Tiejun Li

2.4k total citations
85 papers, 1.4k citations indexed

About

Tiejun Li is a scholar working on Molecular Biology, Statistical and Nonlinear Physics and Genetics. According to data from OpenAlex, Tiejun Li has authored 85 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 20 papers in Statistical and Nonlinear Physics and 8 papers in Genetics. Recurrent topics in Tiejun Li's work include Gene Regulatory Network Analysis (21 papers), stochastic dynamics and bifurcation (10 papers) and Single-cell and spatial transcriptomics (9 papers). Tiejun Li is often cited by papers focused on Gene Regulatory Network Analysis (21 papers), stochastic dynamics and bifurcation (10 papers) and Single-cell and spatial transcriptomics (9 papers). Tiejun Li collaborates with scholars based in China, United States and Japan. Tiejun Li's co-authors include E Weinan, Pingwen Zhang, Xiaoguang Li, Luonan Chen, Peijie Zhou, Fangting Li, Eric Vanden‐Eijnden, Peng Sun, Wei Zhang and Qing Nie and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and The Journal of Chemical Physics.

In The Last Decade

Tiejun Li

78 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tiejun Li China 21 615 233 127 97 94 85 1.4k
Giovanni Russo Italy 31 1.4k 2.3× 238 1.0× 108 0.9× 37 0.4× 104 1.1× 180 3.6k
Martin Held Switzerland 27 2.2k 3.6× 104 0.4× 80 0.6× 10 0.1× 142 1.5× 63 3.5k
Yufeng Liu China 31 1.3k 2.1× 24 0.1× 30 0.2× 92 0.9× 39 0.4× 119 2.6k
Robert A. Singer United States 31 669 1.1× 64 0.3× 52 0.4× 57 0.6× 65 0.7× 87 5.3k
Junwei Wang China 32 1.4k 2.2× 598 2.6× 27 0.2× 13 0.1× 92 1.0× 227 3.6k
Ralf Steuer Germany 32 2.7k 4.4× 179 0.8× 26 0.2× 20 0.2× 122 1.3× 65 3.6k
Marcus Weber Germany 23 1.9k 3.1× 229 1.0× 16 0.1× 18 0.2× 218 2.3× 119 3.2k
Can Chen China 21 769 1.3× 189 0.8× 89 0.7× 6 0.1× 27 0.3× 115 1.4k
Masayuki Sato Japan 30 784 1.3× 29 0.1× 315 2.5× 223 2.3× 20 0.2× 293 3.9k
Philipp Thomas United Kingdom 27 895 1.5× 115 0.5× 13 0.1× 53 0.5× 35 0.4× 76 1.8k

Countries citing papers authored by Tiejun Li

Since Specialization
Citations

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

Fields of papers citing papers by Tiejun Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tiejun Li

This figure shows the co-authorship network connecting the top 25 collaborators of Tiejun Li. A scholar is included among the top collaborators of Tiejun Li 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 Tiejun Li. Tiejun Li 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.
Li, Tiejun, et al.. (2026). Quasi‐Dual‐Channel Oxide Transistors With Enhanced Stability and Performance. Small. 22(18). e12277–e12277.
2.
3.
Li, Ningli, Miaomiao Feng, Yingying Li, et al.. (2025). Locally Delivered Hydrogel with Sustained Release of Flavonol Compound Kaempferol Mitigates Inflammatory Progression of Periodontitis and Enhances the Gut Microflora Composition in Rats. ACS Biomaterials Science & Engineering. 11(3). 1646–1659. 2 indexed citations
4.
Li, Tiejun, et al.. (2024). FECSG-ML: Feature Engineering for Nuclear Reaction Cross Sections Generation Using Machine Learning. Applied Radiation and Isotopes. 214. 111545–111545. 4 indexed citations
5.
Liu, Yangzhi, et al.. (2024). Insights into the characteristics and toxicity of microalgal biochar–derived dissolved organic matter by spectroscopy and machine learning. The Science of The Total Environment. 957. 177648–177648. 3 indexed citations
6.
Qiu, Xiaojie, et al.. (2024). Storm: Incorporating transient stochastic dynamics to infer the RNA velocity with metabolic labeling information. PLoS Computational Biology. 20(11). e1012606–e1012606.
7.
Zhang, Wei, et al.. (2024). EPR-Net: constructing a non-equilibrium potential landscape via a variational force projection formulation. National Science Review. 11(7). nwae052–nwae052. 7 indexed citations
8.
Zhou, Peijie, Federico Bocci, Tiejun Li, & Qing Nie. (2024). Spatial transition tensor of single cells. Nature Methods. 21(6). 1053–1062. 13 indexed citations
9.
Li, Tiejun, et al.. (2024). On the Mathematics of RNA Velocity II: Algorithmic Aspects. 5(1). 182–220. 2 indexed citations
10.
Chen, Xinhai, et al.. (2023). Developing an advanced neural network and physics solver coupled framework for accelerating flow field simulations. Engineering With Computers. 40(2). 1111–1126. 6 indexed citations
11.
12.
Dong, Ji, Peijie Zhou, Yidong Chen, et al.. (2021). Integrating single-cell datasets with ambiguous batch information by incorporating molecular network features. Briefings in Bioinformatics. 23(1). 6 indexed citations
13.
Zhou, Peijie, Shuxiong Wang, Tiejun Li, & Qing Nie. (2021). Dissecting transition cells from single-cell transcriptome data through multiscale stochastic dynamics. Nature Communications. 12(1). 5609–5609. 58 indexed citations
14.
Guo, Yuanming, et al.. (2021). Spectroscopic characterization of dissolved organic matter from macroalgae Ulva pertusa decomposition and its binding behaviors with Cu(II). Ecotoxicology and Environmental Safety. 225. 112811–112811. 10 indexed citations
15.
Li, Tiejun, et al.. (2019). Quantifying pluripotency landscape of cell differentiation from scRNA-seq data by continuous birth-death process. PLoS Computational Biology. 15(11). e1007488–e1007488. 17 indexed citations
16.
Chen, Xianli, Xiaoguang Li, Wei Zhao, Tiejun Li, & Qi Ouyang. (2018). Parameter sensitivity analysis for a stochastic model of mitochondrial apoptosis pathway. PLoS ONE. 13(6). e0198579–e0198579. 3 indexed citations
17.
Wu, Guozhen, Li Zhu, Xing Yuan, et al.. (2017). Britanin Ameliorates Cerebral Ischemia–Reperfusion Injury by Inducing the Nrf2 Protective Pathway. Antioxidants and Redox Signaling. 27(11). 754–768. 77 indexed citations
18.
Zhang, Ran, Guan Yang, Ximei Wu, et al.. (2013). Disruption of Wnt/β-catenin Signaling in Odontoblasts and Cementoblasts Arrests Tooth Root Development in Postnatal Mouse Teeth. International Journal of Biological Sciences. 9(3). 228–236. 85 indexed citations
19.
Wang, Pan, Hua Tang, Baoshu Liu, et al.. (2013). Tumor cell growth inhibitory activity and structure–activity relationship of polyoxygenated steroids from the gorgonian Menella kanisa. Steroids. 78(9). 951–958. 20 indexed citations
20.
Li, Tiejun, Assyr Abdulle, & E Weinan. (2008). Effectiveness of implicit methods for stiff stochastic differential equations. Communications in Computational Physics. 3(2). 295–307. 34 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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