Winnie L. Kan

412 total citations
10 papers, 252 citations indexed

About

Winnie L. Kan is a scholar working on Immunology, Oncology and Genetics. According to data from OpenAlex, Winnie L. Kan has authored 10 papers receiving a total of 252 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Immunology, 3 papers in Oncology and 2 papers in Genetics. Recurrent topics in Winnie L. Kan's work include Immune Cell Function and Interaction (3 papers), Cytokine Signaling Pathways and Interactions (3 papers) and Immune Response and Inflammation (2 papers). Winnie L. Kan is often cited by papers focused on Immune Cell Function and Interaction (3 papers), Cytokine Signaling Pathways and Interactions (3 papers) and Immune Response and Inflammation (2 papers). Winnie L. Kan collaborates with scholars based in Australia, India and Singapore. Winnie L. Kan's co-authors include Angel F. López, Timothy R. Hercus, Michael W. Parker, Sophie E. Broughton, Tracy L. Nero, Urmi Dhagat, Denis Tvorogov, Timothy P. Hughes, Emma F. Barry and Mara Dottore and has published in prestigious journals such as Nature Communications, PLoS ONE and Science Advances.

In The Last Decade

Winnie L. Kan

9 papers receiving 249 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Winnie L. Kan Australia	5	129	76	64	55	34	10	252
Carole Sanchez France	9	205 1.6×	103 1.4×	39 0.6×	71 1.3×	47 1.4×	15	323
Andrew Podd United States	7	304 2.4×	85 1.1×	73 1.1×	54 1.0×	24 0.7×	10	434
Cornelis E. Hack Netherlands	7	148 1.1×	20 0.3×	52 0.8×	61 1.1×	96 2.8×	8	295
Tanja Telieps Germany	6	192 1.5×	73 1.0×	53 0.8×	62 1.1×	20 0.6×	10	306
P.A. Usher Denmark	6	303 2.3×	66 0.9×	52 0.8×	68 1.2×	8 0.2×	7	395
Sandra C. Silva‐Cardoso Netherlands	9	129 1.0×	37 0.5×	50 0.8×	29 0.5×	9 0.3×	9	235
Simanta Pathak United States	9	210 1.6×	86 1.1×	121 1.9×	62 1.1×	29 0.9×	12	371
Oliver Eltherington United Kingdom	4	251 1.9×	57 0.8×	63 1.0×	23 0.4×	8 0.2×	4	325
Y Hamano Japan	5	206 1.6×	27 0.4×	74 1.2×	50 0.9×	46 1.4×	8	319
Manfred Ahlgrimm Germany	8	50 0.4×	90 1.2×	76 1.2×	49 0.9×	56 1.6×	17	272

Countries citing papers authored by Winnie L. Kan

Since Specialization

Citations

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

Fields of papers citing papers by Winnie L. Kan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Winnie L. Kan. 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 Winnie L. Kan. The network helps show where Winnie L. Kan may publish in the future.

Co-authorship network of co-authors of Winnie L. Kan

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

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Kan, Winnie L., Claire M. Weekley, Tracy L. Nero, et al.. (2025). The β Common Cytokine Receptor Family Reveals New Functional Paradigms From Structural Complexities. Immunological Reviews. 329(1). e13430–e13430. 1 indexed citations

2.

Lim, Kelly, Winnie L. Kan, Pramod C. Nair, et al.. (2024). CBL mutations in chronic myelomonocytic leukemia often occur in the RING domain with multiple subclones per patient: Implications for targeting. PLoS ONE. 19(9). e0310641–e0310641.

3.

Kan, Winnie L., Tracy L. Nero, Timothy R. Hercus, et al.. (2021). Messing with βc: A unique receptor with many goals. Seminars in Immunology. 54. 101513–101513. 3 indexed citations

4.

Tvorogov, Denis, Danièl Thomas, Nicholas P. D. Liau, et al.. (2018). Accumulation of JAK activation loop phosphorylation is linked to type I JAK inhibitor withdrawal syndrome in myelofibrosis. Science Advances. 4(11). eaat3834–eaat3834. 41 indexed citations

5.

Broughton, Sophie E., Timothy R. Hercus, Tracy L. Nero, et al.. (2018). A dual role for the N-terminal domain of the IL-3 receptor in cell signalling. Nature Communications. 9(1). 386–386. 31 indexed citations

6.

Broughton, Sophie E., Tracy L. Nero, Urmi Dhagat, et al.. (2015). The βc receptor family – Structural insights and their functional implications. Cytokine. 74(2). 247–258. 60 indexed citations

7.

Broughton, Sophie E., Timothy R. Hercus, Matthew P. Hardy, et al.. (2014). Dual Mechanism of Interleukin-3 Receptor Blockade by an Anti-Cancer Antibody. Cell Reports. 8(2). 410–419. 39 indexed citations

8.

Broughton, Sophie E., Matthew P. Hardy, Tracy L. Nero, et al.. (2014). 78. Cytokine. 70(1). 46–46. 1 indexed citations

9.

Hercus, Timothy R., Urmi Dhagat, Winnie L. Kan, et al.. (2013). Signalling by the beta c family of cytokines. Cytokine & Growth Factor Reviews. 24(3). 2 indexed citations

10.

Hercus, Timothy R., Urmi Dhagat, Winnie L. Kan, et al.. (2013). Signalling by the βc family of cytokines. Cytokine & Growth Factor Reviews. 24(3). 189–201. 74 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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