Deciphering the cellular and molecular landscape of pulmonary fibrosis through single-cell sequencing and machine learning

Deciphering the cellular and molecular landscape of pulmonary fibrosis through single-cell sequencing and machine learning

Abstract Pulmonary fibrosis is characterized by progressive lung scarring, leading to a decline in lung function and an increase in morbidity and mortality. This study leverages single-cell sequencing and machine learning to unravel the complex cellular and molecular mechanisms underlying pulmonary...

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Bibliographic Details
Main Authors: Yong Zhou, Zhongkai Tong, Xiaoxiao Zhu, Chunli Wu, Ying Zhou, Zhaoxing Dong
Format: Article
Language:English
Published: BMC 2025-01-01
Series:Journal of Translational Medicine
Subjects:
Pulmonary fibrosis
Single-cell sequencing
Machine learning
Diagnostic biomarkers
Immune cell profiling
Online Access:https://doi.org/10.1186/s12967-024-06031-8
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https://doi.org/10.1186/s12967-024-06031-8

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