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Yingjie Li on Muck Rack

Yingjie Li

As seen in: The Startup, Nature, Wiley Online Library, arXiv, Frontiers, MDPI, Taylor & Francis Online, The BMJ, ACS Publications, Arthritis Research & Therapy and
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Articles

Adaptive dual-space discriminator for large-scale multi-objective optimization

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By Ziyi Xue, Yingjie Li, Gang Xin, Kaidong Cheng, Xunze Liu
| Nature Verified
Abstract Numerous real-world applications involve large-scale multi-objective optimization problems (LSMOPs) with hundreds or even thousands of decision variables. Although multi-objective evolutionary algorithms (MOEAs) are effective for such tasks, relying solely on objective-space information often provides insufficient selection pressure in high-dimensional settings.
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Genome-directed discovery of an octalin-containing polyether ionophore improves diabetic skin wound healing

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By Chunyan Fang, Zhiwen Liu, Liangliang Bai, Liang Ma, Weiliang Xiong, Lili Sun, Linping Wu, Jing Ni, Wenjun Zhang, Yiguang Zhu, Yanxin Luo, Yingjie Li, Changsheng Zhang
| Nature Verified
Abstract Chronic hard-to-heal skin wounds in diabetes mellitus pose a significant clinical challenge, underscoring the urgent need for additional therapeutics. Herein, we report the identification of a polyether biosynthetic gene cluster (pdm BGC) from the marine-derived Streptomyces marincola SCSIO 03032 through genome mining.
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New insights from data analysis of 12 global clinical studies on hair shedding

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By Yingjie Li, Shengnan Lin, Wellbeing Shanghai
| Wiley Online Library Verified
INTRODUCTION Hair loss is a prevalent condition that affects both men and women worldwide. The incidence of male and female pattern hair loss has been documented across different regions, including UK, US, Norway, Asia and Australia [1-3], with variations observed according to ethnicity, gender and age. Hair loss can be classified into several types, such as androgenic alopecia, male or female pattern hair loss, telogen effluvium, alopecia areata and traction alopecia.
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