Hanshuang Li

569 total citations
25 papers, 320 citations indexed

About

Hanshuang Li is a scholar working on Molecular Biology, Immunology and Oncology. According to data from OpenAlex, Hanshuang Li has authored 25 papers receiving a total of 320 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 3 papers in Immunology and 2 papers in Oncology. Recurrent topics in Hanshuang Li's work include Pluripotent Stem Cells Research (10 papers), CRISPR and Genetic Engineering (10 papers) and Single-cell and spatial transcriptomics (7 papers). Hanshuang Li is often cited by papers focused on Pluripotent Stem Cells Research (10 papers), CRISPR and Genetic Engineering (10 papers) and Single-cell and spatial transcriptomics (7 papers). Hanshuang Li collaborates with scholars based in China, Japan and United States. Hanshuang Li's co-authors include Yongchun Zuo, Chunshen Long, Pengfei Liang, Shuai Liu, Hao Wang, Wuritu Yang, Lei Yang, Na Ta, Hong Yan and Haicheng Li and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and International Journal of Molecular Sciences.

In The Last Decade

Hanshuang Li

25 papers receiving 318 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hanshuang Li China 11 223 41 39 19 19 25 320
Chuanchao Zhang China 10 205 0.9× 36 0.9× 59 1.5× 22 1.2× 18 0.9× 39 319
Chunshen Long China 11 246 1.1× 15 0.4× 48 1.2× 38 2.0× 21 1.1× 22 309
Rezvan Ehsani Norway 6 201 0.9× 26 0.6× 66 1.7× 9 0.5× 25 1.3× 11 296
Parisa Shooshtari Canada 9 156 0.7× 22 0.5× 26 0.7× 9 0.5× 17 0.9× 20 305
Jian Tajbakhsh United States 11 299 1.3× 15 0.4× 34 0.9× 29 1.5× 38 2.0× 22 424
Alexandra So United States 3 106 0.5× 21 0.5× 41 1.1× 12 0.6× 16 0.8× 3 273
Joanna Chen United States 6 301 1.3× 20 0.5× 21 0.5× 13 0.7× 35 1.8× 13 416
Sylwia Mazurek Poland 8 229 1.0× 31 0.8× 51 1.3× 9 0.5× 22 1.2× 12 356
Xianxu Zeng China 12 81 0.4× 70 1.7× 56 1.4× 13 0.7× 9 0.5× 32 365
Garrett Jenkinson United States 10 180 0.8× 16 0.4× 43 1.1× 16 0.8× 66 3.5× 27 277

Countries citing papers authored by Hanshuang Li

Since Specialization
Citations

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

Fields of papers citing papers by Hanshuang Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hanshuang Li

This figure shows the co-authorship network connecting the top 25 collaborators of Hanshuang Li. A scholar is included among the top collaborators of Hanshuang 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 Hanshuang Li. Hanshuang 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.
Yang, Siqi, et al.. (2025). Deciphering Sequence Determinants of Zygotic Genome Activation Genes: Insights From Machine Learning and the ZGAExplorer Platform. Cell Proliferation. 58(12). e70039–e70039. 1 indexed citations
2.
Li, Hanshuang, et al.. (2025). DualNetM: an adaptive dual network framework for inferring functional-oriented markers. BMC Biology. 23(1). 254–254. 1 indexed citations
3.
Jia, Jianchao, et al.. (2024). Identification of Key lncRNAs Associated with Immune Infiltration and Prognosis in Gastric Cancer. Biochemical Genetics. 63(3). 2061–2079. 2 indexed citations
4.
Liang, Pengfei, Hanshuang Li, Chunshen Long, et al.. (2024). Chromatin region binning of gene expression for improving embryo cell subtype identification. Computers in Biology and Medicine. 170. 108049–108049. 1 indexed citations
5.
Hong, Yan, Hanshuang Li, Chunshen Long, et al.. (2024). An increment of diversity method for cell state trajectory inference of time-series scRNA-seq data. Fundamental Research. 4(4). 770–776. 8 indexed citations
6.
Wang, Hao, Zhao‐Yue Zhang, Haicheng Li, et al.. (2023). A cost-effective machine learning-based method for preeclampsia risk assessment and driver genes discovery. Cell & Bioscience. 13(1). 41–41. 28 indexed citations
7.
Long, Chunshen, Hanshuang Li, Pengfei Liang, et al.. (2023). Deciphering the decisive factors driving fate bifurcations in somatic cell reprogramming. Molecular Therapy — Nucleic Acids. 34. 102044–102044. 4 indexed citations
8.
Li, Hanshuang, Chunshen Long, Hong Yan, Liaofu Luo, & Yongchun Zuo. (2023). Characterizing Cellular Differentiation Potency and Waddington Landscape via Energy Indicator. Research. 6. 118–118. 19 indexed citations
9.
Yang, Siqi, et al.. (2022). Competitive binding of TET1 and DNMT3A/B cooperates the DNA methylation pattern in human embryonic stem cells. Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms. 1865(7). 194861–194861. 7 indexed citations
10.
Wang, Shiyuan, Hanshuang Li, Yingli Lv, et al.. (2022). Deep learning-based transcription factor activity for stratification of breast cancer patients. Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms. 1865(6). 194838–194838. 2 indexed citations
11.
Li, Hanshuang, et al.. (2022). The Cumulative Formation of R-loop Interacts with Histone Modifications to Shape Cell Reprogramming. International Journal of Molecular Sciences. 23(3). 1567–1567. 6 indexed citations
12.
Meng, Chi, Hanshuang Li, Na Wei, et al.. (2022). Characterized the diversity of ABCB1 subtypes in immunogenomic landscape for predicting the drug response in breast cancer. Methods. 204. 223–233. 2 indexed citations
13.
Liang, Pengfei, Chunshen Long, Haicheng Li, et al.. (2022). EmAtlas: a comprehensive atlas for exploring spatiotemporal activation in mammalian embryogenesis. Nucleic Acids Research. 51(D1). D924–D932. 15 indexed citations
14.
Wang, Hao, et al.. (2021). eHSCPr discriminating the cell identity involved in endothelial to hematopoietic transition. Bioinformatics. 37(15). 2157–2164. 31 indexed citations
15.
Li, Hanshuang, et al.. (2020). Characterization of DNA Methylation Patterns and Mining of Epigenetic Markers During Genomic Reprogramming in SCNT Embryos. Frontiers in Cell and Developmental Biology. 8. 570107–570107. 9 indexed citations
16.
Li, Hanshuang, et al.. (2020). A Comparative Analysis of Single-Cell Transcriptome Identifies Reprogramming Driver Factors for Efficiency Improvement. Molecular Therapy — Nucleic Acids. 19. 1053–1064. 16 indexed citations
17.
Liang, Pengfei, Wuritu Yang, Xing Chen, et al.. (2020). Machine Learning of Single-Cell Transcriptome Highly Identifies mRNA Signature by Comparing F-Score Selection with DGE Analysis. Molecular Therapy — Nucleic Acids. 20. 155–163. 30 indexed citations
18.
Zuo, Yongchun, et al.. (2019). Analysis of the Epigenetic Signature of Cell Reprogramming by Computational DNA Methylation Profiles. Current Bioinformatics. 15(6). 589–599. 24 indexed citations
19.
Li, Hanshuang, Na Ta, Chunshen Long, et al.. (2019). The spatial binding model of the pioneer factor Oct4 with its target genes during cell reprogramming. Computational and Structural Biotechnology Journal. 17. 1226–1233. 22 indexed citations
20.
Liu, Shuai, et al.. (2019). Prediction of Gene Expression Patterns With Generalized Linear Regression Model. Frontiers in Genetics. 10. 120–120. 40 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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