Markus Stenemo

498 total citations
9 papers, 365 citations indexed

About

Markus Stenemo is a scholar working on Molecular Biology, Nephrology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Markus Stenemo has authored 9 papers receiving a total of 365 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 2 papers in Nephrology and 2 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Markus Stenemo's work include Metabolomics and Mass Spectrometry Studies (2 papers), Advanced Proteomics Techniques and Applications (2 papers) and Protease and Inhibitor Mechanisms (2 papers). Markus Stenemo is often cited by papers focused on Metabolomics and Mass Spectrometry Studies (2 papers), Advanced Proteomics Techniques and Applications (2 papers) and Protease and Inhibitor Mechanisms (2 papers). Markus Stenemo collaborates with scholars based in Sweden, United States and Australia. Markus Stenemo's co-authors include Lars Lind, Johan Ärnlöv, Johan Sundström, Erik Ingelsson, Tove Fall, Bertil Lindahl, Agneta Siegbahn, Emil Hagström, Vilmantas Giedraitis and Christoph Nowak and has published in prestigious journals such as Stroke, Heart and Clinical Journal of the American Society of Nephrology.

In The Last Decade

Markus Stenemo

9 papers receiving 362 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Markus Stenemo Sweden 8 150 109 63 61 49 9 365
Jessica Nigro United States 5 219 1.5× 161 1.5× 86 1.4× 50 0.8× 22 0.4× 7 455
Laura Mouriño-Álvarez Spain 13 210 1.4× 174 1.6× 41 0.7× 13 0.2× 34 0.7× 34 447
Eman A. Elghoroury Egypt 12 134 0.9× 48 0.4× 53 0.8× 17 0.3× 22 0.4× 40 409
Stéphanie Billon‐Crossouard France 12 184 1.2× 69 0.6× 93 1.5× 13 0.2× 38 0.8× 17 443
Kazutoshi Mawatari Japan 9 107 0.7× 121 1.1× 23 0.4× 13 0.2× 37 0.8× 22 346
Hong Zhi China 15 214 1.4× 127 1.2× 36 0.6× 14 0.2× 35 0.7× 34 499
Xufei Yang China 8 176 1.2× 90 0.8× 59 0.9× 28 0.5× 33 0.7× 11 368
Jane A. Dymott United Kingdom 6 193 1.3× 52 0.5× 33 0.5× 11 0.2× 21 0.4× 6 329
Lívia Corrêa Barroso Brazil 9 178 1.2× 207 1.9× 51 0.8× 49 0.8× 131 2.7× 10 512
Rita Nogueira‐Ferreira Portugal 14 177 1.2× 179 1.6× 95 1.5× 15 0.2× 28 0.6× 33 515

Countries citing papers authored by Markus Stenemo

Since Specialization
Citations

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

Fields of papers citing papers by Markus Stenemo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Markus Stenemo

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

All Works

9 of 9 papers shown
1.
Suur, Bianca E, Melody Chemaly, Moritz Lindquist Liljeqvist, et al.. (2022). Therapeutic potential of the Proprotein Convertase Subtilisin/Kexin family in vascular disease. Frontiers in Pharmacology. 13. 988561–988561. 9 indexed citations
2.
Stenemo, Markus, Andrea Ganna, Samira Salihović, et al.. (2019). The Metabolites Urobilin and Sphingomyelin (30:1) are Associated with Incident Heart Failure in the General Population. ESC Heart Failure. 6(4). 764–773. 29 indexed citations
3.
Stenemo, Markus, Christoph Nowak, Liisa Byberg, et al.. (2017). Circulating Proteins as Predictors of Incident Heart Failure in the Elderly. European Journal of Heart Failure. 20(1). 55–62. 76 indexed citations
4.
Carlsson, Axel C., Erik Ingelsson, Johan Sundström, et al.. (2017). Use of Proteomics To Investigate Kidney Function Decline over 5 Years. Clinical Journal of the American Society of Nephrology. 12(8). 1226–1235. 45 indexed citations
5.
Lind, Lars, Johan Sundström, Markus Stenemo, Emil Hagström, & Johan Ärnlöv. (2016). Discovery of new biomarkers for atrial fibrillation using a custom-made proteomics chip. Heart. 103(5). 377–382. 56 indexed citations
6.
Stenemo, Markus, Johan Teleman, Martin Sjöström, et al.. (2016). Cancer associated proteins in blood plasma: Determining normal variation. PROTEOMICS. 16(13). 1928–1937. 6 indexed citations
7.
Carlsson, Axel C., Johan Sundström, Juan Jesús Carrero, et al.. (2016). Use of a proximity extension assay proteomics chip to discover new biomarkers associated with albuminuria. European Journal of Preventive Cardiology. 24(4). 340–348. 14 indexed citations
8.
Lind, Lars, Agneta Siegbahn, Bertil Lindahl, et al.. (2015). Discovery of New Risk Markers for Ischemic Stroke Using a Novel Targeted Proteomics Chip. Stroke. 46(12). 3340–3347. 75 indexed citations
9.
Ganna, Andrea, Tove Fall, Samira Salihović, et al.. (2015). Large-scale non-targeted metabolomic profiling in three human population-based studies. Metabolomics. 12(1). 55 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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