Markus Boehm
Impact in
- Cell Biology top 2%
- Cellular transport and secretion
- Physiology top 2%
Papers in
- Cell Biology 10
- Cellular transport and secretion 8
-
- Computational Drug Discovery Methods 8
- Co-authors
- Juan S. BonifacinoVolker GekelerThomas BeckersCarsten DenkertSilvia NiesporekNaava NaslavskyWilko WeichertPeter S. Backlund
- Journals
- Cancer Research (4 papers)ACS Medicinal Chemistry Letters (4 papers)Clinical Cancer Research (2 papers)Biological Chemistry (2 papers)Bioorganic & Medicinal Chemistry Letters (2 papers)
- Partner nations
- United StatesGermanySwitzerland
In The Last Decade
Markus Boehm
54 papers receiving 2.5k citations
Peers
Comparison fields: 5 of 118
- Cell Biology 748
- Physiology 146
- Immunology and Allergy 152
- Molecular Biology 1.7k
- Virology 84
Countries citing papers authored by Markus Boehm
This map shows the geographic impact of Markus Boehm'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 Markus Boehm with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Markus Boehm more than expected).
Fields of papers citing papers by Markus Boehm
This network shows the impact of papers produced by Markus Boehm. 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 Markus Boehm. The network helps show where Markus Boehm may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Markus Boehm, 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 | 2 | |
| 2 | 2021 | 2 | |
| 3 | 2018 | 24 | |
| 4 | 2016 | 57 | |
| 5 | 2015 | 41 | |
| 6 | 2013 | 12 | |
| 7 | 2013 | 8 | |
| 8 | 2013 | 20 | |
| 9 | BYL719, a next generation PI3K alpha specific inhibitor: Preliminary safety, PK, and efficacy results from the first-in-human study | 2012 | 29 |
| 10 | 2010 | 93 | |
| 11 | 2008 | 299 | |
| 12 | 2007 | 124 | |
| 13 | 2004 | 17 | |
| 14 | 2004 | 118 | |
| 15 | 2003 | 71 | |
| 16 | 2002 | 121 | |
| 17 | 2000 | 69 | |
| 18 | 1999 | 103 | |
| 19 | 1997 | 10 | |
| 20 | 1989 | 18 |
About Markus Boehm
Markus Boehm is a scholar working on Cell Biology, Computational Theory and Mathematics, Immunology and Allergy, Molecular Biology and Virology, having authored 55 papers that have together received 2.5k indexed citations. Recurring topics across this work include Thin-Film Transistor Technologies (9 papers), Computational Drug Discovery Methods (8 papers), Cellular transport and secretion (8 papers), RNA and protein synthesis mechanisms (6 papers), PI3K/AKT/mTOR signaling in cancer (5 papers), CCD and CMOS Imaging Sensors (5 papers), Lipid Membrane Structure and Behavior (5 papers) and Protein Structure and Dynamics (4 papers). The work is most often cited by research in Cell Biology (748 citations), Physiology (146 citations), Immunology and Allergy (152 citations), Molecular Biology (1.7k citations) and Virology (84 citations). Markus Boehm has collaborated with scholars based in United States, Germany and Switzerland. Frequent co-authors include Juan S. Bonifacino, Volker Gekeler, Thomas Beckers, Carsten Denkert, Silvia Niesporek, Naava Naslavsky, Wilko Weichert, Peter S. Backlund, Steve Caplan and Manfred Dietel. Their work appears in journals such as Cancer Research, ACS Medicinal Chemistry Letters, Clinical Cancer Research, Biological Chemistry and Bioorganic & Medicinal Chemistry Letters.
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.