Daniel Schulz
Impact in
- Biophysics top 5%
- Cell Image Analysis Techniques
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- Immunotherapy and Immune Responses
Papers in
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- Gene expression and cancer classification 2
- Single-cell and spatial transcriptomics 2
- RNA Research and Splicing 2
- RNA and protein synthesis mechanisms 2
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- Cell Image Analysis Techniques 2
- Co-authors
- Bernd Bodenmiller (4 shared papers)Nils Eling (2 shared papers)Patrick Cramer (2 shared papers)Tobias Hoch (1 shared paper)Julia M. Martínez Gómez (1 shared paper)Mitchell P. Levesque (1 shared paper)Johannes Soeding (1 shared paper)Anja Kiesel (1 shared paper)
- Journals
- Science Immunology (1 paper)Nature Protocols (1 paper)Nature Methods (1 paper)Journal of Biological Chemistry (1 paper)Science Translational Medicine (1 paper)
- Partner nations
- SwitzerlandGermanyUnited States
In The Last Decade
Daniel Schulz
6 papers receiving 531 citations
Daniel Schulz's Hit Papers
Peers
Comparison fields: 5 of 66
- Biophysics 65
- Immunology 115
- Molecular Biology 342
- Cancer Research 56
- Oncology 99
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 | 2013 | 168 | |
| 2 | Multiplexed imaging mass cytometry of the chemokine milieus in melanoma characterizes features of the response to immunotherapy Hit paper breakdown → | 2022 | 166 |
| 3 | An end-to-end workflow for multiplexed image processing and analysis Hit paper breakdown → | 2023 | 109 |
| 4 | 2014 | 35 | |
| 5 | 2019 | 30 | |
| 6 | 2022 | 24 |
About Daniel Schulz
Daniel Schulz is a scholar working on Molecular Biology, Biophysics, Immunology, Dermatology and Urology, having authored 6 papers that have together received 532 indexed citations. Recurring topics across this work include Gene expression and cancer classification (2 papers), Cell Image Analysis Techniques (2 papers), Single-cell and spatial transcriptomics (2 papers), RNA Research and Splicing (2 papers), RNA and protein synthesis mechanisms (2 papers), Dermatology and Skin Diseases (1 paper), Cancer Immunotherapy and Biomarkers (1 paper) and Immunotherapy and Immune Responses (1 paper). The work is most often cited by research in Biophysics (65 citations), Immunology (115 citations), Molecular Biology (342 citations), Cancer Research (56 citations) and Oncology (99 citations). Daniel Schulz has collaborated with scholars based in Switzerland, Germany and United States. Frequent co-authors include Bernd Bodenmiller, Nils Eling, Patrick Cramer, Tobias Hoch, Julia M. Martínez Gómez, Mitchell P. Levesque, Johannes Soeding, Anja Kiesel, Julien Gagneur and Carlo Baejen. Their work appears in journals such as Science Immunology, Nature Protocols, Nature Methods, Journal of Biological Chemistry and Science Translational Medicine.
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.