Shona Pedersen

5.0k total citations · 1 hit paper
95 papers, 2.4k citations indexed

About

Shona Pedersen is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Shona Pedersen has authored 95 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Molecular Biology, 17 papers in Pulmonary and Respiratory Medicine and 14 papers in Oncology. Recurrent topics in Shona Pedersen's work include Extracellular vesicles in disease (16 papers), Metabolomics and Mass Spectrometry Studies (8 papers) and Blood Coagulation and Thrombosis Mechanisms (8 papers). Shona Pedersen is often cited by papers focused on Extracellular vesicles in disease (16 papers), Metabolomics and Mass Spectrometry Studies (8 papers) and Blood Coagulation and Thrombosis Mechanisms (8 papers). Shona Pedersen collaborates with scholars based in Denmark, Qatar and United States. Shona Pedersen's co-authors include Peter J. Barnes, Søren Risom Kristensen, Lars Ernster, Rune Hedman, Erik Arrhenius, Olle R. Lindberg, JR Tata, Rikke Bæk, Maléne Møller Jørgensen and Evo Kristina Lindersson Søndergaard and has published in prestigious journals such as SHILAP Revista de lepidopterología, Blood and PLoS ONE.

In The Last Decade

Shona Pedersen

88 papers receiving 2.3k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The action of thyroid hormones at the cell level

1963 435 citations Shona Pedersen et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shona Pedersen Denmark	23	1.2k	555	366	361	227	95	2.4k
Hye‐Jin Kim South Korea	33	1.0k 0.9×	264 0.5×	210 0.6×	374 1.0×	229 1.0×	162	3.2k
Daniel Monleón Spain	34	1.7k 1.5×	466 0.8×	325 0.9×	134 0.4×	180 0.8×	110	3.3k
Catherine Guettier France	47	1.1k 1.0×	511 0.9×	546 1.5×	762 2.1×	250 1.1×	240	7.3k
Spiros D. Garbis United Kingdom	31	1.7k 1.4×	487 0.9×	377 1.0×	197 0.5×	87 0.4×	81	3.4k
Robin Farias‐Eisner United States	34	1.5k 1.3×	347 0.6×	878 2.4×	259 0.7×	226 1.0×	69	3.8k
Kaori Suzuki Japan	31	1.9k 1.6×	354 0.6×	325 0.9×	300 0.8×	241 1.1×	102	4.0k
Matthias Meier Germany	38	1.7k 1.4×	410 0.7×	189 0.5×	465 1.3×	447 2.0×	136	4.4k
Annette Feuchtinger Germany	32	1.3k 1.2×	234 0.4×	368 1.0×	369 1.0×	218 1.0×	121	3.0k
Petr Beneš Czechia	26	1.8k 1.6×	279 0.5×	350 1.0×	192 0.5×	178 0.8×	110	3.4k
Gianpiero Pescarmona Italy	41	1.9k 1.6×	838 1.5×	444 1.2×	294 0.8×	174 0.8×	135	4.6k

Countries citing papers authored by Shona Pedersen

Since Specialization

Citations

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

Fields of papers citing papers by Shona Pedersen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shona Pedersen

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

All Works

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20 of 20 papers shown

Shaito, Abdullah, et al.. (2025). Anti-amyloid monoclonal antibody therapies in Alzheimer’s disease – a scoping review. Neuroscience. 589. 50–61. 1 indexed citations

Chowdhury, Muhammad E. H., et al.. (2025). Artificial Intelligence and Machine Learning in Lung Cancer: Advances in Imaging, Detection, and Prognosis. Cancers. 17(24). 3985–3985.

Burgon, Patrick G., et al.. (2025). Apolipoprotein A (ApoA) in Neurological Disorders: Connections and Insights. International Journal of Molecular Sciences. 26(16). 7908–7908. 1 indexed citations

Andreassen, Trygve, Charlotte H. Gotfredsen, Dorte Aalund Olsen, et al.. (2024). Serum metabolic signatures for Alzheimer’s Disease reveal alterations in amino acid composition: a validation study. Metabolomics. 20(1). 7 indexed citations

Djouhri, Laiche, et al.. (2024). Proteomic Analysis of Prehypertensive and Hypertensive Patients: Exploring the Role of the Actin Cytoskeleton. International Journal of Molecular Sciences. 25(9). 4896–4896. 2 indexed citations

Pedersen, Shona, et al.. (2024). Unraveling the proteomic signatures of coronary artery disease and hypercholesterolemia. SHILAP Revista de lepidopterología. 25(6). 1280–1292. 1 indexed citations

Pedersen, Shona, et al.. (2024). MLIP and Its Potential Influence on Key Oncogenic Pathways. Cells. 13(13). 1109–1109.

Mortensen, Joachim Høg, Trygve Andreassen, Dorte Aalund Olsen, et al.. (2024). Serum Lipoprotein Profiling by NMR Spectroscopy Reveals Alterations in HDL-1 and HDL-2 Apo-A2 Subfractions in Alzheimer’s Disease. International Journal of Molecular Sciences. 25(21). 11701–11701.

Vranić, Semir, et al.. (2024). Innovative Deep Learning Architecture for the Classification of Lung and Colon Cancer From Histopathology Images. Applied Computational Intelligence and Soft Computing. 2024(1). 2 indexed citations

10.

Vranić, Semir, et al.. (2023). Proteomic Profiling of Small-Cell Lung Cancer: A Systematic Review. Cancers. 15(20). 5005–5005. 4 indexed citations

11.

Faisal, Md. Ahasan Atick, Muhammad E. H. Chowdhury, Zaid Bin Mahbub, et al.. (2023). NDDNet: a deep learning model for predicting neurodegenerative diseases from gait pattern. Applied Intelligence. 53(17). 20034–20046. 15 indexed citations

12.

Chowdhury, Muhammad E. H., Nasser Al‐Emadi, Huseyin C. Yalcin, et al.. (2023). A novel deep learning technique for morphology preserved fetal ECG extraction from mother ECG using 1D-CycleGAN. Expert Systems with Applications. 235. 121196–121196. 22 indexed citations

13.

Pedersen, Shona, et al.. (2023). Serum NMR-Based Metabolomics Profiling Identifies Lipoprotein Subfraction Variables and Amino Acid Reshuffling in Myeloma Development and Progression. International Journal of Molecular Sciences. 24(15). 12275–12275. 1 indexed citations

14.

Kristensen, Søren Risom, et al.. (2022). Thrombin generation measured on ST Genesia, a new platform in the coagulation routine lab: Assessment of analytical and between‐subject variation. Research and Practice in Thrombosis and Haemostasis. 6(1). e12654–e12654. 13 indexed citations

15.

Pedersen, Shona, et al.. (2021). Identifying metabolic alterations in newly diagnosed small cell lung cancer patients. SHILAP Revista de lepidopterología. 12. 100127–100127. 12 indexed citations

16.

Kristensen, Søren Risom, et al.. (2020). The effect of pH on thrombin generation–An unrecognized potential source of variation. Research and Practice in Thrombosis and Haemostasis. 4(2). 224–229. 4 indexed citations

17.

Kristensen, Søren Risom, et al.. (2020). Reply to a letter from Jackson J et al: Effect of pH on thrombin activity measured by calibrated automated thrombinography. Research and Practice in Thrombosis and Haemostasis. 4(6). 1065–1065. 1 indexed citations

18.

Chandran, Vineesh Indira, Charlotte Welinder, Ann‐Sofie Månsson, et al.. (2019). Ultrasensitive Immunoprofiling of Plasma Extracellular Vesicles Identifies Syndecan-1 as a Potential Tool for Minimally Invasive Diagnosis of Glioma. Clinical Cancer Research. 25(10). 3115–3127. 81 indexed citations

19.

Pedersen, Shona, et al.. (2018). Investigation of procoagulant activity in extracellular vesicles isolated by differential ultracentrifugation. Journal of Extracellular Vesicles. 7(1). 1454777–1454777. 54 indexed citations

20.

Pedersen, Shona, Gunilla Hedlin, Eugenio Baraldi, et al.. (2011). Pharmacological treatment of severe, therapy-resistant asthma in children: what can we learn from where?. European Respiratory Journal. 38(4). 947–958. 33 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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