Frida Lundmark

681 total citations
8 papers, 440 citations indexed

About

Frida Lundmark is a scholar working on Immunology, Pathology and Forensic Medicine and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Frida Lundmark has authored 8 papers receiving a total of 440 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Immunology, 5 papers in Pathology and Forensic Medicine and 1 paper in Cardiology and Cardiovascular Medicine. Recurrent topics in Frida Lundmark's work include T-cell and B-cell Immunology (5 papers), Multiple Sclerosis Research Studies (5 papers) and Immunotherapy and Immune Responses (3 papers). Frida Lundmark is often cited by papers focused on T-cell and B-cell Immunology (5 papers), Multiple Sclerosis Research Studies (5 papers) and Immunotherapy and Immune Responses (3 papers). Frida Lundmark collaborates with scholars based in Sweden, Norway and Denmark. Frida Lundmark's co-authors include Jan Hillert, Kristina Duvefelt, Elisabeth Gulowsen Celius, Hugh Salter, Annette Oturai, Hanne F. Harbo, Janna Saarela, Tomas Olsson, Ingrid Kockum and Ellen Iacobaeus and has published in prestigious journals such as Nature Genetics, Journal of Neuroimmunology and Multiple Sclerosis Journal.

In The Last Decade

Frida Lundmark

8 papers receiving 428 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Frida Lundmark Sweden	7	269	194	101	86	70	8	440
Wangko Lundström Sweden	6	208 0.8×	118 0.6×	88 0.9×	81 0.9×	56 0.8×	8	397
Derek Pappas United States	11	145 0.5×	111 0.6×	188 1.9×	67 0.8×	51 0.7×	18	443
Scott S. Zamvil United States	7	335 1.2×	96 0.5×	88 0.9×	45 0.5×	38 0.5×	7	453
Arianne C. van Sechel Netherlands	6	263 1.0×	212 1.1×	241 2.4×	102 1.2×	83 1.2×	9	614
Kaushal Gandhi Australia	9	130 0.5×	99 0.5×	225 2.2×	52 0.6×	42 0.6×	10	448
S. Sriram United States	6	344 1.3×	162 0.8×	118 1.2×	109 1.3×	71 1.0×	12	605
Rami Gaber Germany	3	264 1.0×	155 0.8×	130 1.3×	63 0.7×	27 0.4×	4	408
R. Philip Kinkel United States	5	210 0.8×	98 0.5×	44 0.4×	40 0.5×	45 0.6×	7	328
R. Medaer Belgium	9	172 0.6×	184 0.9×	56 0.6×	41 0.5×	46 0.7×	16	352
Kelly M. Nikcevich United States	5	362 1.3×	96 0.5×	66 0.7×	71 0.8×	51 0.7×	6	475

Countries citing papers authored by Frida Lundmark

Since Specialization

Citations

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

Fields of papers citing papers by Frida Lundmark

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frida Lundmark

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

All Works

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8 of 8 papers shown

1.

Jeppsson, Fredrik, et al.. (2017). “Wow, It Turned Out Red! First, a Little Yellow, and Then Red!” 1st-Graders’ Work With an Infrared Camera. Journal of Research in Childhood Education. 31(4). 581–596. 8 indexed citations

2.

Lundström, Wangko, Eva Greiner, Frida Lundmark, et al.. (2011). No influence on disease progression of non-HLA susceptibility genes in MS. Journal of Neuroimmunology. 237(1-2). 98–100. 7 indexed citations

3.

Kemppinen, Anu, Minna Suvela, Pentti J. Tienari, et al.. (2009). MYO9B polymorphisms in multiple sclerosis. European Journal of Human Genetics. 17(6). 840–843. 3 indexed citations

4.

Öckinger, Johan, Pernilla Stridh, Amennai Daniel Beyeen, et al.. (2009). Genetic variants of CC chemokine genes in experimental autoimmune encephalomyelitis, multiple sclerosis and rheumatoid arthritis. Genes and Immunity. 11(2). 142–154. 22 indexed citations

5.

Lundmark, Frida, Kristina Duvefelt, & Jan Hillert. (2007). Genetic association analysis of the interleukin 7 gene (IL7) in multiple sclerosis. Journal of Neuroimmunology. 192(1-2). 171–173. 20 indexed citations

6.

Lundmark, Frida, Kristina Duvefelt, Ellen Iacobaeus, et al.. (2007). Variation in interleukin 7 receptor α chain (IL7R) influences risk of multiple sclerosis. Nature Genetics. 39(9). 1108–1113. 357 indexed citations

7.

Lundmark, Frida, Hugh Salter, & Jan Hillert. (2007). An association study of two functional promotor polymorphisms in the myeloperoxidase (MPO) gene in multiple sclerosis. Multiple Sclerosis Journal. 13(6). 697–700. 6 indexed citations

8.

Lundmark, Frida, Hanne F. Harbo, Elisabeth Gulowsen Celius, et al.. (2006). Association analysis of the LAG3 and CD4 genes in multiple sclerosis in two independent populations. Journal of Neuroimmunology. 180(1-2). 193–198. 17 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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