Edwin D. Hawkins

5.4k total citations
54 papers, 2.2k citations indexed

About

Edwin D. Hawkins is a scholar working on Immunology, Molecular Biology and Hematology. According to data from OpenAlex, Edwin D. Hawkins has authored 54 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Immunology, 23 papers in Molecular Biology and 12 papers in Hematology. Recurrent topics in Edwin D. Hawkins's work include T-cell and B-cell Immunology (22 papers), Immune Cell Function and Interaction (20 papers) and Immunotherapy and Immune Responses (15 papers). Edwin D. Hawkins is often cited by papers focused on T-cell and B-cell Immunology (22 papers), Immune Cell Function and Interaction (20 papers) and Immunotherapy and Immune Responses (15 papers). Edwin D. Hawkins collaborates with scholars based in Australia, United Kingdom and United States. Edwin D. Hawkins's co-authors include Philip D. Hodgkin, John Markham, Marian L. Turner, Mirja Hommel, Mark R. Dowling, Axel Kallies, Cristina Lo Celso, Delfim Duarte, Stephen L. Nutt and Gabrielle T. Belz and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Edwin D. Hawkins

51 papers receiving 2.1k citations

Peers

Edwin D. Hawkins

IMMUN

ONCOL

HEMAT

Amrie C. Grammer United States

Rosa Molfetta Italy

Shlomit Reich-Zeliger Israel

Chauncey J. Spooner United States

Fiona Hamey United Kingdom

Miguel Á. de la Fuente Spain

Astraea Jager United States

Carsten Krieg United States

Joakim S. Dahlin Sweden

Sachiko Hirose Japan

Amrie C. Grammer United States

Edwin D. Hawkins

2.0k ×1.7

IMMUN

760 ×0.9

408 ×1.0

ONCOL

118 ×0.4

HEMAT

241 ×1.5

Citations per year, relative to Edwin D. Hawkins Edwin D. Hawkins (= 1×) peers Amrie C. Grammer

Countries citing papers authored by Edwin D. Hawkins

Since Specialization

Citations

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

Fields of papers citing papers by Edwin D. Hawkins

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Edwin D. Hawkins. 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 Edwin D. Hawkins. The network helps show where Edwin D. Hawkins may publish in the future.

Co-authorship network of co-authors of Edwin D. Hawkins

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

All Works

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20 of 20 papers shown

Horne, Christopher R., Adele Preaudet, Samuel N. Young, et al.. (2026). The kinase domain of RIPK3 tunes its scaffolding functions. Cell Death and Differentiation.

Hawkins, Edwin D., et al.. (2025). Towards deciphering the bone marrow microenvironment with spatial multi-omics. Seminars in Cell and Developmental Biology. 167. 10–21. 2 indexed citations

Todorovski, Izabela, Zheng Fan, Isabella Y. Kong, et al.. (2024). RNA kinetics influence the response to transcriptional perturbation in leukaemia cell lines. NAR Cancer. 6(4). zcae039–zcae039. 1 indexed citations

Cawthorne, Wayne, Sarah E. Garnish, Cathrine Hall, et al.. (2024). MLKL deficiency elevates testosterone production in male mice independently of necroptotic functions. Cell Death and Disease. 15(11). 851–851.

Kong, Isabella Y., et al.. (2023). An arrayed CRISPR screen of primary B cells reveals the essential elements of the antibody secretion pathway. Frontiers in Immunology. 14. 1089243–1089243. 6 indexed citations

Samson, André L., Cheree Fitzgibbon, Joanne M. Hildebrand, et al.. (2021). A toolbox for imaging RIPK1, RIPK3, and MLKL in mouse and human cells. Cell Death and Differentiation. 28(7). 2126–2144. 43 indexed citations

Capaldo, Bianca D., François Vaillant, Kellie A. Mouchemore, et al.. (2021). Mammary tumour cells remodel the bone marrow vascular microenvironment to support metastasis. Nature Communications. 12(1). 6920–6920. 69 indexed citations

Kan, Andrey, Simone C. Oostindie, Simon J. Dovedi, et al.. (2021). Cyton2: A Model of Immune Cell Population Dynamics That Includes Familial Instructional Inheritance. SHILAP Revista de lepidopterología. 1. 723337–723337. 7 indexed citations

Kong, Isabella Y., Amanda Light, Izabela Todorovski, et al.. (2020). Temporal Analysis of Brd4 Displacement in the Control of B Cell Survival, Proliferation, and Differentiation. Cell Reports. 33(3). 108290–108290. 5 indexed citations

10.

Akinduro, Olufolake, Tom Weber, Heather Ang, et al.. (2018). Proliferation dynamics of acute myeloid leukaemia and haematopoietic progenitors competing for bone marrow space. Nature Communications. 9(1). 519–519. 62 indexed citations

11.

Athanasiou, Dimitrios, Lowell T. Edgar, Mohammad Jafarnejad, et al.. (2017). The passive biomechanics of human pelvic collecting lymphatic vessels. PLoS ONE. 12(8). e0183222–e0183222. 7 indexed citations

12.

Rautela, Jai, Nikola Baschuk, Clare Y. Slaney, et al.. (2015). Loss of Host Type-I IFN Signaling Accelerates Metastasis and Impairs NK-cell Antitumor Function in Multiple Models of Breast Cancer. Cancer Immunology Research. 3(11). 1207–1217. 60 indexed citations

13.

Hawkins, Edwin D., Jane Oliaro, Axel Kallies, et al.. (2013). Regulation of asymmetric cell division and polarity by Scribble is not required for humoral immunity. Nature Communications. 4(1). 1801–1801. 56 indexed citations

14.

Markham, John, Cameron Wellard, Edwin D. Hawkins, Ken R. Duffy, & Philip D. Hodgkin. (2010). A minimum of two distinct heritable factors are required to explain correlation structures in proliferating lymphocytes. Journal of The Royal Society Interface. 7(48). 1049–1059. 21 indexed citations

15.

Wellard, Cameron, John Markham, Edwin D. Hawkins, & Philip D. Hodgkin. (2010). The effect of correlations on the population dynamics of lymphocytes. Journal of Theoretical Biology. 264(2). 443–449. 16 indexed citations

16.

Hawkins, Edwin D. & Jane Oliaro. (2010). CD46 signaling in T cells: Linking pathogens with polarity. FEBS Letters. 584(24). 4838–4844. 15 indexed citations

17.

Turner, Marian L., Edwin D. Hawkins, & Philip D. Hodgkin. (2008). Quantitative Regulation of B Cell Division Destiny by Signal Strength. The Journal of Immunology. 181(1). 374–382. 50 indexed citations

18.

Hawkins, Edwin D. & Sarah M. Russell. (2008). Upsides and downsides to polarity and asymmetric cell division in leukemia. Oncogene. 27(55). 7003–7017. 27 indexed citations

19.

Hawkins, Edwin D., Mirja Hommel, Marian L. Turner, et al.. (2007). Measuring lymphocyte proliferation, survival and differentiation using CFSE time-series data. Nature Protocols. 2(9). 2057–2067. 187 indexed citations

20.

Rizzitelli, Alexandra, et al.. (2006). The proliferative response of CD4 T cells to steady-state CD8+ dendritic cells is restricted by post-activation death. International Immunology. 18(3). 415–423. 16 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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