Wankun Deng

3.3k total citations · 1 hit paper
28 papers, 2.2k citations indexed

About

Wankun Deng is a scholar working on Molecular Biology, Epidemiology and Oncology. According to data from OpenAlex, Wankun Deng has authored 28 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 6 papers in Epidemiology and 4 papers in Oncology. Recurrent topics in Wankun Deng's work include Autophagy in Disease and Therapy (5 papers), Machine Learning in Bioinformatics (4 papers) and Ubiquitin and proteasome pathways (4 papers). Wankun Deng is often cited by papers focused on Autophagy in Disease and Therapy (5 papers), Machine Learning in Bioinformatics (4 papers) and Ubiquitin and proteasome pathways (4 papers). Wankun Deng collaborates with scholars based in China, United States and Macao. Wankun Deng's co-authors include Yu Xue, Yongbo Wang, Zexian Liu, Han Cheng, Ying Zhang, Shaofeng Lin, Haodong Xu, Jiaqi Zhou, Di Peng and Chenwei Wang and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and The Journal of Cell Biology.

In The Last Decade

Wankun Deng

27 papers receiving 2.2k citations

Hit Papers

HemI: A Toolkit for Illustrating Heatmaps 2014 2026 2018 2022 2014 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wankun Deng China 21 1.5k 408 180 171 165 28 2.2k
Chong Wang China 27 1.3k 0.8× 471 1.2× 83 0.5× 140 0.8× 190 1.2× 115 2.2k
Han Cheng China 22 1.6k 1.1× 560 1.4× 124 0.7× 147 0.9× 117 0.7× 82 2.5k
Yongbo Wang China 15 1.1k 0.7× 372 0.9× 118 0.7× 109 0.6× 89 0.5× 25 1.7k
Beibei Wang China 28 1.2k 0.8× 518 1.3× 150 0.8× 159 0.9× 165 1.0× 185 2.6k
Chunyuan Yang China 8 1.1k 0.7× 210 0.5× 132 0.7× 144 0.8× 143 0.9× 15 1.8k
Dongxue Wang China 24 1.4k 0.9× 401 1.0× 111 0.6× 125 0.7× 75 0.5× 83 2.2k
Markus Schröder Germany 22 854 0.6× 221 0.5× 255 1.4× 136 0.8× 144 0.9× 48 1.9k
Kunxian Shu China 12 984 0.7× 190 0.5× 99 0.6× 167 1.0× 122 0.7× 53 1.7k
John Braisted United States 18 1.7k 1.1× 437 1.1× 112 0.6× 249 1.5× 113 0.7× 40 2.8k
Anand Bachhawat India 27 1.7k 1.1× 415 1.0× 154 0.9× 166 1.0× 230 1.4× 86 2.5k

Countries citing papers authored by Wankun Deng

Since Specialization
Citations

This map shows the geographic impact of Wankun Deng'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 Wankun Deng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wankun Deng more than expected).

Fields of papers citing papers by Wankun Deng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wankun Deng. 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 Wankun Deng. The network helps show where Wankun Deng may publish in the future.

Co-authorship network of co-authors of Wankun Deng

This figure shows the co-authorship network connecting the top 25 collaborators of Wankun Deng. A scholar is included among the top collaborators of Wankun Deng 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 Wankun Deng. Wankun Deng 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.
2.
Wang, Mingqiang, Wankun Deng, David C. Samuels, Zhongming Zhao, & Lukas M. Simon. (2023). MitoTrace: A Computational Framework for Analyzing Mitochondrial Variation in Single-Cell RNA Sequencing Data. Genes. 14(6). 1222–1222. 2 indexed citations
3.
Wang, Chenwei, Xuran Zhuang, Shaofeng Lin, et al.. (2022). PIM1 promotes hepatic conversion by suppressing reprogramming-induced ferroptosis and cell cycle arrest. Nature Communications. 13(1). 5237–5237. 11 indexed citations
4.
Liao, Chenyi, Jiao Qin, Yanqiu Gong, et al.. (2021). Phosphorylation of SNX27 by MAPK11/14 links cellular stress–signaling pathways with endocytic recycling. The Journal of Cell Biology. 220(4). 28 indexed citations
5.
Zhu, Han, Weizhi Zhang, Wanshan Ning, et al.. (2021). Model-based analysis uncovers mutations altering autophagy selectivity in human cancer. Nature Communications. 12(1). 3258–3258. 22 indexed citations
6.
Ruan, Chen, Chenwei Wang, Xuanqing Gong, et al.. (2020). An integrative multi-omics approach uncovers the regulatory role of CDK7 and CDK4 in autophagy activation induced by silica nanoparticles. Autophagy. 17(6). 1426–1447. 40 indexed citations
7.
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
8.
Wang, Chenwei, Shaofeng Lin, Ying Zhang, et al.. (2020). Integrated omics in Drosophila uncover a circadian kinome. Nature Communications. 11(1). 2710–2710. 24 indexed citations
9.
Xin, Yong, Lin Zhao, Wankun Deng, et al.. (2020). Mechanism of cargo recognition by retromer-linked SNX-BAR proteins. PLoS Biology. 18(3). e3000631–e3000631. 57 indexed citations
10.
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
11.
Xu, Haodong, Yongbo Wang, Shaofeng Lin, et al.. (2018). PTMD: A Database of Human Disease-Associated Post-Translational Modifications. Genomics Proteomics & Bioinformatics. 16(4). 244–251. 141 indexed citations
12.
Xu, Haodong, Jiaqi Zhou, Shaofeng Lin, et al.. (2017). PLMD: An updated data resource of protein lysine modifications. Journal of genetics and genomics. 44(5). 243–250. 181 indexed citations
13.
Deng, Wankun, Lili Ma, Ying Zhang, et al.. (2017). THANATOS: an integrative data resource of proteins and post-translational modifications in the regulation of autophagy. Autophagy. 14(2). 296–310. 33 indexed citations
14.
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
15.
Chen, Leilei, Yongbo Wang, Ju‐Xian Song, et al.. (2017). Phosphoproteome-based kinase activity profiling reveals the critical role of MAP2K2 and PLK1 in neuronal autophagy. Autophagy. 13(11). 1969–1980. 52 indexed citations
16.
Ullah, Shahid, Shaofeng Lin, Yang Xu, et al.. (2016). dbPAF: an integrative database of protein phosphorylation in animals and fungi. Scientific Reports. 6(1). 23534–23534. 63 indexed citations
17.
Li, Shujing, Ying Zhang, Yongqiang Lv, et al.. (2016). OUP accepted manuscript. Nucleic Acids Research. 45(D1). D397–D403. 39 indexed citations
18.
Deng, Wankun, Chenwei Wang, Ying Zhang, et al.. (2016). GPS-PAIL: prediction of lysine acetyltransferase-specific modification sites from protein sequences. Scientific Reports. 6(1). 39787–39787. 95 indexed citations
19.
Deng, Wankun, Yongbo Wang, Zexian Liu, Han Cheng, & Yu Xue. (2014). HemI: A Toolkit for Illustrating Heatmaps. PLoS ONE. 9(11). e111988–e111988. 863 indexed citations breakdown →
20.
Yao, Yuangen, Lili Ma, Qiong Jia, et al.. (2014). Systematic characterization of small RNAome during zebrafish early developmental stages. BMC Genomics. 15(1). 117–117. 22 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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