AIMC Topic: T-Lymphocytes

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T cell immune responses deciphered.

Science (New York, N.Y.) May 19, 2022
A machine-learning approach reveals antigen encoding that predicts T cell responses.
Adaptive Immunity Antigen Presentation Humans Machine Learning Animals T-Lymphocytes Mice Antigens
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Cross-tissue immune cell analysis reveals tissue-specific features in humans.

Science (New York, N.Y.) May 13, 2022
Despite their crucial role in health and disease, our knowledge of immune cells within human tissues remains limited. We surveyed the immune compartment of 16 tissues from 12 adult donors by single-cell RNA sequencing and VDJ sequencing generating a ...
Humans Machine Learning Cells, Cultured Sequence Analysis, RNA B-Lymphocytes T-Lymphocytes Organ Specificity Transcriptome Single-Cell Analysis
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iTTCA-MFF: identifying tumor T cell antigens based on multiple feature fusion.

Immunogenetics Mar 5, 2022
Cancer is a terrible disease, recent studies reported that tumor T cell antigens (TTCAs) may play a promising role in cancer treatment. Since experimental methods are still expensive and time-consuming, it is highly desirable to develop automatic com...
T-Lymphocytes Neoplasms Computational Biology Humans Algorithms Amino Acids Amino Acid Sequence Mitochondrial Proteins Membrane Proteins Support Vector Machine
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Rapid, label-free classification of tumor-reactive T cell killing with quantitative phase microscopy and machine learning.

Scientific reports Sep 30, 2021
Quantitative phase microscopy (QPM) enables studies of living biological systems without exogenous labels. To increase the utility of QPM, machine-learning methods have been adapted to extract additional information from the quantitative phase data. ...
T-Lymphocytes Cell Line, Tumor Microscopy, Phase-Contrast Machine Learning Melanoma Time-Lapse Imaging Humans
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Development of quantitative model of a local lymph node assay for evaluating skin sensitization potency applying machine learning CatBoost.

Regulatory toxicology and pharmacology : RTP Jul 24, 2021
The estimated concentrations for a stimulation index of 3 (EC3) in murine local lymph node assay (LLNA) is an important quantitative value for determining the strength of skin sensitization to chemicals, including cosmetic ingredients. However, anima...
Dermatitis, Allergic Contact United Nations Keratinocytes Animal Testing Alternatives Local Lymph Node Assay Cell Line Machine Learning Europe Databases, Factual Animals T-Lymphocytes Humans Dendritic Cells Mice
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Structural constraints in T-cell repertoire selection predicted by machine learning.

Genes and immunity Jul 12, 2021
Machine Learning T-Lymphocytes Lymphocyte Activation
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The Immune Subtypes and Landscape of Gastric Cancer and to Predict Based on the Whole-Slide Images Using Deep Learning.

Frontiers in immunology Jun 28, 2021
BACKGROUND: Gastric cancer (GC) is a highly heterogeneous tumor with different responses to immunotherapy. Identifying immune subtypes and landscape of GC could improve immunotherapeutic strategies.
Deep Learning Immunotherapy Aged Middle Aged Biomarkers, Tumor T-Lymphocytes Male Humans Macrophages Transcriptome Prognosis Female Reproducibility of Results Stomach Neoplasms Tumor Microenvironment
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Ligand Nanocluster Array Enables Artificial-Intelligence-Based Detection of Hidden Features in T-Cell Architecture.

Nano letters Jun 25, 2021
Protein patterning has emerged as a powerful means to interrogate adhering cells. However, the tools to apply a sub-micrometer periodic stimulus and the analysis of the response are still being standardized. We propose a technique combining electron ...
Humans Artificial Intelligence Ligands T-Lymphocytes Printing Intelligence
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Applications of Machine and Deep Learning in Adaptive Immunity.

Annual review of chemical and biomolecular engineering Apr 14, 2021
Adaptive immunity is mediated by lymphocyte B and T cells, which respectively express a vast and diverse repertoire of B cell and T cell receptors and, in conjunction with peptide antigen presentation through major histocompatibility complexes (MHCs)...
T-Lymphocytes Deep Learning Receptors, Antigen, T-Cell Adaptive Immunity
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DeepTCR is a deep learning framework for revealing sequence concepts within T-cell repertoires.

Nature communications Mar 11, 2021
Deep learning algorithms have been utilized to achieve enhanced performance in pattern-recognition tasks. The ability to learn complex patterns in data has tremendous implications in immunogenomics. T-cell receptor (TCR) sequencing assesses the diver...
Databases, Genetic Amino Acid Sequence High-Throughput Nucleotide Sequencing Receptors, Antigen, T-Cell Mice Humans T-Lymphocytes Neural Networks, Computer Deep Learning Algorithms RNA-Seq Animals
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