Anna Goodsall

1.1k total citations · 1 hit paper
7 papers, 895 citations indexed

About

Anna Goodsall is a scholar working on Epidemiology, Immunology and Infectious Diseases. According to data from OpenAlex, Anna Goodsall has authored 7 papers receiving a total of 895 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Epidemiology, 4 papers in Immunology and 2 papers in Infectious Diseases. Recurrent topics in Anna Goodsall's work include T-cell and B-cell Immunology (2 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers) and Mycobacterium research and diagnosis (2 papers). Anna Goodsall is often cited by papers focused on T-cell and B-cell Immunology (2 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers) and Mycobacterium research and diagnosis (2 papers). Anna Goodsall collaborates with scholars based in Australia, United Kingdom and United States. Anna Goodsall's co-authors include A L Ford, JD Sedgwick, William F. Hickey, Michael Levin, Jonathon D. Sedgwick, Suzanne T. Anderson, Simon J. Waddell, David A. Relman, Robert N. Davidson and Mark P. Nicol and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and The Journal of Immunology.

In The Last Decade

Anna Goodsall

7 papers receiving 879 citations

Hit Papers

Normal adult ramified microglia separated from other cent... 1995 2026 2005 2015 1995 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anna Goodsall Australia 7 517 413 212 151 106 7 895
Margit Homola United States 6 528 1.0× 521 1.3× 103 0.5× 75 0.5× 131 1.2× 7 1.0k
Yasaman Shirazi United States 11 403 0.8× 213 0.5× 203 1.0× 83 0.5× 166 1.6× 15 925
Kirstin M. Heutinck Netherlands 15 415 0.8× 206 0.5× 213 1.0× 101 0.7× 196 1.8× 20 1.0k
A L Ford Australia 8 717 1.4× 677 1.6× 72 0.3× 47 0.3× 133 1.3× 8 1.1k
Michael T. Liu United States 10 599 1.2× 206 0.5× 180 0.8× 256 1.7× 99 0.9× 10 1.1k
Maria P. Lemos United States 11 758 1.5× 319 0.8× 91 0.4× 81 0.5× 241 2.3× 22 1.2k
Angela S. Archambault United States 17 452 0.9× 133 0.3× 139 0.7× 92 0.6× 192 1.8× 24 860
Jeanne M. Soos United States 17 657 1.3× 164 0.4× 105 0.5× 66 0.4× 166 1.6× 30 998
Ingeborg Huitinga Netherlands 12 308 0.6× 119 0.3× 69 0.3× 115 0.8× 105 1.0× 16 713
Peter Manders Australia 12 601 1.2× 163 0.4× 126 0.6× 49 0.3× 146 1.4× 16 922

Countries citing papers authored by Anna Goodsall

Since Specialization
Citations

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

Fields of papers citing papers by Anna Goodsall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anna Goodsall

This figure shows the co-authorship network connecting the top 25 collaborators of Anna Goodsall. A scholar is included among the top collaborators of Anna Goodsall 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 Anna Goodsall. Anna Goodsall 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.
Pulickal, Anoop S., Sophie Hambleton, Martin Callaghan, et al.. (2008). Biliary Cirrhosis in a Child with Inherited Interleukin-12 Deficiency. Journal of Tropical Pediatrics. 54(4). 269–271. 20 indexed citations
2.
Kelleher, Peter, Anna Goodsall, Aruni Mulgirigama, et al.. (2006). Interferon-γ therapy in two patients with progressive chronic pulmonary aspergillosis. European Respiratory Journal. 27(6). 1307–1310. 53 indexed citations
3.
Kampmann, Beate, Cheryl Hemingway, Alick Stephens, et al.. (2005). Acquired predisposition to mycobacterial disease due to autoantibodies to IFN-γ. Journal of Clinical Investigation. 115(9). 2480–2488. 179 indexed citations
4.
Ford, A L, et al.. (1996). Tissue digestion with dispase substantially reduces lymphocyte and macrophage cell-surface antigen expression. Journal of Immunological Methods. 194(1). 71–75. 42 indexed citations
5.
Ford, A L, Anna Goodsall, William F. Hickey, & JD Sedgwick. (1995). Normal adult ramified microglia separated from other central nervous system macrophages by flow cytometric sorting. Phenotypic differences defined and direct ex vivo antigen presentation to myelin basic protein-reactive CD4+ T cells compared.. The Journal of Immunology. 154(9). 4309–4321. 533 indexed citations breakdown →
6.
Körner, Heinrich, Anna Goodsall, Bernard J. Scallon, et al.. (1995). Unimpaired autoreactive T-cell traffic within the central nervous system during tumor necrosis factor receptor-mediated inhibition of experimental autoimmune encephalomyelitis.. Proceedings of the National Academy of Sciences. 92(24). 11066–11070. 55 indexed citations
7.
Adams, Elizabeth M., et al.. (1993). Identification of human T cell epitopes in theMycobacterium lepraeheat shock protein 70-kD antigen. Clinical & Experimental Immunology. 94(3). 500–506. 13 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026