Ryan D. Chow
Impact in
Papers in
-
- CRISPR and Genetic Engineering 12
- Single-cell and spatial transcriptomics 4
- Oncology 15
- CAR-T cell therapy research 10
- Cancer Immunotherapy and Biomarkers 4
- Co-authors
- Sidi Chen (20 shared papers)Matthew B. Dong (10 shared papers)Lupeng Ye (11 shared papers)Guangchuan Wang (11 shared papers)Youssef Errami (8 shared papers)Xiaoyun Dai (7 shared papers)Jennifer Chen (3 shared papers)Jonathan J. Park (7 shared papers)
- Journals
- Nature Biotechnology (4 papers)Nature Communications (2 papers)Urologic Oncology Seminars and Original Investigations (2 papers)Nature Immunology (2 papers)Cancer Discovery (2 papers)
- Partner nations
- United StatesJapanChina
In The Last Decade
Ryan D. Chow
33 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 114
- Aging 58
- Oncology 661
- Business and International Management 43
- Molecular Biology 1.2k
- Immunology 355
Countries citing papers authored by Ryan D. Chow
This map shows the geographic impact of Ryan D. Chow'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 Ryan D. Chow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryan D. Chow more than expected).
Fields of papers citing papers by Ryan D. Chow
This network shows the impact of papers produced by Ryan D. Chow. 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 Ryan D. Chow. The network helps show where Ryan D. Chow may publish in the future.
Co-authors
The 25 scholars most cited alongside Ryan D. Chow, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 213 | |
| 2 | 2017 | 175 | |
| 3 | 2019 | 148 | |
| 4 | A genome-scale gain-of-function CRISPR screen in CD8 T cells identifies proline metabolism as a means to enhance CAR-T therapy Hit paper breakdown → | 2022 | 143 |
| 5 | 2015 | 128 | |
| 6 | 2020 | 116 | |
| 7 | 2021 | 99 | |
| 8 | 2018 | 92 | |
| 9 | 2019 | 88 | |
| 10 | 2020 | 87 | |
| 11 | 2018 | 77 | |
| 12 | 2018 | 72 | |
| 13 | 2018 | 60 | |
| 14 | 2021 | 56 | |
| 15 | 2019 | 42 | |
| 16 | 2022 | 40 | |
| 17 | 2023 | 34 | |
| 18 | 2023 | 32 | |
| 19 | 2018 | 29 | |
| 20 | 2024 | 26 |
About Ryan D. Chow
Ryan D. Chow is a scholar working on Molecular Biology, Oncology, Immunology, Genetics and Surgery, having authored 40 papers that have together received 1.9k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (12 papers), CAR-T cell therapy research (10 papers), Immune Cell Function and Interaction (6 papers), Single-cell and spatial transcriptomics (4 papers), Virus-based gene therapy research (4 papers), Cancer Immunotherapy and Biomarkers (4 papers), Bladder and Urothelial Cancer Treatments (3 papers) and Cancer Genomics and Diagnostics (3 papers). The work is most often cited by research in Aging (58 citations), Oncology (661 citations), Business and International Management (43 citations), Molecular Biology (1.2k citations) and Immunology (355 citations). Ryan D. Chow has collaborated with scholars based in United States, Japan and China. Frequent co-authors include Sidi Chen, Matthew B. Dong, Lupeng Ye, Guangchuan Wang, Youssef Errami, Xiaoyun Dai, Jennifer Chen, Jonathan J. Park, Johanna Shen and Paul Renauer. Their work appears in journals such as Nature Biotechnology, Nature Communications, Urologic Oncology Seminars and Original Investigations, Nature Immunology and Cancer Discovery.
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.