Mark A. Dane
Impact in
- Biophysics top 10%
- Cell Image Analysis Techniques
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- Computational Drug Discovery Methods
Papers in
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- Cell Image Analysis Techniques 5
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- Single-cell and spatial transcriptomics 5
- Gene Regulatory Network Analysis 2
- Gene expression and cancer classification 2
- Advanced Biosensing Techniques and Applications 2
- Co-authors
- Laura M. Heiser (15 shared papers)Sean M. Gross (6 shared papers)Elmar Bucher (5 shared papers)Joe W. Gray (6 shared papers)James E. Korkola (8 shared papers)Tiera A. Liby (3 shared papers)Gordon Brent Mills (2 shared papers)Rebecca Lee Smith (4 shared papers)
- Journals
- Cell Systems (3 papers)Journal of Visualized Experiments (2 papers)Communications Biology (2 papers)Bioinformatics (1 paper)Cancer Research (1 paper)
- Partner nations
- United StatesSpainPalestinian Territory
In The Last Decade
Mark A. Dane
19 papers receiving 537 citations
Peers
Comparison fields: 5 of 96
- Biophysics 52
- Computational Theory and Mathematics 105
- Molecular Biology 323
- Cancer Research 55
- Oncology 78
Countries citing papers authored by Mark A. Dane
This map shows the geographic impact of Mark A. Dane'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 Mark A. Dane with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark A. Dane more than expected).
Fields of papers citing papers by Mark A. Dane
This network shows the impact of papers produced by Mark A. Dane. 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 Mark A. Dane. The network helps show where Mark A. Dane may publish in the future.
Co-authors
The 25 scholars most cited alongside Mark A. Dane, 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 | 2017 | 306 | |
| 2 | 2018 | 65 | |
| 3 | 2023 | 31 | |
| 4 | 2022 | 29 | |
| 5 | 2019 | 22 | |
| 6 | 2022 | 21 | |
| 7 | 2019 | 12 | |
| 8 | 2022 | 12 | |
| 9 | 2016 | 12 | |
| 10 | 2020 | 9 | |
| 11 | 2020 | 9 | |
| 12 | 2017 | 9 | |
| 13 | 2026 | 4 | |
| 14 | 2025 | 3 | |
| 15 | 2022 | 2 | |
| 16 | 2019 | 1 | |
| 17 | 2019 | 1 | |
| 18 | 2025 | 1 | |
| 19 | 2005 | 1 | |
| 20 | 2023 | 0 |
About Mark A. Dane
Mark A. Dane is a scholar working on Biophysics, Molecular Biology, Oncology, Cell Biology and Spectroscopy, having authored 20 papers that have together received 550 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (5 papers), Cell Image Analysis Techniques (5 papers), Gene Regulatory Network Analysis (2 papers), Advanced Proteomics Techniques and Applications (2 papers), Gene expression and cancer classification (2 papers), Advanced Biosensing Techniques and Applications (2 papers), Cancer Genomics and Diagnostics (1 paper) and Biomedical and Engineering Education (1 paper). The work is most often cited by research in Biophysics (52 citations), Computational Theory and Mathematics (105 citations), Molecular Biology (323 citations), Cancer Research (55 citations) and Oncology (78 citations). Mark A. Dane has collaborated with scholars based in United States, Spain and Palestinian Territory. Frequent co-authors include Laura M. Heiser, Sean M. Gross, Elmar Bucher, Joe W. Gray, James E. Korkola, Tiera A. Liby, Gordon Brent Mills, Rebecca Lee Smith, Damir Sudar and Michel A. Nederlof. Their work appears in journals such as Cell Systems, Journal of Visualized Experiments, Communications Biology, Bioinformatics and Cancer Research.
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.