Best practices for single-cell analysis across modalities
Recent advances in single-cell technologies have enabled high-throughput molecular
profiling of cells across modalities and locations. Single-cell transcriptomics data can now …
profiling of cells across modalities and locations. Single-cell transcriptomics data can now …
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 …
Combination anti-HIV antibodies provide sustained virological suppression
MC Sneller, J Blazkova, JS Justement, V Shi… - Nature, 2022 - nature.com
Antiretroviral therapy is highly effective in suppressing human immunodeficiency virus (HIV).
However, eradication of the virus in individuals with HIV has not been possible to date …
However, eradication of the virus in individuals with HIV has not been possible to date …
Pan-peptide meta learning for T-cell receptor–antigen binding recognition
The identification of the mechanisms by which T-cell receptors (TCRs) interact with human
antigens provides a crucial opportunity to develop new vaccines, diagnostics and …
antigens provides a crucial opportunity to develop new vaccines, diagnostics and …
Computational and artificial intelligence-based methods for antibody development
Due to their high target specificity and binding affinity, therapeutic antibodies are currently
the largest class of biotherapeutics. The traditional largely empirical antibody development …
the largest class of biotherapeutics. The traditional largely empirical antibody development …
Observed Antibody Space: A diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences
The antibody repertoires of individuals and groups have been used to explore disease
states, understand vaccine responses, and drive therapeutic development. The arrival of B …
states, understand vaccine responses, and drive therapeutic development. The arrival of B …
Deep learning-based prediction of the T cell receptor–antigen binding specificity
Neoantigens play a key role in the recognition of tumour cells by T cells; however, only a
small proportion of neoantigens truly elicit T-cell responses, and few clues exist as to which …
small proportion of neoantigens truly elicit T-cell responses, and few clues exist as to which …
CD4+ T cells exhibit distinct transcriptional phenotypes in the lymph nodes and blood following mRNA vaccination in humans
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and mRNA
vaccination induce robust CD4+ T cell responses. Using single-cell transcriptomics, here …
vaccination induce robust CD4+ T cell responses. Using single-cell transcriptomics, here …
TCRMatch: predicting T-cell receptor specificity based on sequence similarity to previously characterized receptors
WD Chronister, A Crinklaw, S Mahajan, R Vita… - Frontiers in …, 2021 - frontiersin.org
The adaptive immune system in vertebrates has evolved to recognize non-self antigens,
such as proteins expressed by infectious agents and mutated cancer cells. T cells play an …
such as proteins expressed by infectious agents and mutated cancer cells. T cells play an …
Modern hopfield networks and attention for immune repertoire classification
A central mechanism in machine learning is to identify, store, and recognize patterns. How to
learn, access, and retrieve such patterns is crucial in Hopfield networks and the more recent …
learn, access, and retrieve such patterns is crucial in Hopfield networks and the more recent …