Interpretable Aging Signatures in Human Retinal Cell Types Revealed by Single-Cell RNA Sequencing and Sparse Logistic Regression.

Luning Yang, Sen Lin, Yiwen Tao, Qi Pan, Tengda Cai, Yunyan Ye, Jianhui Liu, Yang Zhou, Yongqing Shao, Quanyong Yi, Zen Huat Lu, Lie Chen, Gareth McKay, Richard Rankin, Fan Li, Weihua Meng

Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, University of Nottingham Ningbo China, Ningbo, China.Nottingham Ningbo China Beacons of Excellence Research and Innovation Institute, University of Nottingham Ningbo China, Ningbo, China. · pubmed

Paper

Abstract

To characterize cell-type-specific transcriptional changes during human retinal aging and develop machine learning (ML) model for cellular age discrimination in a Chinese cohort.

The following analysis is generated by AI and may contain errors. It is separate from the authors’ abstract and is not peer review.

Research summary

The paper claims to identify cell-type-specific transcriptional changes in human retinal aging and develop a machine learning model for cellular age discrimination. This research is relevant as it seeks to understand the biological mechanisms of aging at the cellular level, which could contribute to insights into longevity and age-related diseases.

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