Sabine Sampels

82 total papers · 2.9k total citations
64 papers, 2.2k citations indexed

About

Sabine Sampels is a scholar working on Aquatic Science, Animal Science and Zoology and Molecular Biology. According to data from OpenAlex, Sabine Sampels has authored 64 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Aquatic Science, 31 papers in Animal Science and Zoology and 16 papers in Molecular Biology. Recurrent topics in Sabine Sampels's work include Aquaculture Nutrition and Growth (32 papers), Meat and Animal Product Quality (27 papers) and Fatty Acid Research and Health (14 papers). Sabine Sampels is often cited by papers focused on Aquaculture Nutrition and Growth (32 papers), Meat and Animal Product Quality (27 papers) and Fatty Acid Research and Health (14 papers). Sabine Sampels collaborates with scholars based in Sweden, Czechia and Norway. Sabine Sampels's co-authors include Sarvenaz Khalili Tilami, Jana Picková, Nils Ewald, Cecilia Lalander, Markus Langeland, Anders Kiessling, Aleksandar Vidaković, Nima Hematyar, Eva Wiklund and Jan Mráz and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Science of The Total Environment.

In The Last Decade

Sabine Sampels

63 papers receiving 2.1k citations

Hit Papers

Fatty acid composition of... 2017 2026 2020 2023 2019 2017 100 200 300

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Sabine Sampels 685 619 617 472 272 64 2.2k
Flemming Jessen 966 1.4× 648 1.0× 1.3k 2.1× 350 0.7× 356 1.3× 103 2.8k
Wenge Yang 799 1.2× 341 0.6× 603 1.0× 279 0.6× 671 2.5× 84 1.9k
Liv Torunn Mydland 573 0.8× 1.7k 2.8× 661 1.1× 227 0.5× 338 1.2× 107 3.0k
Grethe Hyldig 904 1.3× 567 0.9× 322 0.5× 92 0.2× 670 2.5× 76 1.9k
Torbjörn Lundh 366 0.5× 765 1.2× 708 1.1× 153 0.3× 305 1.1× 96 2.6k
Jan Mráz 357 0.5× 929 1.5× 277 0.4× 125 0.3× 358 1.3× 109 1.8k
Jacques Fanni 410 0.6× 343 0.6× 767 1.2× 298 0.6× 638 2.3× 48 1.9k
Alberto Brugiapaglia 982 1.4× 230 0.4× 215 0.3× 537 1.1× 256 0.9× 63 1.8k
Margarida R. G. Maia 258 0.4× 414 0.7× 337 0.5× 167 0.4× 229 0.8× 60 1.9k
Concetta María Messina 185 0.3× 494 0.8× 438 0.7× 218 0.5× 217 0.8× 78 1.7k

Countries citing papers authored by Sabine Sampels

Since Specialization
Citations

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

Fields of papers citing papers by Sabine Sampels

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sabine Sampels

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

All Works

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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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