Cédric R. Weber

发表

immuneSIM: tunable multi-feature simulation of B- and T-cell receptor repertoires for immunoinformatics benchmarking

Geir Kjetil Sandve, Cédric R. Weber, Rahmad Akbar, 2019, bioRxiv.

Computational Strategies for Dissecting the High-Dimensional Complexity of Adaptive Immune Repertoires

Cédric R. Weber, Alexander Yermanos, Sai T. Reddy, 2017, Front. Immunol..

The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires

Chakravarthi Kanduri, Geir Kjetil Sandve, Eivind Hovig, 2021, Nature Machine Intelligence.

High-throughput antibody engineering in mammalian cells by CRISPR/Cas9-mediated homology-directed mutagenesis

Cédric R. Weber, V. Greiff, S. Reddy, 2018, bioRxiv.

Systems Analysis Reveals High Genetic and Antigen-Driven Predetermination of Antibody Repertoires throughout B Cell Development.

Cédric R. Weber, Enkelejda Miho, V. Greiff, 2017, Cell reports.

In silico proof of principle of machine learning-based antibody design at unconstrained scale

Cédric R. Weber, Ingrid Hobæk Haff, S. Hochreiter, 2021, bioRxiv.

A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding

Geir Kjetil Sandve, Yana Safonova, Cédric R. Weber, 2019, bioRxiv.

Learning the high-dimensional immunogenomic features that predict public and private antibody repertoires

Cédric R. Weber, Enkelejda Miho, V. Greiff, 2017, bioRxiv.

High-throughput antibody engineering in mammalian cells by CRISPR/Cas9-mediated homology-directed mutagenesis

Cédric R. Weber, V. Greiff, S. Reddy, 2018, bioRxiv.

A Single-Cell Atlas of Lymphocyte Adaptive Immune Repertoires and Transcriptomes Reveals Age-Related Differences in Convalescent COVID-19 Patients

Cédric R. Weber, A. Yermanos, S. Reddy, 2021, bioRxiv.

Deep Mutational Learning Predicts ACE2 Binding and Antibody Escape to Combinatorial Mutations in the SARS-CoV-2 Receptor Binding Domain

Cédric R. Weber, A. Yermanos, S. Reddy, 2022, Cell.

High-throughput T cell receptor engineering by functional screening identifies candidates with enhanced potency and specificity.

Cédric R. Weber, S. Reddy, E. Aznauryan, 2022, Immunity.

Deep mutational learning predicts ACE2 binding and antibody escape to combinatorial mutations in the SARS-CoV-2 receptor-binding domain

Cédric R. Weber, A. Yermanos, S. Reddy, 2022, Cell.

A synthetic bispecific antibody capable of neutralizing SARS-CoV-2 Delta and Omicron

Cédric R. Weber, A. Iwasaki, S. Reddy, 2022, bioRxiv.

Predictive profiling of SARS-CoV-2 variants by deep mutational learning

Cédric R. Weber, A. Yermanos, S. Reddy, 2021, bioRxiv.

Learning the High-Dimensional Immunogenomic Features That Predict Public and Private Antibody Repertoires

Cédric R. Weber, Enkelejda Miho, V. Greiff, 2017, The Journal of Immunology.

Individualized VDJ recombination predisposes the available Ig sequence space

Cédric R. Weber, Ingrid Hobæk Haff, R. Akbar, 2021, bioRxiv.

Platypus: an open-access software for integrating lymphocyte single-cell immune repertoires with transcriptomes

Cédric R. Weber, A. Oxenius, A. Yermanos, 2020, bioRxiv.

The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires

Cédric R. Weber, Ingrid Hobæk Haff, S. Hochreiter, 2021, Nature Machine Intelligence.

Echidna: integrated simulations of single-cell immune receptor repertoires and transcriptomes

Cédric R. Weber, V. Greiff, A. Oxenius, 2021, bioRxiv.

A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding.

Cédric R. Weber, Ingrid Hobæk Haff, R. Akbar, 2021, Cell reports.

A compact vocabulary of paratope-epitope interactions enables predictability of antibody-antigen binding

Cédric R. Weber, Ingrid Hobæk Haff, R. Akbar, 2019, bioRxiv.

Reference-based comparison of adaptive immune receptor repertoires

Cédric R. Weber, R. Akbar, Philippe A. Robert, 2022, bioRxiv.

Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning

Cédric R. Weber, S. Reddy, Simon M Meng, 2021, Nature Biomedical Engineering.

CRISPR-targeted display of functional T cell receptors enables engineering of enhanced specificity and prediction of cross-reactivity

Cédric R. Weber, S. Reddy, E. Aznauryan, 2020, bioRxiv.

Deep learning enables therapeutic antibody optimization in mammalian cells by deciphering high-dimensional protein sequence space

Cédric R. Weber, Sai T Reddy, Simon Friedensohn, 2019, bioRxiv.

SARS-CoV-2 reactive and neutralizing antibodies discovered by single-cell sequencing of plasma cells and mammalian display

Cédric R. Weber, Andreas P. Cuny, A. Yermanos, 2021, Cell Reports.

The Physiological Landscape and Specificity of Antibody Repertoires

Cédric R. Weber, S. Reddy, B. Correia, 2021, bioRxiv.

Single-cell sequencing of plasma cells from COVID-19 patients reveals highly expanded clonal lineages produce specific and neutralizing antibodies to SARS-CoV-2

Cédric R. Weber, Andreas P. Cuny, A. Yermanos, 2021, bioRxiv.

Accelerating the prediction of large carbon clusters via structure search: Evaluation of machine-learning and classical potentials

Cédric R. Weber, Patrick Rowe, Jean-Marc Leyssale, 2022, Carbon.

Synthetic coevolution reveals adaptive mutational trajectories of neutralizing antibodies and SARS-CoV-2

Cédric R. Weber, D. Sheward, Joseph M. Taft, 2024, bioRxiv.

High-throughput antibody engineering in mammalian cells by CRISPR/Cas9-mediated homology-directed mutagenesis

Cédric R. Weber, S. Reddy, Cristina Parola, 2018, bioRxiv.

Deep learning-guided selection of antibody therapies with enhanced resistance to current and prospective SARS-CoV-2 Omicron variants

Cédric R. Weber, Joseph M. Taft, Beichen Gao, 2023, bioRxiv.

A finite vocabulary of antibody-antigen interaction enables predictability of paratope-epitope binding

Cédric R. Weber, R. Akbar, Philippe A. Robert, 2019 .

Deep learning enables therapeutic antibody optimization in 1 mammalian cells 2

Cédric R. Weber, Christian Jordi, Bastian Wagner, 2019 .