Stefanie Scheid

14 papers receiving 344 citations

Peers

Stefanie Scheid
Comparison fields: 5 of 61
  • Otorhinolaryngology 13
  • Statistics and Probability 26
  • Molecular Biology 201
  • Aging 5
  • Hematology 22
Replace Danielle Joseph with:
Danielle Joseph France
Sean McGee United States
Jacqueline J. Tao United States
Robert Wappel United States
Shaun Ghanny Canada
Aparna Chhibber United States
Hiroshi Kumimoto Japan
Jana M. Braunger Germany
José Luis Marín‐Rubio United Kingdom
Tae Sung United States
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Citations per field
00.5×1.5×2×2.5×
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Citations per year

Countries citing papers authored by Stefanie Scheid

Since Specialization
Citations

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

Fields of papers citing papers by Stefanie Scheid

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 200372
2 200655
3 200646
4 200435
5 200534
6 200732
7 200429
8 200917
9 200516
10 20066
11 20074
12
A false discovery rate approach to separate the score distributions of induced and non-induced genes
20033
13
The generalized lognormal distribution as an income distribution
20031
14 20071
15 20250
16 20050
17 20050

About Stefanie Scheid

Stefanie Scheid is a scholar working on Molecular Biology, Statistics and Probability, Pulmonary and Respiratory Medicine, Cardiology and Cardiovascular Medicine and Sociology and Political Science, having authored 17 papers that have together received 351 indexed citations. Recurring topics across this work include Gene expression and cancer classification (6 papers), Statistical Methods in Clinical Trials (3 papers), Bioinformatics and Genomic Networks (2 papers), Nitric Oxide and Endothelin Effects (1 paper), Cancer Genomics and Diagnostics (1 paper), T-cell and B-cell Immunology (1 paper), Income, Poverty, and Inequality (1 paper) and Economic theories and models (1 paper). The work is most often cited by research in Otorhinolaryngology (13 citations), Statistics and Probability (26 citations), Molecular Biology (201 citations), Aging (5 citations) and Hematology (22 citations). Stefanie Scheid has collaborated with scholars based in Germany, China and Hungary. Frequent co-authors include Rainer Spang, Xinan Yang, Claudio Lottaz, Stefan Bentink, Mario Drungowski, Rolf Thermann, Henning Witt, Steffen Hennig, Andreas Perrot and Dirk Klingbiel. Their work appears in journals such as Bioinformatics, Experimental Dermatology, Computer applications in the biosciences, IEEE/ACM Transactions on Computational Biology and Bioinformatics and Leukemia.

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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