Shikai Jin

798 total citations
32 papers, 538 citations indexed

About

Shikai Jin is a scholar working on Molecular Biology, Materials Chemistry and Oncology. According to data from OpenAlex, Shikai Jin has authored 32 papers receiving a total of 538 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 9 papers in Materials Chemistry and 3 papers in Oncology. Recurrent topics in Shikai Jin's work include Protein Structure and Dynamics (9 papers), Enzyme Structure and Function (9 papers) and RNA and protein synthesis mechanisms (5 papers). Shikai Jin is often cited by papers focused on Protein Structure and Dynamics (9 papers), Enzyme Structure and Function (9 papers) and RNA and protein synthesis mechanisms (5 papers). Shikai Jin collaborates with scholars based in China, United States and Taiwan. Shikai Jin's co-authors include Wan‐Xi Yang, Peter G. Wolynes, Mingchen Chen, Wei Lu, Nicholas P. Schafer, Xiaojing Wang, Lihua Jin, Qilan Li, Yong Li and Anpei Hu and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Shikai Jin

28 papers receiving 529 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shikai Jin China 14 331 77 77 65 62 32 538
Jinyu Zhu China 11 272 0.8× 34 0.4× 100 1.3× 31 0.5× 38 0.6× 25 537
Teresa Banaś Poland 15 280 0.8× 43 0.6× 97 1.3× 94 1.4× 47 0.8× 35 701
Xinjun Wang China 19 486 1.5× 80 1.0× 163 2.1× 19 0.3× 41 0.7× 57 879
Mark R. Condina Australia 16 383 1.2× 67 0.9× 30 0.4× 9 0.1× 48 0.8× 33 663
Shigeru Hisada Japan 9 104 0.3× 32 0.4× 75 1.0× 21 0.3× 36 0.6× 17 373
Aliakbar Taherian Iran 11 184 0.6× 49 0.6× 25 0.3× 15 0.2× 53 0.9× 21 436
Tae‐Heon Kim South Korea 18 397 1.2× 41 0.5× 240 3.1× 16 0.2× 13 0.2× 51 853
Qing Cheng China 18 396 1.2× 10 0.1× 46 0.6× 24 0.4× 83 1.3× 52 753
Qi Gao China 17 412 1.2× 25 0.3× 129 1.7× 23 0.4× 13 0.2× 54 846

Countries citing papers authored by Shikai Jin

Since Specialization
Citations

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

Fields of papers citing papers by Shikai Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shikai Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Shikai Jin. A scholar is included among the top collaborators of Shikai Jin 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 Shikai Jin. Shikai Jin 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.
Jin, Shikai, et al.. (2025). DNA polymerase actively and sequentially displaces single-stranded DNA-binding proteins. Nature Communications. 16(1). 7431–7431.
2.
Jin, Shikai, Mengxi Zhang, Yuda Chen, et al.. (2025). Real-time imaging of protein microenvironment changes in cells with rotor-based fluorescent amino acids. Nature Chemical Biology. 22(1). 97–108.
3.
Dun, Chen, et al.. (2024). CrysFormer: Protein structure determination via Patterson maps, deep learning, and partial structure attention. Structural Dynamics. 11(4). 44701–44701. 5 indexed citations
4.
Jin, Shikai, Minghui Zhang, H. J. Yang, et al.. (2023). Precise diagnosis and targeted therapy of nodal T-follicular helper cell lymphoma (T-FHCL). Frontiers in Oncology. 13. 1163190–1163190. 2 indexed citations
5.
Jin, Shikai, et al.. (2023). A deep learning solution for crystallographic structure determination. IUCrJ. 10(4). 487–496. 12 indexed citations
6.
Jin, Shikai, et al.. (2023). Update on histone deacetylase inhibitors in peripheral T-cell lymphoma (PTCL). Clinical Epigenetics. 15(1). 124–124. 18 indexed citations
7.
Song, Huajie, Jianqun Wang, Xiaojing Wang, et al.. (2022). HNF4A-AS1-encoded small peptide promotes self-renewal and aggressiveness of neuroblastoma stem cells via eEF1A1-repressed SMAD4 transactivation. Oncogene. 41(17). 2505–2519. 19 indexed citations
8.
Chen, Yuda, Shikai Jin, Mengxi Zhang, et al.. (2022). Unleashing the potential of noncanonical amino acid biosynthesis to create cells with precision tyrosine sulfation. Nature Communications. 13(1). 5434–5434. 45 indexed citations
9.
Jin, Shikai, Wei Lu, Qian Wang, et al.. (2022). Computationally exploring the mechanism of bacteriophage T7 gp4 helicase translocating along ssDNA. Proceedings of the National Academy of Sciences. 119(32). e2202239119–e2202239119. 11 indexed citations
10.
Chen, Xun, Wei Lu, Min‐Yeh Tsai, Shikai Jin, & Peter G. Wolynes. (2022). Exploring the folding energy landscapes of heme proteins using a hybrid AWSEM-heme model. Journal of Biological Physics. 48(1). 37–53. 4 indexed citations
11.
Lu, Wei, Nicholas P. Schafer, Joshua Moller, et al.. (2021). OpenAWSEM with Open3SPN2: A fast, flexible, and accessible framework for large-scale coarse-grained biomolecular simulations. PLoS Computational Biology. 17(2). e1008308–e1008308. 35 indexed citations
12.
Wang, Jianqun, Xiaojing Wang, Yanhua Guo, et al.. (2021). Therapeutic targeting of SPIB/SPI1‐facilitated interplay of cancer cells and neutrophils inhibits aerobic glycolysis and cancer progression. SHILAP Revista de lepidopterología. 11(11). e588–e588. 38 indexed citations
13.
Feng, Yang, Anpei Hu, Yanhua Guo, et al.. (2021). p113 isoform encoded by CUX1 circular RNA drives tumor progression via facilitating ZRF1/BRD4 transactivation. Molecular Cancer. 20(1). 123–123. 51 indexed citations
14.
Jin, Shikai, Mitchell D. Miller, Mingchen Chen, et al.. (2020). Molecular-replacement phasing using predicted protein structures from AWSEM-Suite. IUCrJ. 7(6). 1168–1178. 9 indexed citations
15.
Jin, Shikai, Mingchen Chen, Xun Chen, et al.. (2020). Protein Structure Prediction in CASP13 Using AWSEM-Suite. Journal of Chemical Theory and Computation. 16(6). 3977–3988. 13 indexed citations
16.
Zheng, Weili, Rui Wang, Xi Liu, et al.. (2017). Structural insights into the nuclear import of the histone acetyltransferase males‐absent‐on‐the‐first by importin α1. Traffic. 19(1). 19–28. 7 indexed citations
17.
Zheng, Weili, Yi Lu, Shengchen Lin, et al.. (2017). A Novel Class of Natural FXR Modulators with a Unique Mode of Selective Co‐regulator Assembly. ChemBioChem. 18(8). 721–725. 24 indexed citations
18.
Lu, Yi, Weili Zheng, Shengchen Lin, et al.. (2017). Identification of an Oleanane-Type Triterpene Hedragonic Acid as a Novel Farnesoid X Receptor Ligand with Liver Protective Effects and Anti-inflammatory Activity. Molecular Pharmacology. 93(2). 63–72. 32 indexed citations
19.
Li, Hong, Nan Bao, Yaonan Zhang, et al.. (2016). A renal vascular compartment segmentation method based on dynamic contrast-enhanced images. Technology and Health Care. 24(s2). S631–S639. 4 indexed citations
20.
Wang, Shanshan, Zhao Wang, Shengchen Lin, et al.. (2012). Revealing a natural marine product as a novel agonist for retinoic acid receptors with a unique binding mode and inhibitory effects on cancer cells. Biochemical Journal. 446(1). 79–87. 20 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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