Yakun Pang

1.2k total citations
22 papers, 458 citations indexed

About

Yakun Pang is a scholar working on Hematology, Molecular Biology and Immunology. According to data from OpenAlex, Yakun Pang has authored 22 papers receiving a total of 458 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Hematology, 8 papers in Molecular Biology and 5 papers in Immunology. Recurrent topics in Yakun Pang's work include Acute Myeloid Leukemia Research (7 papers), Hematopoietic Stem Cell Transplantation (6 papers) and Cancer Genomics and Diagnostics (5 papers). Yakun Pang is often cited by papers focused on Acute Myeloid Leukemia Research (7 papers), Hematopoietic Stem Cell Transplantation (6 papers) and Cancer Genomics and Diagnostics (5 papers). Yakun Pang collaborates with scholars based in China, United States and Australia. Yakun Pang's co-authors include Tao Cheng, Weiping Yuan, Hui Cheng, Fang Dong, Sha Hao, Shihui Ma, Guoguang Zheng, John Easton, Wenan Chen and Xiang Chen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Genetics.

In The Last Decade

Yakun Pang

21 papers receiving 456 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Yakun Pang China 11 253 173 108 90 50 22 458
Andrew Volk United States 11 387 1.5× 165 1.0× 114 1.1× 84 0.9× 45 0.9× 25 547
Kadriye Nehir Cosgun United States 6 185 0.7× 157 0.9× 172 1.6× 62 0.7× 54 1.1× 19 413
Glen Raffel United States 11 337 1.3× 162 0.9× 54 0.5× 71 0.8× 66 1.3× 36 505
Vaia Stavropoulou Switzerland 9 269 1.1× 212 1.2× 76 0.7× 57 0.6× 47 0.9× 18 417
Soumen Chakraborty India 13 434 1.7× 197 1.1× 88 0.8× 50 0.6× 60 1.2× 27 635
Annet Z. Brouwers-Vos Netherlands 12 328 1.3× 235 1.4× 73 0.7× 101 1.1× 52 1.0× 17 485
Rika Kanezaki Japan 11 198 0.8× 163 0.9× 68 0.6× 40 0.4× 78 1.6× 19 387
Carl Sandén Sweden 11 198 0.8× 187 1.1× 137 1.3× 54 0.6× 53 1.1× 18 426
Liliana H. Mochmann Germany 10 278 1.1× 155 0.9× 51 0.5× 50 0.6× 61 1.2× 14 436
Subrata Banerjee India 13 269 1.1× 92 0.5× 121 1.1× 102 1.1× 38 0.8× 31 538

Countries citing papers authored by Yakun Pang

Since Specialization
Citations

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

Fields of papers citing papers by Yakun Pang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yakun Pang

This figure shows the co-authorship network connecting the top 25 collaborators of Yakun Pang. A scholar is included among the top collaborators of Yakun Pang 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 Yakun Pang. Yakun Pang 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
2.
Schiffman, Joshua S., Yakun Pang, Yilin Fan, et al.. (2024). Defining heritability, plasticity, and transition dynamics of cellular phenotypes in somatic evolution. Nature Genetics. 56(10). 2174–2184. 8 indexed citations
3.
Mumme, Hope, Sunil S. Raikar, Swati S. Bhasin, et al.. (2023). Single-cell RNA sequencing distinctly characterizes the wide heterogeneity in pediatric mixed phenotype acute leukemia. Genome Medicine. 15(1). 83–83. 8 indexed citations
4.
Barsan, Valentin, Yuntao Xia, Veronica Gonzalez-Pena, et al.. (2022). Simultaneous monitoring of disease and microbe dynamics through plasma DNA sequencing in pediatric patients with acute lymphoblastic leukemia. Science Advances. 8(16). eabj1360–eabj1360. 2 indexed citations
5.
Gonzalez-Pena, Veronica, Sivaraman Natarajan, Yuntao Xia, et al.. (2021). Accurate genomic variant detection in single cells with primary template-directed amplification. Proceedings of the National Academy of Sciences. 118(24). 87 indexed citations
6.
Qin, Pengfei, Yakun Pang, Wenhong Hou, et al.. (2021). Integrated decoding hematopoiesis and leukemogenesis using single-cell sequencing and its medical implication. Cell Discovery. 7(1). 2–2. 27 indexed citations
7.
Cheng, Changde, John Easton, Celeste Rosencrance, et al.. (2019). Latent cellular analysis robustly reveals subtle diversity in large-scale single-cell RNA-seq data. Nucleic Acids Research. 47(22). e143–e143. 24 indexed citations
8.
Liam, Chong Kin, et al.. (2019). Clinical phenotypes of COPD and health-related quality of life: a cross-sectional study. SHILAP Revista de lepidopterología. 3 indexed citations
9.
Wang, Xiaomin, Yanan Gao, Juan Gao, et al.. (2018). Rheb1 loss leads to increased hematopoietic stem cell proliferation and myeloid-biased differentiation in vivo. Haematologica. 104(2). 245–255. 15 indexed citations
10.
Wang, Yu-Chun, Xianlong Li, Ping Lu, et al.. (2016). Loss of Dnmt3b accelerates MLL-AF9 leukemia progression. Leukemia. 30(12). 2373–2384. 31 indexed citations
11.
Pang, Yakun, S. Ma, Sha Hao, et al.. (2015). Altered mesenchymal niche cells impede generation of normal hematopoietic progenitor cells in leukemic bone marrow. Leukemia. 30(1). 154–162. 37 indexed citations
12.
Hu, Xiaoxia, Libing Wang, Hui Cheng, et al.. (2015). Excessive proliferation and impaired function of primitive hematopoietic cells in bone marrow due to senescence post chemotherapy in a T cell acute lymphoblastic leukemia model. Journal of Translational Medicine. 13(1). 234–234. 11 indexed citations
13.
Cheng, Hui, Sha Hao, Yanfeng Liu, et al.. (2015). Leukemic marrow infiltration reveals a novel role for Egr3 as a potent inhibitor of normal hematopoietic stem cell proliferation. Blood. 126(11). 1302–1313. 81 indexed citations
14.
Zhao, Yunze, Jie Zhou, Fang Dong, et al.. (2015). ATF4 plays a pivotal role in the development of functional hematopoietic stem cells in mouse fetal liver. Blood. 126(21). 2383–2391. 62 indexed citations
15.
Ma, Shihui, Yingxu Shi, Yakun Pang, et al.. (2014). Notch1-induced T cell leukemia can be potentiated by microenvironmental cues in the spleen. Journal of Hematology & Oncology. 7(1). 71–71. 35 indexed citations
16.
Yang, Xin, Yu Zhang, Yakun Pang, et al.. (2014). [Expression of CD48 as a live marker to distinguish division of hematopoietic stem cells].. PubMed. 22(3). 573–9. 1 indexed citations
17.
Pang, Yakun. (2014). Close contact investigation of TB in high-burden, low- and middle-income countries.. PubMed. 9(2). 11–7. 2 indexed citations
18.
Lin, Yan, Xiaoxia Hu, Hui Cheng, et al.. (2014). Graft-versus-Host Disease Causes Broad Suppression of Hematopoietic Primitive Cells and Blocks Megakaryocyte Differentiation in a Murine Model. Biology of Blood and Marrow Transplantation. 20(9). 1290–1300. 14 indexed citations
19.
Zhang, Yan, Fang Dong, Na Zhang, et al.. (2013). Suppression of Cytochrome P450 Reductase Enhances Long-Term Hematopoietic Stem Cell Repopulation Efficiency in Mice. PLoS ONE. 8(7). e69913–e69913. 7 indexed citations
20.
Wang, Xiaojuan, Yakun Pang, Hui Cheng, et al.. (2013). [Knockdown of Larp4b in Lin(-) cells does not affect the colony forming ability of mouse hematopoietic cells].. PubMed. 21(3). 735–40. 1 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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