Mario Beilmann

21 papers receiving 615 citations

Mario Beilmann's Hit Papers

The evolving role of investigative toxicology in the pharmaceutical industry 2023 · 132 citations
1320+1+2Years since publication4080120

Peers

Mario Beilmann
Comparison fields: 5 of 100
  • Hepatology 124
  • Small Animals 35
  • Nephrology 30
  • Computational Theory and Mathematics 60
  • Molecular Biology 253
Replace Tadahiro Shinozawa with:
Tadahiro Shinozawa Japan
Walter F. Bobrowski United States
Shingo Niimi Japan
Raymond Reif Germany
Kathleen M. Gilbert United States
Hailin Zhang China
Dawn Applegate United States
Gahl Levy Israel
Monika Niehof Germany
Tom Henkens Belgium
Mario Beilmann relative to Tadahiro Shinozawa Japan Tadahiro Shinozawa's profile →
Citations per field
00.5×7.5×
Tadahiro Shinozawa · 1×
Citations per year

Countries citing papers authored by Mario Beilmann

Since Specialization
Citations

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

Fields of papers citing papers by Mario Beilmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1
The evolving role of investigative toxicology in the pharmaceutical industry
Hit paper breakdown →
2023132
2 200065
3 199765
4 201747
5 201543
6 201840
7 201836
8 200033
9 201829
10 201929
11 200927
12 200426
13 201918
14 20179
15 20248
16 20257
17 20036
18 20196
19 19974
20 20223

About Mario Beilmann

Mario Beilmann is a scholar working on Molecular Biology, Biomedical Engineering, Surgery, Pathology and Forensic Medicine and Hepatology, having authored 21 papers that have together received 634 indexed citations. Recurring topics across this work include 3D Printing in Biomedical Research (7 papers), Pluripotent Stem Cells Research (5 papers), Liver physiology and pathology (4 papers), Organ Transplantation Techniques and Outcomes (4 papers), Pancreatic function and diabetes (3 papers), Computational Drug Discovery Methods (3 papers), Animal testing and alternatives (2 papers) and Cell Adhesion Molecules Research (2 papers). The work is most often cited by research in Hepatology (124 citations), Small Animals (35 citations), Nephrology (30 citations), Computational Theory and Mathematics (60 citations) and Molecular Biology (253 citations). Mario Beilmann has collaborated with scholars based in Germany, United States and United Kingdom. Frequent co-authors include Peter Schirmacher, Hans‐Peter Dienes, George F. Vande Woude, Margarete Odenthal, Adrian Roth, Ulrich Deschl, Harrie C. M. Boonen, Philip Hewitt, Thomas Steger‐Hartmann and Teija Oinonen. Their work appears in journals such as Blood, Nature Reviews Drug Discovery, Cytokine, Scientific Reports and Stem Cells and Development.

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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