Marina Siebert

49 papers receiving 571 citations

Peers

Marina Siebert
Comparison fields: 5 of 80
  • Physiology 236
  • Cell Biology 134
  • Neurology 109
  • Cellular and Molecular Neuroscience 118
  • Neurology 50
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F Stivala Italy
Silvia Casagrande Italy
Davide Tonduti Italy
Josef Ekstein United States
Reza Maroofian United Kingdom
Karen Gorse United States
Xing‐Li Meng United States
Argirios Dinopoulos Greece
Moeenaldeen AlSayed Saudi Arabia
Imen Dorboz France
Marina Siebert relative to F Stivala Italy F Stivala's profile →
Citations per field
00.5×9.3×
F Stivala · 1×
Citations per year

Countries citing papers authored by Marina Siebert

Since Specialization
Citations

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

Fields of papers citing papers by Marina Siebert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Marina Siebert, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Marina Siebert Line = papers co-authored together Marina Siebert links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 51 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014112
2 199567
3 201435
4 201734
5 201528
6 202124
7 202022
8 201920
9 201217
10 201915
11 201115
12 201914
13 201613
14 201913
15 201712
16 202011
17 201711
18 201911
19 201611
20 20219

About Marina Siebert

Marina Siebert is a scholar working on Physiology, Molecular Biology, Cell Biology, Rheumatology and Cellular and Molecular Neuroscience, having authored 51 papers that have together received 581 indexed citations. Recurring topics across this work include Lysosomal Storage Disorders Research (19 papers), Cellular transport and secretion (10 papers), Carbohydrate Chemistry and Synthesis (7 papers), Glycosylation and Glycoproteins Research (5 papers), Parkinson's Disease Mechanisms and Treatments (4 papers), Neurological diseases and metabolism (4 papers), Glycogen Storage Diseases and Myoclonus (4 papers) and Hereditary Neurological Disorders (3 papers). The work is most often cited by research in Physiology (236 citations), Cell Biology (134 citations), Neurology (109 citations), Cellular and Molecular Neuroscience (118 citations) and Neurology (50 citations). Marina Siebert has collaborated with scholars based in Brazil, United States and Germany. Frequent co-authors include Wendy Westbroek, Ellen Sidransky, Maria Luiza Saraiva Pereira, Úrsula da Silveira Matte, Ida Vanessa Döederlein Schwartz, Filippo Pinto e Vairo, Jonas Alex Morales Saute, Roberto Giugliani, Odirlei André Monticielo and Andrese Aline Gasparin. Their work appears in journals such as Oral Diseases, Gene, Molecular Genetics and Metabolism, Clinical Genetics and Frontiers in Psychiatry.

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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