David Van Valen
Impact in
- Biophysics top 0.5%
- Cell Image Analysis Techniques
- Advanced Fluorescence Microscopy Techniques
- Structural Biology top 5%
Papers in
-
- Single-cell and spatial transcriptomics 5
- Protein Structure and Dynamics 2
-
- Cell Image Analysis Techniques 5
- Co-authors
- William D. Graf (4 shared papers)Takamasa Kudo (3 shared papers)Markus W. Covert (2 shared papers)Dylan Bannon (2 shared papers)Erick Moen (2 shared papers)Sean C. Bendall (2 shared papers)Michael Angelo (2 shared papers)Leeat Keren (1 shared paper)
- Journals
- Nature Methods (4 papers)Cell Systems (3 papers)Biophysical Journal (2 papers)Current Biology (1 paper)Cell (1 paper)
- Partner nations
- United StatesNetherlandsUnited Kingdom
In The Last Decade
David Van Valen
14 papers receiving 2.0k citations
David Van Valen's Hit Papers
Peers
Comparison fields: 5 of 144
- Biophysics 600
- Structural Biology 33
- Immunology 380
- Media Technology 160
- Cancer Research 195
Countries citing papers authored by David Van Valen
This map shows the geographic impact of David Van Valen'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 David Van Valen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Van Valen more than expected).
Fields of papers citing papers by David Van Valen
This network shows the impact of papers produced by David Van Valen. 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 David Van Valen. The network helps show where David Van Valen may publish in the future.
Co-authors
The 25 scholars most cited alongside David Van Valen, 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 | Deep learning for cellular image analysis Hit paper breakdown → | 2019 | 766 |
| 2 | A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging Hit paper breakdown → | 2018 | 682 |
| 3 | 2020 | 221 | |
| 4 | 2017 | 112 | |
| 5 | 2021 | 93 | |
| 6 | 2012 | 54 | |
| 7 | 2009 | 37 | |
| 8 | 2010 | 27 | |
| 9 | 2022 | 15 | |
| 10 | 2024 | 9 | |
| 11 | 2023 | 7 | |
| 12 | 2023 | 3 | |
| 13 | 2025 | 3 | |
| 14 | 2025 | 1 |
About David Van Valen
David Van Valen is a scholar working on Molecular Biology, Biophysics, Immunology, Ecology and Oncology, having authored 14 papers that have together received 2.0k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (5 papers), Cell Image Analysis Techniques (5 papers), Bacteriophages and microbial interactions (3 papers), Immune cells in cancer (3 papers), Protein Structure and Dynamics (2 papers), Cancer Cells and Metastasis (2 papers), Bacterial Genetics and Biotechnology (2 papers) and Image Processing Techniques and Applications (2 papers). The work is most often cited by research in Biophysics (600 citations), Structural Biology (33 citations), Immunology (380 citations), Media Technology (160 citations) and Cancer Research (195 citations). David Van Valen has collaborated with scholars based in United States, Netherlands and United Kingdom. Frequent co-authors include William D. Graf, Takamasa Kudo, Markus W. Covert, Dylan Bannon, Erick Moen, Sean C. Bendall, Michael Angelo, Leeat Keren, Soo‐Ryum Yang and Marc Bossé. Their work appears in journals such as Nature Methods, Cell Systems, Biophysical Journal, Current Biology and Cell.
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.