Yaping Guo

1.6k total citations · 1 hit paper
26 papers, 756 citations indexed

About

Yaping Guo is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Yaping Guo has authored 26 papers receiving a total of 756 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 7 papers in Pulmonary and Respiratory Medicine and 6 papers in Oncology. Recurrent topics in Yaping Guo's work include Machine Learning in Bioinformatics (4 papers), Ferroptosis and cancer prognosis (4 papers) and RNA modifications and cancer (4 papers). Yaping Guo is often cited by papers focused on Machine Learning in Bioinformatics (4 papers), Ferroptosis and cancer prognosis (4 papers) and RNA modifications and cancer (4 papers). Yaping Guo collaborates with scholars based in China, United States and South Korea. Yaping Guo's co-authors include Yu Xue, Wanshan Ning, Peiran Jiang, Shaofeng Lin, Wankun Deng, Di Peng, Xiaodan Tan, Ying Zhang, Yang Xu and Chenwei Wang and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Oncogene.

In The Last Decade

Yaping Guo

26 papers receiving 755 citations

Hit Papers

Ubiquitous protein lactylation in health and diseases 2024 2026 2025 2024 10 20 30 40 50
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Ubiquitous protein lactylation in health and diseases
    2024 57 citations Ziyi Wang, Xiao Li et al. Cellular & Molecular Biology Letters profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Yaping Guo China 13 501 108 106 76 72 26 756
Wanshan Ning China 15 539 1.1× 110 1.0× 77 0.7× 67 0.9× 39 0.5× 29 858
Srikant Verma India 5 595 1.2× 38 0.4× 129 1.2× 42 0.6× 86 1.2× 5 891
Jianlun Liu China 13 418 0.8× 67 0.6× 211 2.0× 156 2.1× 70 1.0× 37 770
Yulan Zeng China 14 191 0.4× 114 1.1× 89 0.8× 191 2.5× 136 1.9× 39 633
Minjie Mou China 14 664 1.3× 40 0.4× 123 1.2× 65 0.9× 64 0.9× 30 941
Lulu Li China 13 224 0.4× 33 0.3× 124 1.2× 69 0.9× 63 0.9× 24 457
Mikhail A. Pyatnitskiy Russia 16 537 1.1× 49 0.5× 70 0.7× 59 0.8× 35 0.5× 48 875
K. Sujathan India 15 240 0.5× 48 0.4× 58 0.5× 76 1.0× 57 0.8× 49 633
Peiran Jiang China 9 369 0.7× 114 1.1× 50 0.5× 31 0.4× 25 0.3× 12 583
Ziqing Yang China 12 255 0.5× 54 0.5× 99 0.9× 57 0.8× 62 0.9× 45 464

Countries citing papers authored by Yaping Guo

Since Specialization
Citations

This map shows the geographic impact of Yaping Guo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yaping Guo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yaping Guo more than expected).

Fields of papers citing papers by Yaping Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yaping Guo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yaping Guo. The network helps show where Yaping Guo may publish in the future.

Co-authorship network of co-authors of Yaping Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Yaping Guo. A scholar is included among the top collaborators of Yaping Guo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yaping Guo. Yaping Guo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ning, Wanshan, et al.. (2025). HybridKla: a hybrid deep learning framework for lactylation site prediction. Briefings in Bioinformatics. 26(4). 1 indexed citations
2.
Yuan, Qiang, Xiaoyu Li, Jimin Zhao, et al.. (2025). p38 mediated ACSL4 phosphorylation drives stress-induced esophageal squamous cell carcinoma growth through Src myristoylation. Nature Communications. 16(1). 3319–3319. 1 indexed citations
3.
Wang, Jiaxue, Bing Han, Hui Tao, et al.. (2025). Biodetoxification of both AFB1 and ZEN by Bacillus subtilis ZJ-2019–1 in gastrointestinal environment and in mice. Mycotoxin Research. 41(2). 349–358. 1 indexed citations
4.
Wang, Ziyi, et al.. (2024). Ubiquitous protein lactylation in health and diseases. Cellular & Molecular Biology Letters. 29(1). 23–23. 57 indexed citations breakdown →
5.
Guo, Yaping, et al.. (2024). Hepatic regulator of G protein signaling 14 ameliorates NAFLD through activating cAMP-AMPK signaling by targeting Giα1/3. Molecular Metabolism. 80. 101882–101882. 5 indexed citations
6.
Guo, Yaping, Huifang Wei, Xuechao Jia, et al.. (2024). Multi-omics characterization of esophageal squamous cell carcinoma identifies molecular subtypes and therapeutic targets. JCI Insight. 9(10). 2 indexed citations
7.
Yuan, Qiang, Yuhan Zhang, Zubair Hussain, et al.. (2024). Domperidone inhibits cell proliferation via targeting MEK and CDK4 in esophageal squamous cell carcinoma. Cancer Cell International. 24(1). 114–114. 1 indexed citations
8.
9.
He, Xinyu, Wenjing Chen, Hao Zhou, et al.. (2023). Repurposed pizotifen malate targeting NRF2 exhibits anti-tumor activity through inducing ferroptosis in esophageal squamous cell carcinoma. Oncogene. 42(15). 1209–1223. 22 indexed citations
10.
Yuan, Qiang, Yi Chu, Xiaoyu Li, et al.. (2023). CAFrgDB: a database for cancer-associated fibroblasts related genes and their functions in cancer. Cancer Gene Therapy. 30(6). 917–925. 2 indexed citations
11.
He, Xinyu, Yanan Jiang, Zitong Wang, et al.. (2022). Repurposed benzydamine targeting CDK2 suppresses the growth of esophageal squamous cell carcinoma. Frontiers of Medicine. 17(2). 290–303. 12 indexed citations
12.
Bai, Liuyang, Yaping Guo, Luyun He, et al.. (2022). Perineural Invasion Is a Significant Indicator of High Malignant Degree and Poor Prognosis in Esophageal Cancer: A Systematic Review and Meta-Analysis. Frontiers in Oncology. 12. 816270–816270. 3 indexed citations
13.
Jiang, Peiran, et al.. (2021). FSL-Kla: A few-shot learning-based multi-feature hybrid system for lactylation site prediction. Computational and Structural Biotechnology Journal. 19. 4497–4509. 40 indexed citations
14.
Wu, Xiangyu, Zitong Wang, Yanan Jiang, et al.. (2021). Tegaserod Maleate Inhibits Esophageal Squamous Cell Carcinoma Proliferation by Suppressing the Peroxisome Pathway. Frontiers in Oncology. 11. 683241–683241. 12 indexed citations
15.
Ning, Wanshan, Haodong Xu, Peiran Jiang, et al.. (2020). HybridSucc: A Hybrid-Learning Architecture for General and Species-Specific Succinylation Site Prediction. Genomics Proteomics & Bioinformatics. 18(2). 194–207. 34 indexed citations
16.
Ning, Wanshan, Shijun Lei, Jingjing Yang, et al.. (2020). Open resource of clinical data from patients with pneumonia for the prediction of COVID-19 outcomes via deep learning. Nature Biomedical Engineering. 4(12). 1197–1207. 131 indexed citations
17.
Guo, Yaping, Wanshan Ning, Peiran Jiang, et al.. (2020). GPS-PBS: A Deep Learning Framework to Predict Phosphorylation Sites that Specifically Interact with Phosphoprotein-Binding Domains. Cells. 9(5). 1266–1266. 14 indexed citations
18.
Ning, Wanshan, Peiran Jiang, Yaping Guo, et al.. (2020). GPS-Palm: a deep learning-based graphic presentation system for the prediction ofS-palmitoylation sites in proteins. Briefings in Bioinformatics. 22(2). 1836–1847. 85 indexed citations
19.
Zhang, Ying, Yubin Xie, Wenzhong Liu, et al.. (2019). DeepPhagy: a deep learning framework for quantitatively measuring autophagy activity in Saccharomyces cerevisiae. Autophagy. 16(4). 626–640. 17 indexed citations
20.
Zhou, Jiaqi, Yang Xu, Shaofeng Lin, et al.. (2017). iUUCD 2.0: an update with rich annotations for ubiquitin and ubiquitin-like conjugations. Nucleic Acids Research. 46(D1). D447–D453. 77 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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