Martin Fenner

122 papers receiving 2.1k citations

Peers

Martin Fenner
Comparison fields: 5 of 167
  • Information Systems and Management 220
  • Statistics, Probability and Uncertainty 183
  • Cancer Research 359
  • Molecular Biology 1.1k
  • Information Systems 323
Replace Roger Day with:
Roger Day United States
Thomas Schlange Germany
Michael J. Becich United States
Theodora Bloom United States
Vincent Ferretti Canada
Marie Loh Singapore
Laurence Gamé United Kingdom
Nicole Vasilevsky United States
Michael Krauthammer United States
Sharon F. Terry United States
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Citations per year

Countries citing papers authored by Martin Fenner

Since Specialization
Citations

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

Fields of papers citing papers by Martin Fenner

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 198 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2000198
2 2012174
3 2003142
4 1993111
5 1998105
6 199680
7 200274
8 200574
9 201172
10 201370
11 200657
12 201357
13 200353
14 199751
15 201947
16 201343
17 201243
18 201137
19 198336
20 200336

About Martin Fenner

Martin Fenner is a scholar working on Information Systems, Molecular Biology, Information Systems and Management, Pulmonary and Respiratory Medicine and Management Science and Operations Research, having authored 198 papers that have together received 2.2k indexed citations. Recurring topics across this work include Research Data Management Practices (29 papers), Scientific Computing and Data Management (29 papers), Data Quality and Management (17 papers), Renal cell carcinoma treatment (13 papers), T-cell and B-cell Immunology (9 papers), scientometrics and bibliometrics research (8 papers), Cancer Genomics and Diagnostics (8 papers) and Wikis in Education and Collaboration (7 papers). The work is most often cited by research in Information Systems and Management (220 citations), Statistics, Probability and Uncertainty (183 citations), Cancer Research (359 citations), Molecular Biology (1.1k citations) and Information Systems (323 citations). Martin Fenner has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Toshi Shioda, Elena Elstner, Kurt J. Isselbacher, Jennifer Lin, K. Possinger, C. Zang, Haak Laurel, Ed Pentz, Hans Binz and Laura Paglione. Their work appears in journals such as Journal of Clinical Oncology, Scandinavian Journal of Immunology, European Journal of Cancer, Proceedings of the National Academy of Sciences and International Journal of Cancer.

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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