Maja Wållberg

569 total citations
18 papers, 405 citations indexed

About

Maja Wållberg is a scholar working on Immunology, Genetics and Surgery. According to data from OpenAlex, Maja Wållberg has authored 18 papers receiving a total of 405 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Immunology, 13 papers in Genetics and 5 papers in Surgery. Recurrent topics in Maja Wållberg's work include Diabetes and associated disorders (11 papers), Immune Cell Function and Interaction (9 papers) and T-cell and B-cell Immunology (8 papers). Maja Wållberg is often cited by papers focused on Diabetes and associated disorders (11 papers), Immune Cell Function and Interaction (9 papers) and T-cell and B-cell Immunology (8 papers). Maja Wållberg collaborates with scholars based in United Kingdom, Sweden and Singapore. Maja Wållberg's co-authors include Anne Cooke, F. Susan Wong, E. Allison Green, Robert A. Harris, Pere Santamaría, Adnane Achour, Jonas Bergquist, Esther C.W. Breij, Paola Zaccone and David Thomas and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Immunology and PLoS ONE.

In The Last Decade

Maja Wållberg

18 papers receiving 396 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Maja Wållberg United Kingdom 11 195 182 134 86 84 18 405
Suzana M. Anjos Canada 9 311 1.6× 256 1.4× 98 0.7× 119 1.4× 107 1.3× 9 593
Charles J. Kroger United States 13 141 0.7× 259 1.4× 99 0.7× 73 0.8× 90 1.1× 17 428
Alexis Styche United States 13 322 1.7× 284 1.6× 212 1.6× 183 2.1× 148 1.8× 19 693
Matthew A. Powers United States 11 240 1.2× 137 0.8× 163 1.2× 247 2.9× 73 0.9× 21 615
Ashley E. Ciecko United States 10 163 0.8× 115 0.6× 122 0.9× 67 0.8× 66 0.8× 19 308
Jiro Morimoto Japan 8 190 1.0× 151 0.8× 140 1.0× 65 0.8× 104 1.2× 18 364
F. Vargas Spain 11 341 1.7× 232 1.3× 281 2.1× 101 1.2× 186 2.2× 17 574
Andrea Valle Italy 7 203 1.0× 204 1.1× 112 0.8× 60 0.7× 80 1.0× 9 380
Xuan Geng Canada 4 137 0.7× 189 1.0× 86 0.6× 146 1.7× 51 0.6× 5 415
Nádia Duarte Portugal 12 123 0.6× 413 2.3× 93 0.7× 109 1.3× 77 0.9× 25 672

Countries citing papers authored by Maja Wållberg

Since Specialization
Citations

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

Fields of papers citing papers by Maja Wållberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maja Wållberg

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

All Works

18 of 18 papers shown
1.
Gan, Shu Uin, Richard G. Kay, Fiona M. Gribble, et al.. (2018). Immunosuppression overcomes insulin- and vector-specific immune responses that limit efficacy of AAV2/8-mediated insulin gene therapy in NOD mice. Gene Therapy. 26(1-2). 40–56. 8 indexed citations
2.
Benson, Robert A., Fabien Garçon, John R. Ferdinand, et al.. (2018). Non-Invasive Multiphoton Imaging of Islets Transplanted Into the Pinna of the NOD Mouse Ear Reveals the Immediate Effect of Anti-CD3 Treatment in Autoimmune Diabetes. Frontiers in Immunology. 9. 1006–1006. 9 indexed citations
3.
Scarpini, Cinzia G., Stephen Smith, Maja Wållberg, et al.. (2017). Anti‐oncostatin M antibody inhibits the pro‐malignant effects of oncostatin M receptor overexpression in squamous cell carcinoma. The Journal of Pathology. 244(3). 283–295. 22 indexed citations
4.
Wållberg, Maja, Jenny M. Phillips, Duncan Howie, et al.. (2017). Anti‐ CD 3 treatment up‐regulates programmed cell death protein‐1 expression on activated effector T cells and severely impairs their inflammatory capacity. Immunology. 151(2). 248–260. 20 indexed citations
5.
Thaker, Youg Raj, et al.. (2017). Activated Cdc42-associated kinase 1 (ACK1) binds the sterile α motif (SAM) domain of the adaptor SLP-76 and phosphorylates proximal tyrosines. Journal of Biological Chemistry. 292(15). 6281–6290. 16 indexed citations
6.
Riva, Alessandra, Maja Wållberg, Francesca Ronchi, et al.. (2017). Regulation of type 1 diabetes development and B-cell activation in nonobese diabetic mice by early life exposure to a diabetogenic environment. PLoS ONE. 12(8). e0181964–e0181964. 13 indexed citations
7.
Wong, F. Susan, et al.. (2017). Hyperglycaemia does not affect antigen-specific activation and cytolytic killing by CD8+ T cells in vivo. Bioscience Reports. 37(4). 11 indexed citations
9.
Foale, R, Jing Zhao, Shu Uin Gan, et al.. (2016). Promoter optimisation of lentiviral vectors for efficient insulin gene expression in canine mesenchymal stromal cells: potential surrogate beta cells. The Journal of Gene Medicine. 18(10). 312–321. 10 indexed citations
10.
Wållberg, Maja & Anne Cooke. (2013). Immune mechanisms in type 1 diabetes. Trends in Immunology. 34(12). 583–591. 109 indexed citations
11.
Thomas, David, F. Susan Wong, Paola Zaccone, E. Allison Green, & Maja Wållberg. (2013). Protection of Islet Grafts Through Transforming Growth Factor-β–Induced Tolerogenic Dendritic Cells. Diabetes. 62(9). 3132–3142. 36 indexed citations
12.
Wållberg, Maja, F. Susan Wong, & E. Allison Green. (2011). An Islet-Specific Pulse of TGF-β Abrogates CTL Function and Promotes β Cell Survival Independent of Foxp3+ T Cells. The Journal of Immunology. 186(4). 2543–2551. 10 indexed citations
13.
Wållberg, Maja & E. Allison Green. (2009). Are B Cells a Potential Target for Therapeutic Intervention in the Classical T Cell-Mediated Autoimmune Disease Type 1 Diabetes?. Inflammation & Allergy - Drug Targets. 8(2). 130–138. 3 indexed citations
14.
Wållberg, Maja, et al.. (2008). B-Cells Promote Intra-Islet CD8+ Cytotoxic T-Cell Survival to Enhance Type 1 Diabetes. Diabetes. 57(4). 909–917. 56 indexed citations
15.
Wållberg, Maja, Jonas Bergquist, Adnane Achour, Esther C.W. Breij, & Robert A. Harris. (2007). Malondialdehyde modification of myelin oligodendrocyte glycoprotein leads to increased immunogenicity and encephalitogenicity. European Journal of Immunology. 37(7). 1986–1995. 42 indexed citations
16.
Chamberlain, Giselle, Maja Wållberg, Dan Rainbow, et al.. (2006). A 20-Mb Region of Chromosome 4 Controls TNF-α-Mediated CD8+ T Cell Aggression Toward β Cells in Type 1 Diabetes. The Journal of Immunology. 177(8). 5105–5114. 6 indexed citations
17.
Wållberg, Maja & Robert A. Harris. (2005). Co-infection with Trypanosoma brucei brucei prevents experimental autoimmune encephalomyelitis in DBA/1 mice through induction of suppressor APCs. International Immunology. 17(6). 721–728. 20 indexed citations
18.
Wållberg, Maja, et al.. (2003). Vaccination with myelin oligodendrocyte glycoprotein adsorbed to alum effectively protects DBA/1 mice from experimental autoimmune encephalomyelitis. European Journal of Immunology. 33(6). 1539–1547. 9 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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