Fredrik Levander

4.8k total citations · 1 hit paper
96 papers, 3.2k citations indexed

About

Fredrik Levander is a scholar working on Molecular Biology, Spectroscopy and Plant Science. According to data from OpenAlex, Fredrik Levander has authored 96 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Molecular Biology, 41 papers in Spectroscopy and 19 papers in Plant Science. Recurrent topics in Fredrik Levander's work include Advanced Proteomics Techniques and Applications (39 papers), Metabolomics and Mass Spectrometry Studies (19 papers) and Mass Spectrometry Techniques and Applications (19 papers). Fredrik Levander is often cited by papers focused on Advanced Proteomics Techniques and Applications (39 papers), Metabolomics and Mass Spectrometry Studies (19 papers) and Mass Spectrometry Techniques and Applications (19 papers). Fredrik Levander collaborates with scholars based in Sweden, United Kingdom and Italy. Fredrik Levander's co-authors include Aakash Chawade, Peter Rådström, Erik Alexandersson, Marianne Sandin, Peter James, Erik Andréasson, Johan Malmström, Johan Teleman, Svante Resjö and Eric W. Deutsch and has published in prestigious journals such as Science, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Fredrik Levander

90 papers receiving 3.1k citations

Hit Papers

mzML—a Community Standard for Mass Spectrometry Data 2010 2026 2015 2020 2010 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
Fredrik Levander Sweden 31 1.9k 1.1k 612 338 189 96 3.2k
Christina Ludwig Germany 27 2.4k 1.2× 953 0.9× 314 0.5× 155 0.5× 88 0.5× 94 3.4k
Hélian Boucherie France 23 2.7k 1.4× 731 0.7× 442 0.7× 296 0.9× 73 0.4× 49 3.5k
Simona Arena Italy 32 1.4k 0.7× 273 0.2× 685 1.1× 445 1.3× 194 1.0× 72 2.5k
Conrad Bessant United Kingdom 32 1.8k 0.9× 985 0.9× 371 0.6× 130 0.4× 274 1.4× 87 3.4k
Nicholas Shulman United States 14 3.1k 1.6× 1.5k 1.3× 241 0.4× 122 0.4× 78 0.4× 21 4.6k
Hannes Hahne Germany 25 2.5k 1.3× 842 0.8× 117 0.2× 253 0.7× 142 0.8× 48 3.5k
José A. Dianes United Kingdom 8 3.2k 1.7× 1000 0.9× 494 0.8× 104 0.3× 94 0.5× 11 5.0k
Charles Ansong United States 33 2.0k 1.0× 1.0k 1.0× 199 0.3× 169 0.5× 46 0.2× 85 3.4k
Monique Slijper Netherlands 35 2.5k 1.3× 752 0.7× 468 0.8× 102 0.3× 36 0.2× 54 3.5k
Antonio Malorni Italy 28 1.3k 0.7× 494 0.4× 143 0.2× 483 1.4× 95 0.5× 94 2.4k

Countries citing papers authored by Fredrik Levander

Since Specialization
Citations

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

Fields of papers citing papers by Fredrik Levander

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fredrik Levander

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

All Works

20 of 20 papers shown
1.
Rönnerman, Elisabeth Werner, Pernilla Dahm‐Kähler, Per Karlsson, et al.. (2025). Unveiling histotype-specific biomarkers in ovarian carcinoma using proteomics. PubMed. 33(3). 201019–201019. 1 indexed citations
3.
Levander, Fredrik, et al.. (2024). LRPPRC and SLIRP synergize to maintain sufficient and orderly mammalian mitochondrial translation. Nucleic Acids Research. 52(18). 11266–11282. 5 indexed citations
4.
Siino, Valentina, et al.. (2023). Quantification of proteomic profile changes in the hemolymph of crayfish during in vitro coagulation. Developmental & Comparative Immunology. 147. 104760–104760. 5 indexed citations
5.
Tran, Huy Cuong, Katja Bernfur, Kasim Khan, et al.. (2023). An mTRAN-mRNA interaction mediates mitochondrial translation initiation in plants. Science. 381(6661). eadg0995–eadg0995. 10 indexed citations
6.
Bouyssié, David, Salvador Capella-Gutiérrez, José M. Fernández, et al.. (2023). WOMBAT-P: Benchmarking Label-Free Proteomics Data Analysis Workflows. Journal of Proteome Research. 23(1). 418–429.
7.
Ávila, Renato Ivan de, et al.. (2023). A proteomics dataset capturing myeloid cell responses upon cellular exposure to fungicides, adjuvants and fungicide formulations. Data in Brief. 46. 108878–108878. 1 indexed citations
8.
Ashraf, Muhammad, Kanakachari Mogilicherla, Gothandapani Sellamuthu, et al.. (2023). Comparative gut proteomics study revealing adaptive physiology of Eurasian spruce bark beetle, Ips typographus (Coleoptera: Scolytinae). Frontiers in Plant Science. 14. 1157455–1157455. 7 indexed citations
9.
Siino, Valentina, Ashfaq Ali, Giulia Accardi, et al.. (2022). Plasma proteome profiling of healthy individuals across the life span in a Sicilian cohort with long‐lived individuals. Aging Cell. 21(9). e13684–e13684. 12 indexed citations
10.
Ávila, Renato Ivan de, et al.. (2022). Adjuvants in fungicide formulations can be skin sensitizers and cause different types of cell stress responses. Toxicology Reports. 9. 2030–2041. 7 indexed citations
11.
Masoumi, Katarzyna Chmielarska, Wondossen Sime, Valentina Siino, et al.. (2016). NLK-mediated phosphorylation of HDAC1 negatively regulates Wnt signaling. Molecular Biology of the Cell. 28(2). 346–355. 22 indexed citations
12.
Hosseini, Sara, Svante Resjö, Yongfeng Liu, et al.. (2015). Comparative proteomic analysis of hyphae and germinating cysts of Phytophthora pisi and Phytophthora sojae. Journal of Proteomics. 117. 24–40. 14 indexed citations
13.
Sandin, Marianne, Ashfaq Ali, Karin Hansson, et al.. (2013). An Adaptive Alignment Algorithm for Quality-controlled Label-free LC-MS. Molecular & Cellular Proteomics. 12(5). 1407–1420. 30 indexed citations
14.
Sandin, Marianne, Morten Krogh, Karin Hansson, & Fredrik Levander. (2011). Generic workflow for quality assessment of quantitative label‐free LC‐MS analysis. PROTEOMICS. 11(6). 1114–1124. 27 indexed citations
15.
Cappadona, Salvatore, Paolo Nanni, Marco Benevento, et al.. (2010). Improved Label-Free LC-MS Analysis by Wavelet-Based Noise Rejection. SHILAP Revista de lepidopterología. 2010. 1–9. 54 indexed citations
16.
Eisenacher, Martin, Michael Kohl, Lennart Martens, et al.. (2008). Proteomics Data Collection – 4th ProDaC Workshop 15 August 2008, Amsterdam, The Netherlands. PROTEOMICS. 9(2). 218–222. 2 indexed citations
17.
Cappadona, Salvatore, et al.. (2008). Wavelet-Based Method for Noise Characterization and Rejection in High-Performance Liquid Chromatography Coupled to Mass Spectrometry. Analytical Chemistry. 80(13). 4960–4968. 36 indexed citations
18.
Levander, Fredrik, et al.. (2007). Automated reporting from gel‐based proteomics experiments using the open source Proteios database application. PROTEOMICS. 7(5). 668–674. 26 indexed citations
19.
Eisenacher, Martin, Tanja Hardt, Michael Hamacher, et al.. (2007). Proteomics Data Collection – The 1st ProDaC workshop 26 April 2007 Ecole Normale Supérieur, Lyon, France. PROTEOMICS. 7(17). 3034–3037. 5 indexed citations
20.
Dalevi, Daniel, et al.. (2004). Modular, scriptable and automated analysis tools for high-throughput peptide mass fingerprinting. Bioinformatics. 20(18). 3628–3635. 64 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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