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Shengli Yin

As seen in: Nature, Optica
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Articles

Revealing genetic foundations underlying cardiometabolic traits: integrating twin and GWAS data in Asian populations

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By Xuanming Hong, Ming Li, Weihua Cao, Jun Lv, Canqing Yu, Tao Huang, Dianjianyi Sun, Chunxiao Liao, Yuanjie Pang, Runhua Hu, Ruqin Gao, Min Yu, Jinyi Zhou, Xianping Wu, Yu Chi Liu, Shengli Yin, Wenjing Gao
| Nature Verified
Abstract Traditional twin studies have reported high heritability estimates for common cardiometabolic traits, yet discrepancies compared to genome-wide association studies (GWAS) derived estimates underscore the effects of “missing heritability”, potentially attributed to genetic interactions and environmental influences. However, research exploring potential contributors to missing heritability in cardiometabolic phenotypes remains scarce and largely confined to European populations.
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Wind vector retrieval algorithm for a coherent Doppler lidar based on KNN-COOKS

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By Jie Yu, Rongzheng Cao, Shengli Yin, Junshuai Liu
| Optica Verified
The wind vector retrieval from a coherent Doppler lidar system in the plan position indicator (PPI) scanning mode often suffers from high inversion errors in horizontal wind speed and direction at far-range gates due to “erroneous” radial wind speed. To address this, we propose a weighted sine wave fitting algorithm that combines K-nearest neighbors and Cook’s distance (KNN-COOKS).
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