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Wenjie Yin

As seen in: Nature, Wiley Online Library, MDPI, Science Magazine, Cell Press, Mechanical Engineering Magazine, Journal of Risk
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Articles

A chemistry-informed deep learning network for mitigating the stratospheric OH data gap

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By Harold F. Levison, Jessica Wan, Louise Brennan, Wenjie Yin, Chen Zhou, Wuhu Feng, Sandip Dhomse, Richard Pope, Luis Millán, Martyn P. Chipperfield
| Science Magazine Verified
Abstract INTRODUCTION RESULTS DISCUSSION MATERIALS AND METHODS Acknowledgments Supplementary Materials REFERENCES Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract The hydroxyl (OH) radical is a key species in stratospheric chemistry, driving ozone loss and the coupling of other chemical families. However, global OH observations are very sparse, with a critical gap in satellite-based observations since 2009.
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Scale-dependent model-observation inconsistencies in global terrestrial water storage models - Communications Earth & Environment

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By Gangqiang Zhang, Tongren Xu, Shaomin Liu, Liqiang Zhang, Sayed M. Bateni, Jianzhi Dong, Wenjie Yin
| Nature Verified
Abstract Accurate representation of terrestrial water storage is essential for water resource management and climate adaptation, yet model‑observation inconsistencies hinder global water cycle assessment. Here we show, using a unified multi‑scale framework, that seven model products with diverse modeling strategies and varying structural completeness exhibit scale‑dependent performance against Gravity Recovery and Climate Experiment observations across global, climate-zone, and basin scales.
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Hypoxia‐induced regional heterogeneity in proliferative vitreoretinopathy: implications for targeted therapies

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By Wenjie Yin, Miao Xu, Yan Gao, Zixuan Niu
| Wiley Online Library Verified
Data availability statement The gene expression microarray data for human retinal detachment specimens were downloaded from the Gene Expression Omnibus (GEO) database (accession number GSE28133; https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28133) for analysis. Single-cell transcriptomic data for healthy human retina were obtained from GSE155288 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE155288).
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