@eawag.bsky.social , #UZH & beyond
@eawag.bsky.social , #UZH & beyond
Thx to my fellow co-authors: #MarjorieCouton #LucaCarraro @francoiskeck.bsky.social @lorihandley.bsky.social @leeselab.bsky.social #XiaoweiZhang #YanZhang & @rosiecblackman.bsky.social ; @eawag.bsky.social #UZH @alexmckay.bsky.social
Thx to my fellow co-authors: #MarjorieCouton #LucaCarraro @francoiskeck.bsky.social @lorihandley.bsky.social @leeselab.bsky.social #XiaoweiZhang #YanZhang & @rosiecblackman.bsky.social ; @eawag.bsky.social #UZH @alexmckay.bsky.social
This demonstrate the power of eDNA-based datasets offering a scalable approach for #detecting and #attributing #biodiversity change and informing conservation strategies under accelerating global change.
Great collaboration across many labs & datasets!
Led by #YanZhang #UZH @eawag.bsky.social
This demonstrate the power of eDNA-based datasets offering a scalable approach for #detecting and #attributing #biodiversity change and informing conservation strategies under accelerating global change.
Great collaboration across many labs & datasets!
Led by #YanZhang #UZH @eawag.bsky.social
👉 onlinelibrary.wiley.com/journal/1365...
👉 onlinelibrary.wiley.com/journal/1365...
“Mineral biosignature identification from Raman spectroscopy using machine learning” by Yanzhang Li et al. earned a score of 38, driven by strong media attention. Read more: https://ow.ly/pXuK50ZENap
“Mineral biosignature identification from Raman spectroscopy using machine learning” by Yanzhang Li et al. earned a score of 38, driven by strong media attention. Read more: https://ow.ly/pXuK50ZENap
Yanzhao Wang, Yanzhang Shao, Dan Liu, Zhixuan Hu, Yifei Xu, Huanhuan Gao, Xihong Wang, Xiaogang Su, Fei Ding*, He Xiu Xu*
Nano-Micro Lett. (2026) 18:445
doi.org/10.1007/s408...
Yanzhao Wang, Yanzhang Shao, Dan Liu, Zhixuan Hu, Yifei Xu, Huanhuan Gao, Xihong Wang, Xiaogang Su, Fei Ding*, He Xiu Xu*
Nano-Micro Lett. (2026) 18:445
doi.org/10.1007/s408...
en.wikipedia.org/wiki/Zhao_Ti...
en.wikipedia.org/wiki/Zhao_Ti...
“Mineral biosignature identification from Raman spectroscopy using machine learning” by Yanzhang Li et al. earned a score of 38, driven by strong media attention. Read more: https://ow.ly/1Jyh50ZENCW
“Mineral biosignature identification from Raman spectroscopy using machine learning” by Yanzhang Li et al. earned a score of 38, driven by strong media attention. Read more: https://ow.ly/1Jyh50ZENCW
https://arxiv.org/pdf/2605.00104
Yanzhang Zhu, Zhe Wang, Meng Cheng, Zheng Yan.
https://arxiv.org/pdf/2605.00104
Yanzhang Zhu, Zhe Wang, Meng Cheng, Zheng Yan.
https://arxiv.org/pdf/2508.07277
Yanzhang Zhu, Zenan Liu, Zhe Wang, Yan-Cheng Wang, Zheng Yan.
https://arxiv.org/pdf/2508.07277
Yanzhang Zhu, Zenan Liu, Zhe Wang, Yan-Cheng Wang, Zheng Yan.
https://arxiv.org/pdf/2507.20556
Yanzhang He, Yimin Liu, Chengguang Bao.
https://arxiv.org/pdf/2507.20556
Yanzhang He, Yimin Liu, Chengguang Bao.