Ina Vorberg

2.8k total citations
60 papers, 1.9k citations indexed

About

Ina Vorberg is a scholar working on Molecular Biology, Neurology and Nutrition and Dietetics. According to data from OpenAlex, Ina Vorberg has authored 60 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Molecular Biology, 29 papers in Neurology and 20 papers in Nutrition and Dietetics. Recurrent topics in Ina Vorberg's work include Prion Diseases and Protein Misfolding (54 papers), Neurological diseases and metabolism (29 papers) and Trace Elements in Health (20 papers). Ina Vorberg is often cited by papers focused on Prion Diseases and Protein Misfolding (54 papers), Neurological diseases and metabolism (29 papers) and Trace Elements in Health (20 papers). Ina Vorberg collaborates with scholars based in Germany, United States and Canada. Ina Vorberg's co-authors include Suzette A. Priola, Hermann Schätzl, Martin H. Groschup, A Raines, Eberhard Pfaff, Carmen Nussbaum‐Krammer, Shu Liu, Sabine Gilch, Julia Hofmann and Roger A. Moore and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Lancet and Journal of Biological Chemistry.

In The Last Decade

Ina Vorberg

60 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ina Vorberg Germany 29 1.7k 662 515 353 149 60 1.9k
Samantha L. Eaton United Kingdom 19 1.3k 0.8× 328 0.5× 290 0.6× 260 0.7× 111 0.7× 42 1.7k
Sabine Gilch Canada 27 2.3k 1.3× 837 1.3× 720 1.4× 369 1.0× 129 0.9× 75 2.7k
Victoria Lewis Australia 23 1.6k 0.9× 423 0.6× 285 0.6× 293 0.8× 90 0.6× 65 2.0k
David W. Colby United States 21 2.2k 1.3× 636 1.0× 392 0.8× 672 1.9× 237 1.6× 23 2.6k
Richard J. Kascsak United States 29 2.4k 1.4× 1.1k 1.7× 911 1.8× 601 1.7× 159 1.1× 56 2.8k
Ollivier Milhavet France 22 1.8k 1.1× 452 0.7× 352 0.7× 389 1.1× 90 0.6× 33 2.3k
Regina Kascsak United States 27 2.5k 1.4× 1.1k 1.7× 1.0k 2.0× 351 1.0× 247 1.7× 40 2.8k
Ryuichiro Atarashi Japan 26 2.5k 1.5× 1.2k 1.9× 733 1.4× 496 1.4× 436 2.9× 63 2.9k
Vincent Béringue France 31 3.7k 2.2× 1.7k 2.6× 1.2k 2.3× 357 1.0× 176 1.2× 113 4.0k
Hermann C. Altmeppen Germany 23 1.1k 0.6× 527 0.8× 224 0.4× 477 1.4× 171 1.1× 53 1.6k

Countries citing papers authored by Ina Vorberg

Since Specialization
Citations

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

Fields of papers citing papers by Ina Vorberg

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ina Vorberg

This figure shows the co-authorship network connecting the top 25 collaborators of Ina Vorberg. A scholar is included among the top collaborators of Ina Vorberg 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 Ina Vorberg. Ina Vorberg 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.
Liu, Shu, et al.. (2023). Reactivated endogenous retroviruses promote protein aggregate spreading. Nature Communications. 14(1). 5034–5034. 20 indexed citations
2.
Opakua, Alain Ibáñez de, et al.. (2023). Acetylation discriminates disease-specific tau deposition. Nature Communications. 14(1). 5919–5919. 21 indexed citations
3.
Liu, Shu, Katerina Konstantoulea, Stephan A. Müller, et al.. (2021). Highly efficient intercellular spreading of protein misfolding mediated by viral ligand-receptor interactions. Nature Communications. 12(1). 5739–5739. 53 indexed citations
4.
Buschle, Alexander, Xia Wu, Stefan Krebs, et al.. (2021). Human ORC/MCM density is low in active genes and correlates with replication time but does not delimit initiation zones. eLife. 10. 25 indexed citations
5.
Michiels, Emiel, Shu Liu, Rodrigo Gallardo, et al.. (2020). Entropic Bristles Tune the Seeding Efficiency of Prion-Nucleating Fragments. Cell Reports. 30(8). 2834–2845.e3. 10 indexed citations
6.
Arndt, Verena, Benedetta Bolognesi, Shu Liu, et al.. (2019). Fibril-induced glutamine-/asparagine-rich prions recruit stress granule proteins in mammalian cells. Life Science Alliance. 2(4). e201800280–e201800280. 7 indexed citations
7.
Broemer, Meike, Ilian Atanassov, Ina Vorberg, et al.. (2019). Deregulated Splicing Is a Major Mechanism of RNA-Induced Toxicity in Huntington's Disease. Journal of Molecular Biology. 431(9). 1869–1877. 59 indexed citations
8.
Romanyuk, Andrey, Julia V. Sopova, Aleksandr A. Rubel, et al.. (2018). Mammalian amyloidogenic proteins promote prion nucleation in yeast. Journal of Biological Chemistry. 293(9). 3436–3450. 23 indexed citations
9.
10.
Bester, Romina, et al.. (2017). Prion strains depend on different endocytic routes for productive infection. Scientific Reports. 7(1). 6923–6923. 30 indexed citations
11.
12.
Hafner‐Bratkovič, Iva, Romina Bester, Primož Pristovšek, et al.. (2011). Globular Domain of the Prion Protein Needs to Be Unlocked by Domain Swapping to Support Prion Protein Conversion. Journal of Biological Chemistry. 286(14). 12149–12156. 75 indexed citations
13.
Nunziante, Max, Kerstin Ackermann, Kim N. Dietrich, et al.. (2011). Proteasomal Dysfunction and Endoplasmic Reticulum Stress Enhance Trafficking of Prion Protein Aggregates through the Secretory Pathway and Increase Accumulation of Pathologic Prion Protein. Journal of Biological Chemistry. 286(39). 33942–33953. 42 indexed citations
14.
Bach, Christian, Sabine Gilch, Alex D. Greenwood, et al.. (2009). Prion-induced Activation of Cholesterogenic Gene Expression by Srebp2 in Neuronal Cells. Journal of Biological Chemistry. 284(45). 31260–31269. 32 indexed citations
15.
Gilch, Sabine, et al.. (2009). Inhibition of cholesterol recycling impairs cellular PrPSc propagation. Cellular and Molecular Life Sciences. 66(24). 3979–3991. 34 indexed citations
16.
Caetano, Fabiana A., Marilene H. Lopes, Glaucia N. M. Hajj, et al.. (2008). Endocytosis of Prion Protein Is Required for ERK1/2 Signaling Induced by Stress-Inducible Protein 1. Journal of Neuroscience. 28(26). 6691–6702. 84 indexed citations
17.
Nussbaum‐Krammer, Carmen, Elisabeth Kremmer, Hermann Schätzl, & Ina Vorberg. (2008). Dynamic interactions of Sup35p and PrP prion protein domains modulate aggregate nucleation and seeding. Prion. 2(3). 99–106. 10 indexed citations
18.
Stengel, Anna, Christian Bach, Ina Vorberg, et al.. (2006). Prion infection influences murine endogenous retrovirus expression in neuronal cells. Biochemical and Biophysical Research Communications. 343(3). 825–831. 12 indexed citations
19.
Vorberg, Ina & Suzette A. Priola. (2002). Molecular Basis of Scrapie Strain Glycoform Variation. Journal of Biological Chemistry. 277(39). 36775–36781. 63 indexed citations
20.
Vorberg, Ina, A. Buschmann, Silke S. Harmeyer, et al.. (1999). A Novel Epitope for the Specific Detection of Exogenous Prion Proteins in Transgenic Mice and Transfected Murine Cell Lines. Virology. 255(1). 26–31. 41 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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