Xiaojun Ding

4.8k total citations · 1 hit paper
59 papers, 3.7k citations indexed

About

Xiaojun Ding is a scholar working on Molecular Biology, Genetics and Artificial Intelligence. According to data from OpenAlex, Xiaojun Ding has authored 59 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 10 papers in Genetics and 7 papers in Artificial Intelligence. Recurrent topics in Xiaojun Ding's work include Autophagy in Disease and Therapy (6 papers), Genomics and Chromatin Dynamics (5 papers) and Neural dynamics and brain function (5 papers). Xiaojun Ding is often cited by papers focused on Autophagy in Disease and Therapy (6 papers), Genomics and Chromatin Dynamics (5 papers) and Neural dynamics and brain function (5 papers). Xiaojun Ding collaborates with scholars based in China, United States and Canada. Xiaojun Ding's co-authors include She Chen, Ian G. Ganley, Du Lam, Xuejun Jiang, Junru Wang, Qing Zhong, Weiliang Fan, Qiming Sun, Keling Chen and Feng Shao and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Xiaojun Ding

55 papers receiving 3.7k citations

Hit Papers

ULK1·ATG13·FIP200 Complex Mediates mTOR Signaling and Is ... 2009 2026 2014 2020 2009 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xiaojun Ding China 20 1.9k 1.7k 588 384 310 59 3.7k
Javier E. Irazoqui United States 21 1.7k 0.9× 899 0.5× 651 1.1× 288 0.8× 212 0.7× 34 3.3k
Zhiping Xie China 26 2.1k 1.1× 2.9k 1.7× 1.1k 1.9× 231 0.6× 336 1.1× 75 4.5k
Shunsuke Kimura Japan 30 1.9k 1.0× 1.9k 1.1× 775 1.3× 590 1.5× 372 1.2× 112 4.7k
Peter K. Kim Canada 33 3.2k 1.7× 2.4k 1.4× 1.1k 1.9× 324 0.8× 329 1.1× 70 5.1k
Nathan Brady Germany 32 3.1k 1.6× 3.0k 1.7× 786 1.3× 460 1.2× 431 1.4× 45 5.9k
Jean‐Christophe Rain France 35 4.9k 2.5× 1.1k 0.7× 602 1.0× 492 1.3× 123 0.4× 57 6.5k
Isabelle Beau France 32 1.7k 0.9× 1.4k 0.8× 379 0.6× 310 0.8× 216 0.7× 60 3.9k
William B. Snyder United States 26 2.9k 1.5× 502 0.3× 690 1.2× 365 1.0× 161 0.5× 53 7.6k
Evelina Gatti France 35 2.1k 1.1× 966 0.6× 1.2k 2.1× 1.9k 5.0× 231 0.7× 60 4.8k
Steven Howell United Kingdom 45 4.0k 2.1× 932 0.5× 489 0.8× 1.1k 2.8× 84 0.3× 125 7.0k

Countries citing papers authored by Xiaojun Ding

Since Specialization
Citations

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

Fields of papers citing papers by Xiaojun Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaojun Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaojun Ding. A scholar is included among the top collaborators of Xiaojun Ding 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 Xiaojun Ding. Xiaojun Ding 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.
Ma, Zhigang, Min Fang, Xiaojun Ding, et al.. (2024). Screening of Bovine Coronavirus Multiepitope Vaccine Candidates: An Immunoinformatics Approach. Transboundary and Emerging Diseases. 2024(1). 5986893–5986893. 3 indexed citations
2.
Ding, Xiaojun, et al.. (2023). Research on the Clothing Classification of the She Ethnic Group in Different Regions Based on FPA-CNN. Applied Sciences. 13(17). 9676–9676. 2 indexed citations
3.
Ding, Xiaojun, et al.. (2023). Research on She nationality clothing recognition based on color feature fusion with PSO-SVM. Autex Research Journal. 24(1). 1 indexed citations
4.
Gao, Xiang, Yanchen Xie, Hong-Jun Hao, et al.. (2021). Complement C3 polymorphism is associated with the susceptibility of myasthenia gravis in Chinese adult patients. Journal of Neuroimmunology. 353. 577487–577487. 4 indexed citations
5.
Peng, Xiaoqing, et al.. (2021). Investigating Different DNA Methylation Patterns at the Resolution of Methylation Haplotypes. Frontiers in Genetics. 12. 697279–697279. 5 indexed citations
6.
Yan, Jun, et al.. (2020). obaDIA: one-step biological analysis pipeline for data-independent acquisition and other quantitative proteomics data. Bioinformatics. 37(14). 2066–2067. 3 indexed citations
7.
Zhang, Xuehua, et al.. (2018). Analysis of clinical and electrophysiological characteristics of 150 patients with amyotrophic lateral sclerosis in China. Neurological Sciences. 40(2). 363–369. 13 indexed citations
8.
Hong, Yu, Xu Zhang, Yanchen Xie, et al.. (2016). Gene Polymorphisms for Both Auto-antigen and Immune-Modulating Proteins Are Associated with the Susceptibility of Autoimmune Myasthenia Gravis. Molecular Neurobiology. 54(6). 4771–4780. 16 indexed citations
9.
Xiong, Jun, Zhuqiang Zhang, Jiayu Chen, et al.. (2016). Cooperative Action between SALL4A and TET Proteins in Stepwise Oxidation of 5-Methylcytosine. Molecular Cell. 64(5). 913–925. 97 indexed citations
10.
Mao, Zhuo, Lü Pan, Weixiang Wang, et al.. (2014). Anp32e, a higher eukaryotic histone chaperone directs preferential recognition for H2A.Z. Cell Research. 24(4). 389–399. 104 indexed citations
11.
Yao, Qing, Li Zhang, Xiaobo Wan, et al.. (2014). Structure and Specificity of the Bacterial Cysteine Methyltransferase Effector NleE Suggests a Novel Substrate in Human DNA Repair Pathway. PLoS Pathogens. 10(11). e1004522–e1004522. 24 indexed citations
12.
Ding, Xiaojun. (2013). The core transverse shear line control system transformation based on fuzzy control. Manufacturing Technology & Machine Tool.
13.
Ma, Ben, Yuan Wen, Zhuqiang Zhang, et al.. (2013). Histone H2A Ubiquitination Inhibits the Enzymatic Activity of H3 Lysine 36 Methyltransferases. Journal of Biological Chemistry. 288(43). 30832–30842. 56 indexed citations
14.
Li, Shan, Li Zhang, Qing Yao, et al.. (2013). Pathogen blocks host death receptor signalling by arginine GlcNAcylation of death domains. Nature. 501(7466). 242–246. 215 indexed citations
15.
Ding, Xiaojun. (2012). The Cognitive Verification Studies of the Excellence of Qin. 2 indexed citations
16.
Cui, Jixin, Qing Yao, Shan Li, et al.. (2010). Glutamine Deamidation and Dysfunction of Ubiquitin/NEDD8 Induced by a Bacterial Effector Family. Science. 329(5996). 1215–1218. 160 indexed citations
17.
Fan, Weiliang, Zaiming Tang, Dandan Chen, et al.. (2010). Keap1 facilitates p62-mediated ubiquitin aggregate clearance via autophagy. Autophagy. 6(5). 614–621. 201 indexed citations
18.
Zhu, Weina, Junjun Zhang, Xiaojun Ding, et al.. (2009). Crossmodal effects of Guqin and piano music on selective attention: An event-related potential study. Neuroscience Letters. 466(1). 21–26. 8 indexed citations
19.
Wen, Yuan, Jingwei Xie, Chengzu Long, et al.. (2009). Heterogeneous Nuclear Ribonucleoprotein L Is a Subunit of Human KMT3a/Set2 Complex Required for H3 Lys-36 Trimethylation Activity in Vivo. Journal of Biological Chemistry. 284(23). 15701–15707. 82 indexed citations
20.
Zhu, Weina, Lun Zhao, Junjun Zhang, et al.. (2008). The influence of Mozart's sonata K.448 on visual attention: An ERPs study. Neuroscience Letters. 434(1). 35–40. 14 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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