Probing T-cell response by sequence-based probabilistic modeling

Probing T-cell response by sequence-based probabilistic modeling

With the increasing ability to use high-throughput next-generation sequencing to quantify the diversity of the human T cell receptor (TCR) repertoire, the ability to use TCR sequences to infer antigen-specificity could greatly aid potential diagnostics and therapeutics. Here, we use a machine-learni...

Full description

Bibliographic Details
Main Authors: Balachandran, V.P (Author), Bravi, B. (Author), Cocco, S. (Author), Greenbaum, B.D (Author), Monasson, R. (Author), Mora, T. (Author), Walczak, A.M (Author)
Format: Article
Language:English
Published: Public Library of Science 2021
Subjects:
antigen function
antigen specificity
Article
biology
cancer survivor
Cancer Survivors
Carcinoma, Pancreatic Ductal
cell expansion
cluster analysis
Cluster Analysis
cohort analysis
Computational Biology
Datasets as Topic
epitope
human
human cell
Humans
immunology
infection
information processing
lymphocyte antigen receptor
lymphocyte clone
machine learning
mathematical model
Models, Statistical
pancreas carcinoma
pancreas tumor
Pancreatic Neoplasms
procedures
Receptors, Antigen, T-Cell
restricted Boltzmann machine
statistical model
T lymphocyte
T lymphocyte receptor
T-Lymphocytes
tumor growth
Online Access:View Fulltext in Publisher

Internet

View Fulltext in Publisher

Similar Items