Xenia Schafer

2.0k citations
21 papers · 1.5k indexed · 1 hit paper · h-index 14

Xenia Schafer

20 papers receiving 1.5k citations

Hit Papers

Dissecting self-renewal in stem cells with RNA interference7572006202620122019250500750

Peers

Xenia Schafer
Comparison fields: 5 of 96
  • Cancer Research 258
  • Molecular Biology 1.1k
  • Virology 38
  • Immunology 166
  • Physiology 34
Replace Richard T. Timms with:
Richard T. Timms United Kingdom
Guinevere L. Grice United Kingdom
Lina Herhaus Germany
Graciana Diez‐Roux Italy
Elisabeth Kowenz‐Leutz Germany
Rebecca Dunn United States
Thomas Slagsvold Norway
Jong Heon Kim South Korea
Somdutta Dhir United Kingdom
Martin Schlumpberger Germany
Xenia Schafer relative to Richard T. Timms United Kingdom Richard T. Timms's profile →
Citations per field
00.5×1.5×1.8×
Richard T. Timms · 1×
Citations per year

Countries citing papers authored by Xenia Schafer

Since Specialization
Citations

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

Fields of papers citing papers by Xenia Schafer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Xenia Schafer, 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 Xenia Schafer Line = papers co-authored together Xenia Schafer links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20243
3 20231
4 20226
5 202126
6 202010
7 201947
8 201916
9 201713
10 2016116
11 2016118
12 201541
13 201453
14 20131
15 201195
16 201078
17 200863
18 200820
19 200618
20
Dissecting self-renewal in stem cells with RNA interferencebreakdown →
2006757

About Xenia Schafer

Xenia Schafer is a scholar working on Virology, Clinical Biochemistry and Geriatrics and Gerontology, having authored 21 papers that have together received 1.5k indexed citations. Recurring topics across this work include Cytomegalovirus and herpesvirus research (9 papers), Cancer, Hypoxia, and Metabolism (5 papers), Metabolism and Genetic Disorders (4 papers), HIV Research and Treatment (3 papers), interferon and immune responses (2 papers), Virus-based gene therapy research (2 papers), Mitochondrial Function and Pathology (2 papers) and Sirtuins and Resveratrol in Medicine (2 papers). The work is most often cited by research in Cancer Research (258 citations), Molecular Biology (1.1k citations) and Virology (38 citations). Xenia Schafer has collaborated with scholars based in United States, Germany and France. Frequent co-authors include Joshua Munger, Ihor R. Lemischka, Radu Dobrin, Rong Lu, Natalia Ivanova, John M. Levorse, Christina J. DeCoste, Iulia Kotenko, Cody M. Spencer and Paul S. Brookes. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

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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