Mushan Li

813 total citations
10 papers, 446 citations indexed

About

Mushan Li is a scholar working on Molecular Biology, Surgery and Spectroscopy. According to data from OpenAlex, Mushan Li has authored 10 papers receiving a total of 446 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Surgery and 2 papers in Spectroscopy. Recurrent topics in Mushan Li's work include CRISPR and Genetic Engineering (3 papers), Genomics and Chromatin Dynamics (3 papers) and Pluripotent Stem Cells Research (2 papers). Mushan Li is often cited by papers focused on CRISPR and Genetic Engineering (3 papers), Genomics and Chromatin Dynamics (3 papers) and Pluripotent Stem Cells Research (2 papers). Mushan Li collaborates with scholars based in United States, China and India. Mushan Li's co-authors include Zhen Shao, Jian Xu, Yuannyu Zhang, Xin Liu, Feng Zhou, Zhimin Gu, Kathryn E. Dickerson, Hui Cao, Min Ni and Michael Q. Zhang and has published in prestigious journals such as Cell, Nature Cell Biology and Genome Research.

In The Last Decade

Mushan Li

10 papers receiving 443 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mushan Li United States	7	363	52	49	46	32	10	446
Yelena Chernyavskaya United States	9	403 1.1×	29 0.6×	119 2.4×	22 0.5×	50 1.6×	12	510
Xiufei Chen China	7	433 1.2×	61 1.2×	124 2.5×	13 0.3×	14 0.4×	8	607
Lara Zorro Shahidian France	7	404 1.1×	33 0.6×	45 0.9×	29 0.6×	9 0.3×	8	478
Nicolas Stankovic‐Valentin Germany	13	617 1.7×	26 0.5×	83 1.7×	15 0.3×	39 1.2×	15	720
Zhenhua Sui China	11	180 0.5×	38 0.7×	22 0.4×	95 2.1×	87 2.7×	16	316
Shruti Sinha India	11	124 0.3×	28 0.5×	57 1.2×	24 0.5×	25 0.8×	26	264
Ulrike Hebling Germany	10	176 0.5×	31 0.6×	36 0.7×	14 0.3×	23 0.7×	14	392
Tejaswini Mishra United States	10	413 1.1×	85 1.6×	154 3.1×	12 0.3×	18 0.6×	16	548
Prabakaran Nagarajan United States	10	287 0.8×	18 0.3×	26 0.5×	17 0.4×	25 0.8×	14	355

Countries citing papers authored by Mushan Li

Since Specialization

Citations

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

Fields of papers citing papers by Mushan Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mushan Li

This figure shows the co-authorship network connecting the top 25 collaborators of Mushan Li. A scholar is included among the top collaborators of Mushan 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 Mushan Li. Mushan Li is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

Huang, Jing, Li Ruan, Xuan Guo, et al.. (2024). zMAP toolset: model-based analysis of large-scale proteomic data via a variance stabilizing z-transformation. Genome biology. 25(1). 267–267. 2 indexed citations

Liu, Gang, Yana Li, Mushan Li, et al.. (2023). Charting a high-resolution roadmap for regeneration of pancreatic β cells by in vivo transdifferentiation from adult acinar cells. Science Advances. 9(21). eadg2183–eadg2183. 6 indexed citations

Li, Mushan & Yanyuan Ma. (2023). An Update on Measurement Error Modeling. Annual Review of Statistics and Its Application. 11(1). 279–296. 1 indexed citations

Liu, Gang, Yana Li, Tengjiao Zhang, et al.. (2021). Single-Cell RNA Sequencing Reveals Sexually Dimorphic Transcriptome and Type 2 Diabetes Genes in Mouse Islet β Cells. Genomics Proteomics & Bioinformatics. 19(3). 408–422. 18 indexed citations

Li, Mushan, Haojie Chen, Jian Xu, et al.. (2020). MAnorm2 for quantitatively comparing groups of ChIP-seq samples. Genome Research. 31(1). 131–145. 37 indexed citations

Li, Mushan, Jian Liu, Qian Wang, et al.. (2019). MAP: model-based analysis of proteomic data to detect proteins with significant abundance changes. Cell Discovery. 5(1). 40–40. 14 indexed citations

Li, Shuang, Mushan Li, Xiaojian Liu, et al.. (2018). Genetic and Chemical Screenings Identify HDAC3 as a Key Regulator in Hepatic Differentiation of Human Pluripotent Stem Cells. Stem Cell Reports. 11(1). 22–31. 24 indexed citations

Liu, Xin, Yuannyu Zhang, Yong Chen, et al.. (2018). CAPTURE: In Situ Analysis of Chromatin Composition of Endogenous Genomic Loci by Biotinylated dCas9. Current Protocols in Molecular Biology. 123(1). e64–e64. 15 indexed citations

Liu, Xin, Yuannyu Zhang, Yong Chen, et al.. (2017). In Situ Capture of Chromatin Interactions by Biotinylated dCas9. Cell. 170(5). 1028–1043.e19. 208 indexed citations

10.

Liu, Xin, Yuannyu Zhang, Min Ni, et al.. (2017). Regulation of mitochondrial biogenesis in erythropoiesis by mTORC1-mediated protein translation. Nature Cell Biology. 19(6). 626–638. 121 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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