Iris K. Pang

2.9k total citations · 2 hit papers
8 papers, 2.3k citations indexed

About

Iris K. Pang is a scholar working on Immunology, Molecular Biology and Epidemiology. According to data from OpenAlex, Iris K. Pang has authored 8 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Immunology, 4 papers in Molecular Biology and 4 papers in Epidemiology. Recurrent topics in Iris K. Pang's work include Immune Response and Inflammation (6 papers), interferon and immune responses (5 papers) and Influenza Virus Research Studies (4 papers). Iris K. Pang is often cited by papers focused on Immune Response and Inflammation (6 papers), interferon and immune responses (5 papers) and Influenza Virus Research Studies (4 papers). Iris K. Pang collaborates with scholars based in United States, Japan and Argentina. Iris K. Pang's co-authors include Akiko Iwasaki, Takeshi Ichinohe, John Ho, Thomas S. Murray, Yosuke Kumamoto, David R. Peaper, Padmini S. Pillai, Piotr Bielecki, Subhasis Mohanty and Denisa D. Wagner and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Immunology.

In The Last Decade

Iris K. Pang

8 papers receiving 2.3k citations

Hit Papers

Microbiota regulates immune defense against respiratory t... 2010 2026 2015 2020 2011 2010 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Iris K. Pang United States 8 1.2k 1.0k 743 670 175 8 2.3k
Navkiran Gill Canada 20 1.1k 0.9× 753 0.7× 410 0.6× 546 0.8× 154 0.9× 27 2.2k
Liesbeth Jacobs Netherlands 19 1.1k 0.9× 1.7k 1.7× 718 1.0× 917 1.4× 78 0.4× 28 3.4k
Trees Jansen Netherlands 13 1.1k 0.9× 1.7k 1.6× 501 0.7× 748 1.1× 62 0.4× 15 3.0k
Lauren Lipuma United States 11 1.5k 1.3× 853 0.8× 628 0.8× 1.3k 1.9× 51 0.3× 12 3.2k
Julia Cahenzli Switzerland 7 1.3k 1.1× 815 0.8× 210 0.3× 531 0.8× 204 1.2× 8 2.3k
Stephanie M. Dillon United States 28 1.1k 0.9× 1.6k 1.6× 546 0.7× 715 1.1× 45 0.3× 53 3.3k
Eva Sverremark‐Ekström Sweden 31 782 0.7× 1.6k 1.5× 770 1.0× 308 0.5× 206 1.2× 92 3.4k
Lisa M. Mattei United States 19 950 0.8× 520 0.5× 661 0.9× 551 0.8× 39 0.2× 39 2.2k
Keiichiro Suzuki Japan 23 1.6k 1.4× 2.4k 2.3× 289 0.4× 778 1.2× 112 0.6× 31 4.1k
Maaike Stoel Netherlands 9 1.2k 1.0× 725 0.7× 195 0.3× 525 0.8× 115 0.7× 10 2.2k

Countries citing papers authored by Iris K. Pang

Since Specialization
Citations

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

Fields of papers citing papers by Iris K. Pang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Iris K. Pang

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

All Works

8 of 8 papers shown
1.
Pillai, Padmini S., Ryan D. Molony, Kimberly Martinod, et al.. (2016). Mx1 reveals innate pathways to antiviral resistance and lethal influenza disease. Science. 352(6284). 463–466. 186 indexed citations
2.
Schmid, Edward T., Iris K. Pang, Eugenio Antonio Carrera Silva, et al.. (2016). AXL receptor tyrosine kinase is required for T cell priming and antiviral immunity. eLife. 5. 47 indexed citations
3.
Pang, Iris K., Takeshi Ichinohe, & Akiko Iwasaki. (2013). IL-1R signaling in dendritic cells replaces pattern-recognition receptors in promoting CD8+ T cell responses to influenza A virus. Nature Immunology. 14(3). 246–253. 113 indexed citations
4.
Pang, Iris K., Padmini S. Pillai, & Akiko Iwasaki. (2013). Efficient influenza A virus replication in the respiratory tract requires signals from TLR7 and RIG-I. Proceedings of the National Academy of Sciences. 110(34). 13910–13915. 67 indexed citations
5.
Ichinohe, Takeshi, Iris K. Pang, Yosuke Kumamoto, et al.. (2011). Microbiota regulates immune defense against respiratory tract influenza A virus infection. Proceedings of the National Academy of Sciences. 108(13). 5354–5359. 1144 indexed citations breakdown →
6.
Pang, Iris K. & Akiko Iwasaki. (2011). Control of antiviral immunity by pattern recognition and the microbiome. Immunological Reviews. 245(1). 209–226. 78 indexed citations
7.
Pang, Iris K. & Akiko Iwasaki. (2010). Inflammasomes as mediators of immunity against influenza virus. Trends in Immunology. 32(1). 34–41. 131 indexed citations
8.
Ichinohe, Takeshi, Iris K. Pang, & Akiko Iwasaki. (2010). Influenza virus activates inflammasomes via its intracellular M2 ion channel. Nature Immunology. 11(5). 404–410. 519 indexed citations breakdown →

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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