Shang Li

4.4k total citations · 1 hit paper
52 papers, 2.8k citations indexed

About

Shang Li is a scholar working on Molecular Biology, Physiology and Genetics. According to data from OpenAlex, Shang Li has authored 52 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Molecular Biology, 15 papers in Physiology and 10 papers in Genetics. Recurrent topics in Shang Li's work include Telomeres, Telomerase, and Senescence (12 papers), DNA Repair Mechanisms (8 papers) and CRISPR and Genetic Engineering (7 papers). Shang Li is often cited by papers focused on Telomeres, Telomerase, and Senescence (12 papers), DNA Repair Mechanisms (8 papers) and CRISPR and Genetic Engineering (7 papers). Shang Li collaborates with scholars based in Singapore, United States and China. Shang Li's co-authors include Wen‐Hwa Lee, Phang‐Lang Chen, Lei Zheng, Z. Dave Sharp, Chi‐Fen Chen, Yumay Chen, Thomas G. Boyer, Jun Xiao, Qing Zhong and Muhammad Khairul Ramlee and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Shang Li

49 papers receiving 2.7k citations

Hit Papers

Association of BRCA1 with... 1999 2026 2008 2017 1999 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shang Li Singapore 21 2.1k 655 612 542 415 52 2.8k
Lily I. Huschtscha Australia 20 2.1k 1.0× 458 0.7× 1.0k 1.7× 1.1k 2.0× 595 1.4× 26 3.0k
Andrzej K. Bednarek Poland 28 1.9k 0.9× 1.2k 1.9× 239 0.4× 619 1.1× 481 1.2× 103 3.1k
Mario Cioce Italy 21 2.6k 1.2× 315 0.5× 301 0.5× 706 1.3× 426 1.0× 34 3.3k
Purificacı́on Muñoz Spain 29 2.5k 1.2× 263 0.4× 1.2k 2.0× 1.1k 2.1× 755 1.8× 35 3.8k
Darjus F. Tschaharganeh Germany 22 2.3k 1.1× 320 0.5× 397 0.6× 1.1k 2.0× 583 1.4× 34 3.5k
Yie Liu United States 31 1.8k 0.8× 201 0.3× 919 1.5× 441 0.8× 218 0.5× 62 2.5k
Beth B. McConnell United States 21 2.3k 1.1× 649 1.0× 270 0.4× 459 0.8× 390 0.9× 26 2.7k
Sohee Jun United States 21 1.4k 0.7× 152 0.2× 592 1.0× 412 0.8× 322 0.8× 28 2.0k
Greg Hannon United States 14 1.9k 0.9× 154 0.2× 500 0.8× 1.1k 2.0× 515 1.2× 21 2.6k
Girdhar G. Sharma United States 23 2.4k 1.1× 217 0.3× 324 0.5× 655 1.2× 374 0.9× 27 2.7k

Countries citing papers authored by Shang Li

Since Specialization
Citations

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

Fields of papers citing papers by Shang Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shang Li

This figure shows the co-authorship network connecting the top 25 collaborators of Shang Li. A scholar is included among the top collaborators of Shang 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 Shang Li. Shang 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, Shang, et al.. (2025). Spatial transcriptomics-aided localization for single-cell transcriptomics with STALocator. Cell Systems. 16(2). 101195–101195. 3 indexed citations
2.
3.
Novera, Wisna, See Wee Lim, Yuk Kien Chong, et al.. (2024). EZH2 functional dichotomy in reactive oxygen species-stratified glioblastoma. Neuro-Oncology. 27(2). 398–414. 2 indexed citations
4.
Tan, Kar Wai, Xiubo Fan, Zhiyong Poon, et al.. (2023). Cord blood–derived V δ 2 + and V δ 2 T cells acquire differential cell state compositions upon in vitro expansion. Science Advances. 9(24). eadf3120–eadf3120. 7 indexed citations
5.
Yao, Bing, Shang Li, Jingwan Zhou, et al.. (2023). EBF2 Links KMT2D‐Mediated H3K4me1 to Suppress Pancreatic Cancer Progression via Upregulating KLLN. Advanced Science. 11(2). e2302037–e2302037. 8 indexed citations
6.
Tham, Cheng Yong, Lai-Fong Poon, Tingdong Yan, et al.. (2023). High-throughput telomere length measurement at nucleotide resolution using the PacBio high fidelity sequencing platform. Nature Communications. 14(1). 281–281. 27 indexed citations
7.
Fan, Xiubo, Chin Teck Ng, Jia Tan, et al.. (2022). Dampened Inflammation and Improved Survival After CXCL5 Administration in Murine Lupus via Myeloid and Neutrophil Pathways. Arthritis & Rheumatology. 75(4). 553–566. 12 indexed citations
8.
Li, Shang, et al.. (2022). Clinical Effectiveness of Platelet-Rich Plasma for Long-Bone Delayed Union and Nonunion: A Systematic Review and Meta-Analysis. Frontiers in Medicine. 8. 771252–771252. 19 indexed citations
9.
Cai, Yichao, Ying Zhang, Yan Ping Loh, et al.. (2021). H3K27me3-rich genomic regions can function as silencers to repress gene expression via chromatin interactions. Nature Communications. 12(1). 719–719. 172 indexed citations
10.
Ross, Cecil, et al.. (2017). MiRNA182 regulates percentage of myeloid and erythroid cells in chronic myeloid leukemia. Cell Death and Disease. 8(1). e2547–e2547. 16 indexed citations
11.
Zhang, Qian, Leiping Zeng, Peng Zhou, et al.. (2017). IFNAR2-dependent gene expression profile induced by IFN-α in Pteropus alecto bat cells and impact of IFNAR2 knockout on virus infection. PLoS ONE. 12(8). e0182866–e0182866. 24 indexed citations
12.
Yan, Yaw Kai, et al.. (2016). Downregulation of oncogenic RAS and c-Myc expression in MOLT-4 leukaemia cells by a salicylaldehyde semicarbazone copper(II) complex. Scientific Reports. 6(1). 36868–36868. 13 indexed citations
13.
Ramlee, Muhammad Khairul, Tingdong Yan, Alice M.S. Cheung, Charles Chuah, & Shang Li. (2015). High-throughput genotyping of CRISPR/Cas9-mediated mutants using fluorescent PCR-capillary gel electrophoresis. Scientific Reports. 5(1). 15587–15587. 70 indexed citations
14.
Wu, Bingli, Chunquan Li, Zepeng Du, et al.. (2014). Network based analyses of gene expression profile of LCN2 overexpression in esophageal squamous cell carcinoma. Scientific Reports. 4(1). 5403–5403. 29 indexed citations
15.
Gopalakrishnan, Veena, et al.. (2013). Cdk1 Regulates the Temporal Recruitment of Telomerase and Cdc13-Stn1-Ten1 Complex for Telomere Replication. Molecular and Cellular Biology. 34(1). 57–70. 27 indexed citations
16.
Ghosh, Arkasubhra, Gaye Saginc, Shi Chi Leow, et al.. (2012). Telomerase directly regulates NF-κB-dependent transcription. Nature Cell Biology. 14(12). 1270–1281. 303 indexed citations
17.
Li, Shang, Mehdi Nosrati, & Mohammed Kashani–Sabet. (2007). Knockdown of Telomerase RNA Using Hammerhead Ribozymes and RNA Interference. Methods in molecular biology. 405. 113–131. 17 indexed citations
18.
Zheng, Lei, Hongyi Pan, Shang Li, et al.. (2000). Sequence-Specific Transcriptional Corepressor Function for BRCA1 through a Novel Zinc Finger Protein, ZBRK1. Molecular Cell. 6(4). 757–768. 203 indexed citations
19.
Li, Shang, Nicholas S. Y. Ting, Lei Zheng, et al.. (2000). Functional link of BRCA1 and ataxia telangiectasia gene product in DNA damage response. Nature. 406(6792). 210–215. 261 indexed citations
20.
Chen, Chi‐Fen, Shang Li, Yumay Chen, et al.. (1996). The Nuclear Localization Sequences of the BRCA1 Protein Interact with the Importin-α Subunit of the Nuclear Transport Signal Receptor. Journal of Biological Chemistry. 271(51). 32863–32868. 165 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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