Enhancing single-cell biology through advanced AI-powered microfluidics

被引:5
|
作者
Gao, Zhaolong [1 ]
Li, Yiwei [1 ]
机构
[1] Huazhong Univ Sci & Technol, Coll Life Sci & Technol, Dept Biomed Engn, Key Lab Biomed Photon MOE,Wuhan Natl Lab Optoelect, Wuhan 430074, Peoples R China
基金
中国国家自然科学基金;
关键词
Cell signaling - Cells - Clinical research - Cytology - Diagnosis;
D O I
10.1063/5.0170050
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Microfluidic technology has largely benefited both fundamental biological research and translational clinical diagnosis with its advantages in high-throughput, single-cell resolution, high integrity, and wide-accessibility. Despite the merits we obtained from microfluidics in the last two decades, the current requirement of intelligence in biomedicine urges the microfluidic technology to process biological big data more efficiently and intelligently. Thus, the current readout technology based on the direct detection of the signals in either optics or electrics was not able to meet the requirement. The implementation of artificial intelligence (AI) in microfluidic technology matches up with the large-scale data usually obtained in the high-throughput assays of microfluidics. At the same time, AI is able to process the multimodal datasets obtained from versatile microfluidic devices, including images, videos, electric signals, and sequences. Moreover, AI provides the microfluidic technology with the capability to understand and decipher the obtained datasets rather than simply obtaining, which eventually facilitates fundamental and translational research in many areas, including cell type discovery, cell signaling, single-cell genetics, and diagnosis. In this Perspective, we will highlight the recent advances in employing AI for single-cell biology and present an outlook on the future direction with more advanced AI algorithms.
引用
收藏
页数:6
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