Marc Hafner
Impact in
- Biophysics top 2%
- Cell Image Analysis Techniques
-
- Computational Drug Discovery Methods
Papers in
-
- Computational Drug Discovery Methods 14
- Co-authors
- Peter K. SorgerMario NiepelMirra ChungAvi Ma’ayanQiaonan DuanHeinz KoepplJeremy L. MuhlichAndrew D. Rouillard
- Journals
- Cancer Research (12 papers)Nature Communications (2 papers)Journal of Biological Chemistry (2 papers)Nucleic Acids Research (2 papers)BMC Bioinformatics (2 papers)
- Partner nations
- United StatesSwitzerlandFrance
In The Last Decade
Marc Hafner
56 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 137
- Biophysics 173
- Computational Theory and Mathematics 470
- Molecular Biology 1.2k
- Oncology 467
- Cancer Research 246
Countries citing papers authored by Marc Hafner
This map shows the geographic impact of Marc Hafner'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 Marc Hafner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc Hafner more than expected).
Fields of papers citing papers by Marc Hafner
This network shows the impact of papers produced by Marc Hafner. 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 Marc Hafner. The network helps show where Marc Hafner may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Marc Hafner, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 3 | |
| 4 | 2024 | 10 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 9 | |
| 7 | 2023 | 6 | |
| 8 | 2022 | 9 | |
| 9 | 2022 | 2 | |
| 10 | 2021 | 20 | |
| 11 | 2019 | 43 | |
| 12 | 2017 | 65 | |
| 13 | Growth rate inhibition metrics correct for confounders in measuring sensitivity to cancer drugs Hit paper breakdown → | 2016 | 387 |
| 14 | 2015 | 95 | |
| 15 | 2015 | 92 | |
| 16 | 2014 | 32 | |
| 17 | 2012 | 55 | |
| 18 | 2012 | 6 | |
| 19 | 2012 | 4 | |
| 20 | 2011 | 70 |
About Marc Hafner
Marc Hafner is a scholar working on Computational Theory and Mathematics, Biophysics, Oncology, Molecular Biology and Cancer Research, having authored 58 papers that have together received 2.0k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (14 papers), Advanced Breast Cancer Therapies (13 papers), HER2/EGFR in Cancer Research (8 papers), Gene Regulatory Network Analysis (8 papers), Estrogen and related hormone effects (7 papers), Monoclonal and Polyclonal Antibodies Research (6 papers), Bioinformatics and Genomic Networks (6 papers) and Protein Degradation and Inhibitors (6 papers). The work is most often cited by research in Biophysics (173 citations), Computational Theory and Mathematics (470 citations), Molecular Biology (1.2k citations), Oncology (467 citations) and Cancer Research (246 citations). Marc Hafner has collaborated with scholars based in United States, Switzerland and France. Frequent co-authors include Peter K. Sorger, Mario Niepel, Mirra Chung, Avi Ma’ayan, Qiaonan Duan, Heinz Koeppl, Jeremy L. Muhlich, Andrew D. Rouillard, Nicolas Fernandez and Andreas Wagner. Their work appears in journals such as Cancer Research, Nature Communications, Journal of Biological Chemistry, Nucleic Acids Research and BMC Bioinformatics.
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.