W.A. Macdonald

1.9k total citations
16 papers, 1.5k citations indexed

About

W.A. Macdonald is a scholar working on Immunology, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, W.A. Macdonald has authored 16 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Immunology, 4 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Molecular Biology. Recurrent topics in W.A. Macdonald's work include T-cell and B-cell Immunology (12 papers), Immunotherapy and Immune Responses (12 papers) and Immune Cell Function and Interaction (11 papers). W.A. Macdonald is often cited by papers focused on T-cell and B-cell Immunology (12 papers), Immunotherapy and Immune Responses (12 papers) and Immune Cell Function and Interaction (11 papers). W.A. Macdonald collaborates with scholars based in Australia and United States. W.A. Macdonald's co-authors include James McCluskey, Jamie Rossjohn, Anthony W. Purcell, Lars Kjer‐Nielsen, Craig S. Clements, Scott R. Burrows, Lauren K. Ely, Julia K. Archbold, Andrëw G. Brööks and Nicole A. Mifsud and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Experimental Medicine and Immunity.

In The Last Decade

W.A. Macdonald

15 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
W.A. Macdonald Australia	15	1.2k	272	237	202	196	16	1.5k
S. Meuer Germany	10	1.1k 0.9×	220 0.8×	419 1.8×	231 1.1×	11 0.1×	14	1.4k
Andréa Luciana Soares da Silva Brazil	5	387 0.3×	131 0.5×	42 0.2×	88 0.4×	71 0.4×	7	632
Věra Hauptfeld United States	22	833 0.7×	304 1.1×	240 1.0×	59 0.3×	60 0.3×	41	1.5k
Shiro Shibayama Japan	13	662 0.6×	310 1.1×	82 0.3×	414 2.0×	34 0.2×	26	1.2k
G. B. Ferrara Italy	16	741 0.6×	87 0.3×	47 0.2×	83 0.4×	19 0.1×	34	970
Robert J. Ziccardi United States	19	742 0.6×	247 0.9×	194 0.8×	93 0.5×	27 0.1×	30	1.2k
H. David Kay United States	9	1.0k 0.9×	189 0.7×	247 1.0×	218 1.1×	16 0.1×	11	1.3k
V J Merluzzi United States	14	552 0.5×	297 1.1×	164 0.7×	252 1.2×	27 0.1×	27	1.4k
Karin Bilger France	21	343 0.3×	134 0.5×	55 0.2×	339 1.7×	17 0.1×	41	1.6k
Dominic J. Barker United Kingdom	7	1.6k 1.3×	231 0.8×	191 0.8×	70 0.3×	14 0.1×	12	1.8k

Countries citing papers authored by W.A. Macdonald

Since Specialization

Citations

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

Fields of papers citing papers by W.A. Macdonald

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by W.A. Macdonald. 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 W.A. Macdonald. The network helps show where W.A. Macdonald may publish in the future.

Co-authorship network of co-authors of W.A. Macdonald

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

All Works

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16 of 16 papers shown

1.

Beddoe, Travis, Zhenjun Chen, Craig S. Clements, et al.. (2009). Antigen Ligation Triggers a Conformational Change within the Constant Domain of the αβ T Cell Receptor. Immunity. 30(6). 777–788. 94 indexed citations

2.

Macdonald, W.A., Zhenjun Chen, Stéphanie Gras, et al.. (2009). T Cell Allorecognition via Molecular Mimicry. Immunity. 31(6). 897–908. 211 indexed citations

3.

Archbold, Julia K., W.A. Macdonald, Stéphanie Gras, et al.. (2009). Natural micropolymorphism in human leukocyte antigens provides a basis for genetic control of antigen recognition. The Journal of Experimental Medicine. 206(1). 209–219. 80 indexed citations

4.

Kostenko, Lyudmila, Anthony W. Purcell, Nicholas A. Williamson, et al.. (2008). Human Leukocyte Antigen Class I-Restricted Activation of CD8+ T Cells Provides the Immunogenetic Basis of a Systemic Drug Hypersensitivity. Immunity. 29(1). 165–165. 1 indexed citations

5.

Dai, Shaodong, Eric S. Huseby, Kira Rubtsova, et al.. (2008). Crossreactive T Cells Spotlight the Germline Rules for αβ T Cell-Receptor Interactions with MHC Molecules. Immunity. 28(3). 324–334. 136 indexed citations

6.

Archbold, Julia K., W.A. Macdonald, Scott R. Burrows, Jamie Rossjohn, & James McCluskey. (2008). T-cell allorecognition: a case of mistaken identity or déjà vu?. Trends in Immunology. 29(5). 220–226. 39 indexed citations

7.

Kostenko, Lyudmila, Anthony W. Purcell, Nicholas A. Williamson, et al.. (2008). Human Leukocyte Antigen Class I-Restricted Activation of CD8+ T Cells Provides the Immunogenetic Basis of a Systemic Drug Hypersensitivity. Immunity. 28(6). 822–832. 248 indexed citations

8.

Archbold, Julia K., Lauren K. Ely, Lars Kjer‐Nielsen, et al.. (2007). T cell allorecognition and MHC restriction—A case of Jekyll and Hyde?. Molecular Immunology. 45(3). 583–598. 30 indexed citations

9.

Archbold, Julia K., W.A. Macdonald, John J. Miles, et al.. (2006). Alloreactivity between Disparate Cognate and Allogeneic pMHC-I Complexes Is the Result of Highly Focused, Peptide-dependent Structural Mimicry. Journal of Biological Chemistry. 281(45). 34324–34332. 49 indexed citations

10.

Clements, Craig S., Michelle A. Dunstone, W.A. Macdonald, James McCluskey, & Jamie Rossjohn. (2006). Specificity on a knife-edge: the αβ T cell receptor. Current Opinion in Structural Biology. 16(6). 787–795. 36 indexed citations

11.

Borg, Natalie A., Lauren K. Ely, Travis Beddoe, et al.. (2005). The CDR3 regions of an immunodominant T cell receptor dictate the 'energetic landscape' of peptide-MHC recognition. Nature Immunology. 6(2). 171–180. 152 indexed citations

12.

Purcell, Anthony W., W.A. Macdonald, Lars Kjer‐Nielsen, et al.. (2004). Natural HLA Class I Polymorphism Controls the Pathway of Antigen Presentation and Susceptibility to Viral Evasion. The Journal of Experimental Medicine. 200(1). 13–24. 135 indexed citations

13.

Macdonald, W.A., Anthony W. Purcell, Nicole A. Mifsud, et al.. (2003). A Naturally Selected Dimorphism within the HLA-B44 Supertype Alters Class I Structure, Peptide Repertoire, and T Cell Recognition. The Journal of Experimental Medicine. 198(5). 679–691. 167 indexed citations

14.

Purcell, Anthony W., Weiguang Zeng, Nicole A. Mifsud, et al.. (2003). Dissecting the role of peptides in the immune response: theory, practice and the application to vaccine design. Journal of Peptide Science. 9(5). 255–281. 48 indexed citations

15.

Macdonald, W.A., David Williams, Craig S. Clements, et al.. (2002). Identification of a dominant self‐ligand bound to three HLA B44 alleles and the preliminary crystallographic analysis of recombinant forms of each complex. FEBS Letters. 527(1-3). 27–32. 33 indexed citations

16.

Clements, Craig S., Lars Kjer‐Nielsen, W.A. Macdonald, et al.. (2002). The production, purification and crystallization of a soluble heterodimeric form of a highly selected T-cell receptor in its unliganded and liganded state. Acta Crystallographica Section D Biological Crystallography. 58(12). 2131–2134. 52 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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