Skip To Main Content
Yanying Guo on Muck Rack

Yanying Guo

As seen in: Nature, MDPI, BioRxiv, Dove Medical Press
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile

Get in touch with Yanying

Contact Yanying, search articles and posts on X, monitor coverage, and track replies from one place.

Learn more about Muck Rack

Actions

Share this page

Is this you?

As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work.
Claim your profile

Articles

Uncovering ectopic GC-like niches for tumor reactive lymphocyte priming in lung adenocarcinoma using Stereo-XCR-seq

|
By Xiaojuan Zhan, Yang Zhang, Zhong Liu, Chengwu Liu, Yanying Guo, Yi Liu, Wenwen Zhou, Yixin Yan, Hui Zeng, Xuan Dong, Xiaoyu Chen, Rong Ma, Fan Zhu, Xubin Zheng, Xinxing Li, Sen Hou, Zhidong Gao, Jinwen Yin, Francis Chan, Qin Wu, Senyi Deng, Yin Yao, Shengbao Suo, Chuanyu Liu, Longqi Liu, Xun Xu, Yong Hou, HaoRan Tao, Yuliang Dong, Tao Zeng, Hanyong Sun, Li Zuo, Hua Wang, Xin Zhe Liu, Zhifang Wu, Jingying Zhou, Zexian Zeng, Yu Feng, Mengye Huang, Yingqi Dong, Haohang Yang, Xinlei Ai
| Nature Verified
Abstract T/B cell receptors (T/BCR), coordinating antigen-targeting immune response, play crucial roles in anti-tumor immune response. Tracking T and B cell clonal evolution in situ at single-cell resolution is essential for understanding the adaptive immune responses.
Open in Who Shared Issue with article?

Explainable deep learning framework incorporating medical knowledge for insulin titration in diabetes - Communications Medicine

|
By Haowei He, Zhen Ying, Biao Li, Yujuan Fan, Ping Wang, Jiaping Lu, Liming Wu, Yanying Guo, Guangyu Wang, Yang Yuan, Ying Chen, Xiaoying Li, Hexu Zhao
| Nature Verified
Abstract Deep learning has shown promise in diabetes management but faces challenges in real-world application due to its “black-box” nature, characterized by opaque internal decision-making processes. Explainable artificial intelligence (XAI) methods have been proposed to enhance model transparency. However, most of current XAI methods applied in the medical field often ignore the interaction of features in complex environments and pose deviation from clinical domain knowledge.
Open in Who Shared Issue with article?

Inhibition of TWEAK/Fn14 Ameliorates Sarcopenic Obesity by Restoring Mitochondrial Biogenesis via the AMPK/SIRT1/PGC-1α Axis

|
By Saiyare Xuekelati, Zhuoya Maimaitiwusiman, Yanying Guo
| Dove Medical Press
Back to Journals » Diabetes, Metabolic Syndrome and Obesity » Volume 19 Original Research Metabolic Disorders and Complications Authors Xuekelati S , Maimaitiwusiman Z, Guo Y, Guo S, Xu Q , Ke J, Xu L, Yang Y , Wang H Received 30 January 2026 Accepted for publication 5 May 2026 Published 18 May 2026 Volume 2026:19 596507 DOI https://doi.org/10.2147/DMSO.S596507 Checked for plagiarism Yes Review by Single anonymous peer review Peer reviewer comments 2 Editor who approved publication: Professor...
Open in Who Shared Issue with article?
See all 5 articles