Daniel Schulz
Impact in
- Biophysics top 5%
- Cell Image Analysis Techniques
-
- Immunotherapy and Immune Responses
Papers in
-
- Cell Image Analysis Techniques 3
-
- Immunotherapy and Immune Responses 2
- Co-authors
- Bernd Bodenmiller (4 shared papers)Nils Eling (3 shared papers)Mitchell Paul Levesque (2 shared papers)Julia M. Martínez Gómez (1 shared paper)Tobias Hoch (1 shared paper)Patrick Cramer (2 shared papers)Michelle M. Daniel (1 shared paper)Jonas Windhager (1 shared paper)
- Journals
- Clinical Cancer Research (2 papers)Science Translational Medicine (1 paper)Neuro-Oncology (1 paper)Cell Reports Methods (1 paper)Journal of Biological Chemistry (1 paper)
- Partner nations
- SwitzerlandUnited StatesGermany
In The Last Decade
Daniel Schulz
7 papers receiving 620 citations
Daniel Schulz's Hit Papers
Peers
Comparison fields: 5 of 70
- Biophysics 73
- Immunology 141
- Molecular Biology 360
- Oncology 125
- Cancer Research 59
Countries citing papers authored by Daniel Schulz
This map shows the geographic impact of Daniel Schulz'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 Daniel Schulz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Schulz more than expected).
Fields of papers citing papers by Daniel Schulz
This network shows the impact of papers produced by Daniel Schulz. 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 Daniel Schulz. The network helps show where Daniel Schulz may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Schulz, 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 | Multiplexed imaging mass cytometry of the chemokine milieus in melanoma characterizes features of the response to immunotherapy Hit paper breakdown → | 2022 | 196 |
| 2 | 2013 | 163 | |
| 3 | An end-to-end workflow for multiplexed image processing and analysis Hit paper breakdown → | 2023 | 160 |
| 4 | 2019 | 35 | |
| 5 | 2014 | 34 | |
| 6 | 2022 | 26 | |
| 7 | 2022 | 9 | |
| 8 | 2026 | 0 | |
| 9 | 2025 | 0 | |
| 10 | 2026 | 0 |
About Daniel Schulz
Daniel Schulz is a scholar working on Biophysics, Immunology, Otorhinolaryngology, Molecular Biology and Urology, having authored 10 papers that have together received 623 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (3 papers), Cell Image Analysis Techniques (3 papers), Gene expression and cancer classification (2 papers), Immunotherapy and Immune Responses (2 papers), RNA Research and Splicing (2 papers), RNA and protein synthesis mechanisms (2 papers), RNA modifications and cancer (1 paper) and Head and Neck Cancer Studies (1 paper). The work is most often cited by research in Biophysics (73 citations), Immunology (141 citations), Molecular Biology (360 citations), Oncology (125 citations) and Cancer Research (59 citations). Daniel Schulz has collaborated with scholars based in Switzerland, United States and Germany. Frequent co-authors include Bernd Bodenmiller, Nils Eling, Mitchell Paul Levesque, Julia M. Martínez Gómez, Tobias Hoch, Patrick Cramer, Michelle M. Daniel, Jonas Windhager, Vito Riccardo Tomaso Zanotelli and Anja Kiesel. Their work appears in journals such as Clinical Cancer Research, Science Translational Medicine, Neuro-Oncology, Cell Reports Methods and Journal of Biological Chemistry.
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.