Application of CRISPR Technology in Influenza Detection

Luping Ding

2025

Abstract

This study explores the application of CRISPR technology in influenza detection, detailing its technical principles, advantages, practical applications, and challenges. Originating from the bacterial adaptive immune system, CRISPR has demonstrated significant potential in detecting influenza A and B viruses due to its high specificity, sensitivity, and rapid detection capabilities. The CRISPR-Cas system, particularly Cas12 and Cas13, enables precise recognition of viral RNA or DNA, making it a promising tool for early and accurate diagnosis. However, the lack of standardized protocols remains a key challenge, affecting the reproducibility and comparability of test results across different laboratories. Despite these limitations, ongoing advancements in CRISPR-based diagnostic platforms, such as SHERLOCK and DETECTR, are expected to enhance the efficiency and accessibility of influenza detection. With continuous optimization, CRISPR holds great promise for strengthening infectious disease surveillance and prevention, providing a crucial safeguard for global public health.

Paper Citation

in Harvard Style

Ding L. (2025). Application of CRISPR Technology in Influenza Detection. In Proceedings of the 1st International Conference on Biomedical Engineering and Food Science - Volume 1: BEFS; ISBN 978-989-758-789-4, SciTePress, pages 453-457. DOI: 10.5220/0014499100004933

in Bibtex Style

@conference{befs25,
author={Luping Ding},
title={Application of CRISPR Technology in Influenza Detection},
booktitle={Proceedings of the 1st International Conference on Biomedical Engineering and Food Science - Volume 1: BEFS},
year={2025},
pages={453-457},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0014499100004933},
isbn={978-989-758-789-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Biomedical Engineering and Food Science - Volume 1: BEFS
TI - Application of CRISPR Technology in Influenza Detection
SN - 978-989-758-789-4
AU - Ding L.
PY - 2025
SP - 453
EP - 457
DO - 10.5220/0014499100004933
PB - SciTePress