Daniela Stauffer

1.0k citations
13 papers · 831 · h-index 12

Impact in

Papers in

Daniela Stauffer

13 papers receiving 813 citations

Peers

Daniela Stauffer
Comparison fields: 5 of 85
  • Cellular and Molecular Neuroscience 302
  • Neurology 132
  • Molecular Biology 541
  • Cell Biology 112
  • Neurology 38
Replace Yuxi Shan with:
Yuxi Shan China
Mei Kwan Canada
Mattéa J. Finelli United Kingdom
Takahiro Fujimoto Japan
Emma Kettle Australia
Jeremy W. Linsley United States
Pascal Neuville France
Ilaria Palmisano United Kingdom
M. Garrido Spain
Pengfei Lin China
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Citations per field
00.5×1.7×
Yuxi Shan · 1×
Citations per year

Countries citing papers authored by Daniela Stauffer

Since Specialization
Citations

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

Fields of papers citing papers by Daniela Stauffer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 2001271
2 2006169
3 201265
4 201654
5 200551
6 200141
7 199937
8 201333
9 201333
10 200332
11 200624
12 201519
13
Estrogen Receptor alpha (ER alpha) and Estrogen Related Receptor alpha (ERR alpha) are both transcriptional regulators of the Runx2-I isoform
20132

About Daniela Stauffer

Daniela Stauffer is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Neurology, Oncology and Genetics, having authored 13 papers that have together received 831 indexed citations. Recurring topics across this work include Parkinson's Disease Mechanisms and Treatments (4 papers), Plant Gene Expression Analysis (2 papers), Receptor Mechanisms and Signaling (2 papers), Estrogen and related hormone effects (2 papers), Peptidase Inhibition and Analysis (2 papers), Alzheimer's disease research and treatments (1 paper), Ubiquitin and proteasome pathways (1 paper) and Renal cell carcinoma treatment (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (302 citations), Neurology (132 citations), Molecular Biology (541 citations), Cell Biology (112 citations) and Neurology (38 citations). Daniela Stauffer has collaborated with scholars based in Switzerland, Italy and France. Frequent co-authors include Giorgio Rovelli, Jean‐Philippe Pin, Jaroslav Blahoš, Bruno Martoglio, Peer‐Hendrik Kuhn, Elena Friedmann, Sarah Vreugde, Stefan F. Lichtenthaler, Ehud Hauben and Simone Schleeger. Their work appears in journals such as Journal of Biological Chemistry, Gene, Bioorganic & Medicinal Chemistry Letters, Nature Cell Biology and Molecular and Cellular Endocrinology.

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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