K. Christopher García
- Immunology top 0.05%
- Molecular Biology top 0.2%
- Oncology top 0.2%
- Radiology, Nuclear Medicine and Imaging top 0.2%
- Cellular and Molecular Neuroscience top 0.2%
- Co-authors
- Ian A. WilsonLuc TeytonPer A. PetersonMassimo DeganoPatrick J. LupardusMartin J. BoulangerXiao-lin HeXinquan Wang
- Topics
- Immune Cell Function and Interaction (115 papers)T-cell and B-cell Immunology (110 papers)Monoclonal and Polyclonal Antibodies Research (55 papers)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
K. Christopher García
293 papers receiving 28.1k citations
Hit Papers
Peers
Comparison fields: 5 of 170
- Immunology 14.2k
- Molecular Biology 10.6k
- Oncology 6.7k
- Radiology, Nuclear Medicine and Imaging 3.7k
- Cellular and Molecular Neuroscience 3.6k
Countries citing papers authored by K. Christopher García
This map shows the geographic impact of K. Christopher García'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 K. Christopher García with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K. Christopher García more than expected).
Fields of papers citing papers by K. Christopher García
This network shows the impact of papers produced by K. Christopher García. 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 K. Christopher García. The network helps show where K. Christopher García may publish in the future.
Co-authorship network of co-authors of K. Christopher García
This figure shows the co-authorship network connecting the top 25 collaborators of K. Christopher García. A scholar is included among the top collaborators of K. Christopher García based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with K. Christopher García. K. Christopher García is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 5 | |
| 3 | 1 | |
| 4 | 14 | |
| 5 | 0 | |
| 6 | 27 | |
| 7 | 6 | |
| 8 | 8 | |
| 9 | 16 | |
| 10 | 65 | |
| 11 | 115 | |
| 12 | Selective targeting of engineered T cells using orthogonal IL-2 cytokine-receptor complexesbreakdown → | 275 |
| 13 | 63 | |
| 14 | 205 | |
| 15 | 197 | |
| 16 | 376 | |
| 17 | Structural Basis of Wnt Recognition by Frizzledbreakdown → | 635 |
| 18 | 91 | |
| 19 | 364 | |
| 20 | 215 |
About K. Christopher García
K. Christopher García is a scholar working on Immunology, Oncology and Radiology, Nuclear Medicine and Imaging, having authored 298 papers that have together received 28.5k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (115 papers), T-cell and B-cell Immunology (110 papers) and Monoclonal and Polyclonal Antibodies Research (55 papers). The work is most often cited by research in Immunology (14.2k citations), Oncology (6.7k citations) and Cellular and Molecular Neuroscience (3.6k citations). K. Christopher García has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Ian A. Wilson, Luc Teyton, Per A. Peterson, Massimo Degano, Patrick J. Lupardus, Martin J. Boulanger, Xiao-lin He, Xinquan Wang, Christoph Thomas and Aaron M. Ring. Their work appears in journals such as Nature, Science 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.