AIMC Topic: Immunologic Memory

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Sensitive detection of rare disease-associated cell subsets via representation learning.

Nature communications Apr 6, 2017
Rare cell populations play a pivotal role in the initiation and progression of diseases such as cancer. However, the identification of such subpopulations remains a difficult task. This work describes CellCnn, a representation learning approach to de...
Humans Neural Networks, Computer Cytokines Prognosis Single-Cell Analysis Monocytes Signal Transduction Acquired Immunodeficiency Syndrome Cytomegalovirus Infections Supervised Machine Learning Survival Analysis Killer Cells, Natural T-Lymphocyte Subsets Rare Diseases Neoplasm, Residual Leukemia Immunologic Memory
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High-dimensional profiling clusters asthma severity by lymphoid and non-lymphoid status.

Cell reports Apr 13, 2021
Clinical definitions of asthma fail to capture the heterogeneity of immune dysfunction in severe, treatment-refractory disease. Applying mass cytometry and machine learning to bronchoalveolar lavage (BAL) cells, we find that corticosteroid-resistant ...
Humans Machine Learning Interleukin-10 Macrophages Asthma Severity of Illness Index Gene Expression Profiling Case-Control Studies Proteomics Signal Transduction Immunity, Innate CD8-Positive T-Lymphocytes CD4-Positive T-Lymphocytes Gene Expression Regulation Interferon-gamma Bronchoalveolar Lavage Fluid Adrenal Cortex Hormones Anti-Asthmatic Agents Adaptive Immunity Immunologic Memory Interleukin-7 Receptors, IgE
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