Daniel J. Kuster
Impact in
- Immunology top 5%
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
- Immunotherapy and Immune Responses
- IL-33, ST2, and ILC Pathways
Papers in
-
- Protein Structure and Dynamics 3
- Chemical Synthesis and Analysis 3
- Bioinformatics and Genomic Networks 1
-
- Click Chemistry and Applications 2
- Co-authors
- Garland R. Marshall (6 shared papers)David J. Weiss (1 shared paper)Cédric Louvet (1 shared paper)James M. Gardner (1 shared paper)Marc Martínez‐Llordella (1 shared paper)David von Schack (1 shared paper)Peter Ruminski (1 shared paper)Jeffrey A. Bluestone (1 shared paper)
- Journals
- PLoS ONE (1 paper)Chemistry - A European Journal (1 paper)Biopolymers (1 paper)Journal of Computer-Aided Molecular Design (1 paper)Biophysical Journal (1 paper)
- Partner nations
- United StatesAustralia
In The Last Decade
Daniel J. Kuster
7 papers receiving 656 citations
Daniel J. Kuster's Hit Papers
Peers
Comparison fields: 5 of 83
- Immunology 428
- Oncology 79
- Molecular Biology 193
- Immunology and Allergy 12
- Transplantation 5
Countries citing papers authored by Daniel J. Kuster
This map shows the geographic impact of Daniel J. Kuster'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 J. Kuster with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel J. Kuster more than expected).
Fields of papers citing papers by Daniel J. Kuster
This network shows the impact of papers produced by Daniel J. Kuster. 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 J. Kuster. The network helps show where Daniel J. Kuster may publish in the future.
Co-authors
The 23 scholars most cited alongside Daniel J. Kuster, 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 | Neuropilin-1 distinguishes natural and inducible regulatory T cells among regulatory T cell subsets in vivo Hit paper breakdown → | 2012 | 523 |
| 2 | 2007 | 77 | |
| 3 | 2015 | 24 | |
| 4 | 2005 | 18 | |
| 5 | 2010 | 14 | |
| 6 | 2009 | 6 | |
| 7 | 2009 | 1 | |
| 8 | 2025 | 0 |
About Daniel J. Kuster
Daniel J. Kuster is a scholar working on Molecular Biology, Organic Chemistry, Spectroscopy, Pharmacology and Atomic and Molecular Physics, and Optics, having authored 8 papers that have together received 663 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (3 papers), Chemical Synthesis and Analysis (3 papers), Click Chemistry and Applications (2 papers), Mass Spectrometry Techniques and Applications (2 papers), Immunotherapy and Immune Responses (1 paper), Enzyme Structure and Function (1 paper), T-cell and B-cell Immunology (1 paper) and Bioinformatics and Genomic Networks (1 paper). The work is most often cited by research in Immunology (428 citations), Oncology (79 citations), Molecular Biology (193 citations), Immunology and Allergy (12 citations) and Transplantation (5 citations). Daniel J. Kuster has collaborated with scholars based in United States and Australia. Frequent co-authors include Garland R. Marshall, David J. Weiss, Cédric Louvet, James M. Gardner, Marc Martínez‐Llordella, David von Schack, Peter Ruminski, Jeffrey A. Bluestone, Dan Davini and Bryan A. Anthony. Their work appears in journals such as PLoS ONE, Chemistry - A European Journal, Biopolymers, Journal of Computer-Aided Molecular Design and Biophysical Journal.
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.