Marius Wunderle

698 citations
16 papers · 314 · h-index 10

Impact in

Papers in

    • BRCA gene mutations in cancer 6
    • Nutrition, Genetics, and Disease 1
    • Cancer Genomics and Diagnostics 2
    • Breast Cancer Treatment Studies 2

Marius Wunderle

14 papers receiving 312 citations

Peers

Marius Wunderle
Comparison fields: 5 of 77
  • Health Informatics 7
  • Clinical Biochemistry 34
  • Cancer Research 54
  • Genetics 92
  • Pathology and Forensic Medicine 35
Replace Kaoru Nakano with:
Kaoru Nakano Japan
Chi‐Juei Jeng Taiwan
Colin P. Bergstrom United States
Debora M.I. Fersching Germany
Barbara Siegele Germany
Min Sun China
Yoshinari Takemoto Japan
Kyewon Park United States
Chunyue Feng China
Marius Wunderle relative to Kaoru Nakano Japan Kaoru Nakano's profile →
Citations per field
00.5×4.9×
Kaoru Nakano · 1×
Citations per year

Countries citing papers authored by Marius Wunderle

Since Specialization
Citations

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

Fields of papers citing papers by Marius Wunderle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 201686
2 201350
3 201843
4 201829
5 201721
6 202018
7 201712
8 201812
9 202012
10 202011
11 20197
12 20176
13 20205
14 20232
15 20190
16 20150

About Marius Wunderle

Marius Wunderle is a scholar working on Genetics, Cancer Research, Molecular Biology, Occupational Therapy and Pathology and Forensic Medicine, having authored 16 papers that have together received 314 indexed citations. Recurring topics across this work include BRCA gene mutations in cancer (6 papers), DNA Repair Mechanisms (2 papers), Cancer Genomics and Diagnostics (2 papers), Breast Cancer Treatment Studies (2 papers), Nutrition, Genetics, and Disease (1 paper), Wound Healing and Treatments (1 paper), Machine Learning in Healthcare (1 paper) and Pressure Ulcer Prevention and Management (1 paper). The work is most often cited by research in Health Informatics (7 citations), Clinical Biochemistry (34 citations), Cancer Research (54 citations), Genetics (92 citations) and Pathology and Forensic Medicine (35 citations). Marius Wunderle has collaborated with scholars based in Germany, Hungary and Iran. Frequent co-authors include Peter A. Fasching, Matthias W. Beckmann, André Reis, Juliane Hoyer, Michael P. Lux, Yinchong Yang, Volker Tresp, Georgia Vasileiou, Cornelia Kraus and Steffen Uebe. Their work appears in journals such as Medical Physics, Scientific Reports, BMC Cancer, Current Issues in Molecular Biology and The Breast.

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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