David Van Valen

5.2k citations
14 papers · 1.9k indexed · 2 hit papers · h-index 9

Impact in

Papers in

David Van Valen

14 papers receiving 1.9k citations

Hit Papers

Deep learning for cellular image analysis 2019 · 737 citations
7372018202620202023200400600

Peers

David Van Valen
Comparison fields: 5 of 144
  • Biophysics 615
  • Structural Biology 33
  • Media Technology 166
  • Immunology 388
  • Cancer Research 216
Replace Karl Rohr with:
Karl Rohr Germany
Kyle W. Karhohs United States
Carsten Marr Germany
Mark‐Anthony Bray United States
Allen Goodman United States
Carolina Wählby Sweden
Minh Doan United States
Vannary Meas‐Yedid France
Tim Becker Germany
Claire McQuin United States
David Van Valen relative to Karl Rohr Germany Karl Rohr's profile →
Citations per field
00.5×
Karl Rohr · 1×
Citations per year

Countries citing papers authored by David Van Valen

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network

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.

Border = papers with David Van Valen Line = papers co-authored together David Van Valen links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 20251
2 20252
3 20246
4 20236
5 20233
6 202213
7 202186
8 2020206
9
Deep learning for cellular image analysis
Hit paper breakdown →
2019737
10
A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging
Hit paper breakdown →
2018653
11 2017110
12 201252
13 201027
14 200937

About David Van Valen

David Van Valen is a scholar working on Biophysics, Endocrinology, Media Technology, Immunology and Ecology, having authored 14 papers that have together received 1.9k 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), Bacterial Genetics and Biotechnology (2 papers), Image Processing Techniques and Applications (2 papers) and Cancer Cells and Metastasis (2 papers). The work is most often cited by research in Biophysics (615 citations), Structural Biology (33 citations), Media Technology (166 citations), Immunology (388 citations) and Cancer Research (216 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, Michael Angelo, Sean C. Bendall, Soo‐Ryum Yang, Diana M. Marquez and Allison W. Kurian. Their work appears in journals such as Nature Methods, Cell Systems, Biophysical Journal, Nature Cell Biology and Current Biology.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026