
NATURE IMMUNOLOGY (2019)
T cell antigen discovery via signaling and antigen-presenting bifunctional receptors
Alok Joglekar et al.
NATURE METHODS (2019)
High-throughput Screening of Human Tumor Antigen-specific CD4 T Cells, Including Neoantigen-reactive T Cells
Carla Costa-Nunes et al.
CLINICAL CANCER RESEARCH (2019)
Neoantigen identification strategies enable personalized immunotherapy in refractory solid tumors
Fangjun Chen et al.
JOURNAL OF CLINICAL INVESTIGATION (2019)
In silico simulation of a clinical trial with anti-CTLA-4 and anti-PD-L1 immunotherapies in metastatic breast cancer using a systems pharmacology model
Hanwen Wang et al.
ROYAL SOCIETY OPEN SCIENCE (2019)
Evaluating a Multiscale Mechanistic Model of the Immune System to Predict Human Immunogenicity for a Biotherapeutic in Phase 1
Lora Hamuro et al.
AAPS JOURNAL (2019)
MHCSeqNet: a deep neural network model for universal MHC binding prediction
Poomarin Phloyphisut et al.
BMC BIOINFORMATICS (2019)
Quantitative Mechanistic Modeling in Support of Pharmacological Therapeutics Development in Immuno-Oncology
Kirill Peskov et al.
FRONTIERS IN IMMUNOLOGY (2019)
Efficient identification of neoantigen-specific T-cell responses in advanced human ovarian cancer
Song Liu et al.
JOURNAL FOR IMMUNOTHERAPY OF CANCER (2019)
Best practices for bioinformatic characterization of neoantigens for clinical utility
Megan M. Richters et al.
GENOME MEDICINE (2019)
A QSP Model for Predicting Clinical Responses to Monotherapy, Combination and Sequential Therapy Following CTLA-4, PD-1, and PD-L1 Checkpoint Blockade
Oleg Milberg et al.
SCIENTIFIC REPORTS (2019)
Development of tumor mutation burden as an immunotherapy biomarker: utility for the oncology clinic
T. A. Chan et al.
ANNALS OF ONCOLOGY (2019)
Deep learning using tumor HLA peptide mass spectrometry datasets improves neoantigen identification
Brendan Bulik-Sullivan et al.
NATURE BIOTECHNOLOGY (2019)
Identification of candidate neoantigens produced by fusion transcripts in human osteosarcomas
Susan K. Rathe et al.
SCIENTIFIC REPORTS (2019)
Normative data for flow cytometry immunophenotyping of benign lymph nodes sampled by surgical biopsy
Gregory David Scott et al.
JOURNAL OF CLINICAL PATHOLOGY (2018)
Antigen Identification for Orphan T Cell Receptors Expressed on Tumor-Infiltrating Lymphocytes
Marvin H. Gee et al.
CELL (2018)
Improved methods for predicting peptide binding affinity to MHC class II molecules
Kamilla Kjaergaard Jensen et al.
IMMUNOLOGY (2018)
Natural variation in the parameters of innate immune cells is preferentially driven by genetic factors
Etienne Patin et al.
NATURE IMMUNOLOGY (2018)
Immune recognition of somatic mutations leading to complete durable regression in metastatic breast cancer
Nikolaos Zacharakis et al.
NATURE MEDICINE (2018)
Phenotype molding of stromal cells in the lung tumor microenvironment
Diether Lambrechts et al.
NATURE MEDICINE (2018)
MHCflurry: Open-Source Class I MHC Binding Affinity Prediction
Timothy J. O'Donnell et al.
CELL SYSTEMS (2018)
TSNAdb: A Database for Tumor-specific Neoantigens from Immunogenomics Data Analysis
Jingcheng Wu et al.
GENOMICS PROTEOMICS & BIOINFORMATICS (2018)
Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy
Razvan Cristescu et al.
SCIENCE (2018)
Human immunology studies using organ donors: Impact of clinical variations on immune parameters in tissues and circulation
D. J. Carpenter et al.
AMERICAN JOURNAL OF TRANSPLANTATION (2018)
Dendritic Cells Display Subset and Tissue-Specific Maturation Dynamics over Human Life
Tomer Granot et al.
IMMUNITY (2017)
IFN-γ-related mRNA profile predicts clinical response to PD-1 blockade
Mark Ayers et al.
JOURNAL OF CLINICAL INVESTIGATION (2017)
NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data
Vanessa Jurtz et al.
JOURNAL OF IMMUNOLOGY (2017)
A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy
Marta Luksza et al.
NATURE (2017)
Estimation of immune cell content in tumour tissue using single-cell RNA-seq data
Max Schelker et al.
NATURE COMMUNICATIONS (2017)
Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint Blockade
Pornpimol Charoentong et al.
CELL REPORTS (2017)
Tumor and Microenvironment Evolution during Immunotherapy with Nivolumab
Nadeem Riaz et al.
CELL (2017)
Characterization of the T-Cell Receptor Repertoire and Immune Microenvironment in Patients with Locoregionally Advanced Squamous Cell Carcinoma of the Head and Neck
Vassiliki Saloura et al.
CLINICAL CANCER RESEARCH (2017)
Gapped sequence alignment using artificial neural networks: application to the MHC class I system
Massimo Andreatta et al.
BIOINFORMATICS (2016)
Systematic evaluation of pembrolizumab dosing in patients with advanced non-small-cell lung cancer
M. Chatterjee et al.
ANNALS OF ONCOLOGY (2016)
T cell fate and clonality inference from single-cell transcriptomes
Michael J. T. Stubbington et al.
NATURE METHODS (2016)
Long-term maintenance of human naive T cells through in situ homeostasis in lymphoid tissue sites
Joseph J. C. Thome et al.
SCIENCE IMMUNOLOGY (2016)
MiXCR: software for comprehensive adaptive immunity profiling
Dmitriy A. Bolotin et al.
NATURE METHODS (2015)
Robust enumeration of cell subsets from tissue expression profiles
Aaron M. Newman et al.
NATURE METHODS (2015)
Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer
Naiyer A. Rizvi et al.
SCIENCE (2015)
Multiplex Identification of Antigen-Specific T Cell Receptors Using a Combination of Immune Assays and Immune Receptor Sequencing
Mark Klinger et al.
PLOS ONE (2015)
Spatial Map of Human T Cell Compartmentalization and Maintenance over Decades of Life
Joseph J. C. Thome et al.
CELL (2014)
Towards error-free profiling of immune repertoires
Mikhail Shugay et al.
NATURE METHODS (2014)
Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma
Alexandra Snyder et al.
NEW ENGLAND JOURNAL OF MEDICINE (2014)
A Mechanistic, Multiscale Mathematical Model of Immunogenicity for Therapeutic Proteins: Part 1-Theoretical Model
X. Chen et al.
CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY (2014)
A Mechanistic, Multiscale Mathematical Model of Immunogenicity for Therapeutic Proteins: Part 2-Model Applications
X. Chen et al.
CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY (2014)
Systems Pharmacology for Drug Discovery and Development: Paradigm Shift or Flash in the Pan?
P. Vicini et al.
CLINICAL PHARMACOLOGY & THERAPEUTICS (2013)
Distribution and Compartmentalization of Human Circulating and Tissue-Resident Memory T Cell Subsets
Taheri Sathaliyawala et al.
IMMUNITY (2013)
Oncology Meets Immunology: The Cancer-Immunity Cycle
Daniel S. Chen et al.
IMMUNITY (2013)
NetMHCIIpan-3.0, a common pan-specific MHC class II prediction method including all three human MHC class II isotypes, HLA-DR, HLA-DP and HLA-DQ
Edita Karosiene et al.
IMMUNOGENETICS (2013)
The Cancer Genome Atlas Pan-Cancer analysis project
John N. Weinstein et al.
NATURE GENETICS (2013)
An effective and effecient peptide binding prediction approach for a broad set of HLA-DR molecules based on ordered weighted averaging of binding pocket profiles
Wen-Jun Shen et al.
PROTEOME SCIENCE (2013)
NetMHCcons: a consensus method for the major histocompatibility complex class I predictions
Edita Karosiene et al.
IMMUNOGENETICS (2012)
TEPITOPEpan: Extending TEPITOPE for Peptide Binding Prediction Covering over 700 HLA-DR Molecules
Lianming Zhang et al.
PLOS ONE (2012)
Coordinated regulation of myeloid cells by tumours
Dmitry I. Gabrilovich et al.
NATURE REVIEWS IMMUNOLOGY (2012)
NNAlign: A Web-Based Prediction Method Allowing Non-Expert End-User Discovery of Sequence Motifs in Quantitative Peptide Data
Massimo Andreatta et al.
PLOS ONE (2011)
MultiRTA: A simple yet reliable method for predicting peptide binding affinities for multiple class II MHC allotypes
Andrew J. Bordner et al.
BMC BIOINFORMATICS (2010)
The PickPocket method for predicting binding specificities for receptors based on receptor pocket similarities: application to MHC-peptide binding
Hao Zhang et al.
BIOINFORMATICS (2009)
Quantifying the development of the peripheral naive CD4+ T-cell pool in humans
Iren Bains et al.
BLOOD (2009)
Derivation of an amino acid similarity matrix for peptide: MHC binding and its application as a Bayesian prior
Yohan Kim et al.
BMC BIOINFORMATICS (2009)
A Framework for Assessing Inter-individual Variability in Pharmacokinetics Using Virtual Human Populations and Integrating General Knowledge of Physical Chemistry, Biology, Anatomy, Physiology and Genetics: A Tale of 'Bottom-Up' vs 'Top-Down' Recognition of Covariates
Masoud Jamei et al.
DRUG METABOLISM AND PHARMACOKINETICS (2009)
Prediction of MHC class II binding affinity using SMM-align, a novel stabilization matrix alignment method
Morten Nielsen et al.
BMC BIOINFORMATICS (2007)
A validated mathematical model of cell-mediated immune response to tumor growth
LG de Pillis et al.
CANCER RESEARCH (2005)
Prediction of MHC class I binding peptides using profile motifs
PA Reche et al.
HUMAN IMMUNOLOGY (2002)
ProPred: prediction of HLA-DR binding sites
H Singh et al.
BIOINFORMATICS (2001)