High-fidelity in silico generation and augmentation of TCR repertoire data using generative adversarial networks

High-fidelity in silico generation and augmentation of TCR repertoire data using generative adversarial networks

Abstract Engineered T-cell receptor (eTCR) systems rely on accurately generated T-cell receptor (TCR) sequences to enhance immunotherapy predictability and efficacy. The most variable and crucial part of the TCR receptor is the CDR3 sequence region. Current methods for generating CDR3 sequences, inc...

Full description

Saved in:
Bibliographic Details
Main Authors: Piotr Religa, Michel-Edwar Mickael, Norwin Kubick, Jarosław Olav Horbańczuk, Nikko Floretes, Mariusz Sacharczuk, Atanas G. Atanasov
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-025-01172-2
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1038/s41598-025-01172-2

Similar Items