Gong Yun

2.2k total citations · 1 hit paper
7 papers, 1.7k citations indexed

About

Gong Yun is a scholar working on Immunology, Molecular Biology and Hematology. According to data from OpenAlex, Gong Yun has authored 7 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Immunology, 2 papers in Molecular Biology and 2 papers in Hematology. Recurrent topics in Gong Yun's work include Immune Cell Function and Interaction (6 papers), T-cell and B-cell Immunology (5 papers) and Hematopoietic Stem Cell Transplantation (2 papers). Gong Yun is often cited by papers focused on Immune Cell Function and Interaction (6 papers), T-cell and B-cell Immunology (5 papers) and Hematopoietic Stem Cell Transplantation (2 papers). Gong Yun collaborates with scholars based in United States, France and Russia. Gong Yun's co-authors include Jeffrey S. Miller, Philip B. McGlave, Angela Panoskaltsis‐Mortari, John E. Wagner, Bruce R. Blazar, Chap T. Le, Todd E. DeFor, Paul J. Orchard, Yvette Soignier and Susan K. Fautsch and has published in prestigious journals such as Blood, The Journal of Immunology and Journal of Proteome Research.

In The Last Decade

Gong Yun

7 papers receiving 1.6k citations

Hit Papers

Successful adoptive trans... 2005 2026 2012 2019 2005 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gong Yun United States 6 1.5k 978 516 181 92 7 1.7k
Yvette Soignier United States 3 1.3k 0.9× 930 1.0× 483 0.9× 118 0.7× 87 0.9× 6 1.5k
Ian J. Okazaki United States 15 1.6k 1.1× 1.3k 1.3× 494 1.0× 264 1.5× 111 1.2× 25 2.0k
Susan K. Fautsch United States 8 1.5k 1.0× 1.0k 1.1× 624 1.2× 130 0.7× 100 1.1× 9 1.7k
Michelle Gleason United States 8 1.2k 0.8× 784 0.8× 255 0.5× 154 0.9× 32 0.3× 11 1.3k
Brea A. Jewell United States 6 871 0.6× 541 0.6× 164 0.3× 135 0.7× 47 0.5× 7 991
Sara Abdel-Latif United States 3 821 0.6× 527 0.5× 159 0.3× 102 0.6× 44 0.5× 4 919
Petja Lefterova Germany 11 782 0.5× 638 0.7× 140 0.3× 149 0.8× 104 1.1× 19 949
Hanny Fredrix Netherlands 18 798 0.5× 416 0.4× 290 0.6× 254 1.4× 69 0.8× 24 976
Jooeun Bae United States 17 578 0.4× 453 0.5× 472 0.9× 513 2.8× 25 0.3× 37 1.1k
Teresa Rasalan United States 12 953 0.6× 742 0.8× 72 0.1× 293 1.6× 77 0.8× 17 1.2k

Countries citing papers authored by Gong Yun

Since Specialization
Citations

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

Fields of papers citing papers by Gong Yun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gong Yun

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

All Works

7 of 7 papers shown
1.
Cichocki, Frank, Todd Lenvik, Neeraj Sharma, et al.. (2010). Cutting Edge: KIR Antisense Transcripts Are Processed into a 28-Base PIWI-Like RNA in Human NK Cells. The Journal of Immunology. 185(4). 2009–2012. 53 indexed citations
2.
Godal, Robert, Veronika Bachanová, Michelle Gleason, et al.. (2010). Natural Killer Cell Killing of Acute Myelogenous Leukemia and Acute Lymphoblastic Leukemia Blasts by Killer Cell Immunoglobulin-Like Receptor–Negative Natural Killer Cells after NKG2A and LIR-1 Blockade. Biology of Blood and Marrow Transplantation. 16(5). 612–621. 79 indexed citations
3.
McCullar, Valarie, Robert A.J. Oostendorp, Angela Panoskaltsis‐Mortari, et al.. (2008). Mouse fetal and embryonic liver cells differentiate human umbilical cord blood progenitors into CD56-negative natural killer cell precursors in the absence of interleukin-15. Experimental Hematology. 36(5). 598–608. 36 indexed citations
4.
Yun, Gong, Jakub Tolar, Steven G. E. Marsh, et al.. (2007). A novel method for KIR-ligand typing by pyrosequencing to predict NK cell alloreactivity. Clinical Immunology. 123(3). 272–280. 11 indexed citations
5.
Lund, Troy C., Lorraine Anderson, Valarie McCullar, et al.. (2006). iTRAQ Is a Useful Method To Screen for Membrane-Bound Proteins Differentially Expressed in Human Natural Killer Cell Types. Journal of Proteome Research. 6(2). 644–653. 55 indexed citations
6.
Miller, Jeffrey S., Yvette Soignier, Angela Panoskaltsis‐Mortari, et al.. (2005). Successful adoptive transfer and in vivo expansion of human haploidentical NK cells in patients with cancer. Blood. 105(8). 3051–3057. 1428 indexed citations breakdown →
7.
Yun, Gong. (2004). NF-kB and neurodegenerative disorder in central nervous system. 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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