Ryan D. Chow

3.7k citations
38 papers · 1.9k · h-index 21

Impact in

  • Aging top 5%
  • Oncology top 5%
    • CAR-T cell therapy research
    • Cancer Immunotherapy and Biomarkers

Papers in

    • CRISPR and Genetic Engineering 12
    • Single-cell and spatial transcriptomics 4
    • CAR-T cell therapy research 10
    • Cancer Immunotherapy and Biomarkers 4

Ryan D. Chow

32 papers receiving 1.9k citations

Peers

Ryan D. Chow
Comparison fields: 5 of 112
  • Aging 57
  • Oncology 645
  • Business and International Management 42
  • Molecular Biology 1.2k
  • Immunology 340
Replace Christian Schmidl with:
Christian Schmidl Germany
Shoichi Date Japan
Andrew J. Kueh Australia
Vincenzo Corbo Italy
Sarah Krausz Netherlands
Benjamin G. Gowen United States
Christopher W. Peterson United States
René Overmeer Netherlands
Yueying Cao United States
Martin W. LaFleur United States
Ryan D. Chow relative to Christian Schmidl Germany Christian Schmidl's profile →
Citations per field
00.5×4.2×
Christian Schmidl · 1×
Citations per year

Countries citing papers authored by Ryan D. Chow

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Ryan D. Chow Line = papers co-authored together Ryan D. Chow links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019225
2 2017176
3 2019153
4 2022150
5 2015129
6 2020122
7 2021102
8 201897
9 201990
10 202090
11 201879
12 201872
13 201863
14 202157
15 202244
16 201943
17 202337
18 202335
19 202433
20 201830

About Ryan D. Chow

Ryan D. Chow is a scholar working on Molecular Biology, Oncology, Immunology, Genetics and Surgery, having authored 38 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), Single-cell and spatial transcriptomics (4 papers), Cancer Immunotherapy and Biomarkers (4 papers), Immune Cell Function and Interaction (4 papers), Virus-based gene therapy research (4 papers), Cancer Genomics and Diagnostics (3 papers) and Bladder and Urothelial Cancer Treatments (3 papers). The work is most often cited by research in Aging (57 citations), Oncology (645 citations), Business and International Management (42 citations), Molecular Biology (1.2k citations) and Immunology (340 citations). Ryan D. Chow has collaborated with scholars based in United States, Japan and China. Frequent co-authors include Sidi Chen, Lupeng Ye, Matthew B. Dong, 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, Cancer Discovery, Nature Immunology, Urologic Oncology Seminars and Original Investigations and Nature Communications.

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.

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