Martin Stenström

830 total citations
16 papers, 660 citations indexed

About

Martin Stenström is a scholar working on Immunology, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Martin Stenström has authored 16 papers receiving a total of 660 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Immunology, 4 papers in Molecular Biology and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Martin Stenström's work include T-cell and B-cell Immunology (6 papers), Immune Cell Function and Interaction (5 papers) and Immune Response and Inflammation (4 papers). Martin Stenström is often cited by papers focused on T-cell and B-cell Immunology (6 papers), Immune Cell Function and Interaction (5 papers) and Immune Response and Inflammation (4 papers). Martin Stenström collaborates with scholars based in Sweden, Germany and Switzerland. Martin Stenström's co-authors include Tomas Leanderson, Fredrik Ivars, David Liberg, Susanna Cardell, Anders Björk, Anders Olsson, Thomas Vogl, Johannes Roth, Per Björk and Dan Holmberg and has published in prestigious journals such as The Journal of Immunology, Cancer Research and PLoS Biology.

In The Last Decade

Martin Stenström

16 papers receiving 653 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Martin Stenström Sweden 11 416 288 82 80 51 16 660
Elahe Crockett-Torabi United States 11 338 0.8× 196 0.7× 75 0.9× 34 0.4× 51 1.0× 12 666
Ganapathy Sriram United States 13 342 0.8× 280 1.0× 185 2.3× 44 0.6× 55 1.1× 19 679
Erik Ehinger United States 9 666 1.6× 348 1.2× 123 1.5× 49 0.6× 49 1.0× 12 870
David Soler United States 12 249 0.6× 134 0.5× 94 1.1× 60 0.8× 38 0.7× 26 505
Ekaterina Pylaeva Germany 12 407 1.0× 157 0.5× 173 2.1× 63 0.8× 54 1.1× 34 613
Hirotaka Kazama Japan 9 549 1.3× 373 1.3× 88 1.1× 48 0.6× 53 1.0× 16 914
Claudia Gemelli Italy 18 143 0.3× 289 1.0× 114 1.4× 35 0.4× 77 1.5× 24 561
Graeme P. Sullivan Ireland 9 485 1.2× 225 0.8× 96 1.2× 45 0.6× 40 0.8× 13 738
Soile Tuomela Finland 15 388 0.9× 354 1.2× 136 1.7× 21 0.3× 70 1.4× 19 854
Daria Briukhovetska Germany 6 366 0.9× 202 0.7× 273 3.3× 55 0.7× 60 1.2× 6 674

Countries citing papers authored by Martin Stenström

Since Specialization
Citations

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

Fields of papers citing papers by Martin Stenström

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Martin Stenström

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

All Works

16 of 16 papers shown
1.
Stenström, Martin, Marie Törngren, David Liberg, et al.. (2016). Paquinimod reduces skin fibrosis in tight skin 1 mice, an experimental model of systemic sclerosis. Journal of Dermatological Science. 83(1). 52–59. 41 indexed citations
2.
Stenström, Martin, Mats Nilsson, Helena Eriksson, et al.. (2014). FRI0516 Paquinimod (ABR-215757), an Immunomodulatory Compound, Reduces Fibrosis in the Tight Skin-1 (TSK-1) Model for Systemic Sclerosis. Annals of the Rheumatic Diseases. 73. 574–574. 1 indexed citations
3.
Hesselstrand, Roger, Jörg H. W. Distler, Gabriela Riemekasten, et al.. (2014). FRI0496 An Open-Label Study to Evaluate Biomarkers and Safety in Systemic Sclerosis (SSC) Patients Treated with Paquinimod (ABR-215757). Annals of the Rheumatic Diseases. 73. 566–567. 3 indexed citations
4.
Sundstedt, Anette, Anders Olsson, Martin Stenström, et al.. (2013). Abstract B17: Immunomodulation by tasquinimod: Combination with immunotherapy results in enhanced CD8 T cell responses and improved antitumor effects.. Cancer Research. 73(1_Supplement). B17–B17. 1 indexed citations
5.
Källberg, Eva, Martin Stenström, David Liberg, Fredrik Ivars, & Tomas Leanderson. (2012). CD11b+Ly6C++Ly6G- cells show distinct function in mice with chronic inflammation or tumor burden. BMC Immunology. 13(1). 69–69. 26 indexed citations
6.
Lood, Christian, Martin Stenström, Helena Tydén, et al.. (2011). Protein synthesis of the pro-inflammatory S100A8/A9 complex in plasmacytoid dendritic cells and cell surface S100A8/A9 on leukocyte subpopulations in systemic lupus erythematosus. Arthritis Research & Therapy. 13(2). R60–R60. 52 indexed citations
7.
8.
Stenström, Martin, et al.. (2010). Selective depletion of splenic CD4 dendritic cells in mice treated with immunomodulatory quinoline-3-carboxamide ABR-215757. International Immunopharmacology. 10(8). 837–842. 6 indexed citations
9.
Björk, Per, Anders Björk, Thomas Vogl, et al.. (2009). Identification of Human S100A9 as a Novel Target for Treatment of Autoimmune Disease via Binding to Quinoline-3-Carboxamides. PLoS Biology. 7(4). e1000097–e1000097. 270 indexed citations
10.
Rolf, Julia, Martin Stenström, Emma Smith, et al.. (2008). Molecular profiling reveals distinct functional attributes of CD1d-restricted natural killer (NK) T cell subsets. Molecular Immunology. 45(9). 2607–2620. 33 indexed citations
11.
Stenström, Martin, Markus Sköld, Åsa Andersson, & Susanna Cardell. (2005). Natural killer T‐cell populations in C57BL/6 and NK1.1 congenic BALB.NK mice—a novel thymic subset defined in BALB.NK mice. Immunology. 114(3). 336–345. 17 indexed citations
12.
Borg, Jörgen, Pernilla Nevsten, Reine Wallenberg, et al.. (2004). Amino-terminal anchored surface display in insect cells and budded baculovirus using the amino-terminal end of neuraminidase. Journal of Biotechnology. 114(1-2). 21–30. 28 indexed citations
13.
Duarte, Nádia, Martin Stenström, Susana Campino, et al.. (2004). Prevention of Diabetes in Nonobese Diabetic Mice Mediated by CD1d-Restricted Nonclassical NKT Cells. The Journal of Immunology. 173(5). 3112–3118. 87 indexed citations
14.
Sköld, Markus, Martin Stenström, Stéphane Sidobre, et al.. (2003). MHC‐dependent and ‐independent modulation of endogenous Ly49 receptors on NK1.1+ T lymphocytes directed by T‐cell receptor type. Immunology. 110(3). 313–321. 18 indexed citations
15.
Stenström, Martin, Markus Sköld, Anna Ericsson, et al.. (2003). Surface receptors identify mouse NK1.1+ T cell subsets distinguished by function and T cell receptor type. European Journal of Immunology. 34(1). 56–65. 36 indexed citations
16.
Emtestam, Lennart, Ingrid Nicander, Martin Stenström, & Stig Ollmar. (1998). Electrical Impedance of Nodular Basal Cell Carcinoma: A Pilot Study. Dermatology. 197(4). 313–316. 37 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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