Dan Jin
Impact in
- Genetics top 10%
- Glioma Diagnosis and Treatment
- Orthopedics and Sports Medicine top 10%
Papers in
-
- Single-cell and spatial transcriptomics 3
- RNA Interference and Gene Delivery 2
-
- interferon and immune responses 5
- Immunotherapy and Immune Responses 3
- Co-authors
- Diane L. Trinh (4 shared papers)Mathew Sebastian (6 shared papers)Marco A. Marra (4 shared papers)Véronique Leblanc (3 shared papers)Tarun E. Hutchinson (2 shared papers)David Tran (1 shared paper)Ashley Ghiaseddin (1 shared paper)Maryam Rahman (2 shared papers)
- Journals
- Neuro-Oncology (7 papers)Urolithiasis (2 papers)Blood (2 papers)PLoS ONE (2 papers)Cancer Cell (2 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Dan Jin
40 papers receiving 509 citations
Peers
Comparison fields: 5 of 85
- Genetics 101
- Orthopedics and Sports Medicine 39
- Cancer Research 55
- Immunology 73
- Biochemistry 19
Countries citing papers authored by Dan Jin
This map shows the geographic impact of Dan Jin'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 Dan Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Jin more than expected).
Fields of papers citing papers by Dan Jin
This network shows the impact of papers produced by Dan Jin. 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 Dan Jin. The network helps show where Dan Jin may publish in the future.
Co-authors
The 25 scholars most cited alongside Dan Jin, 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 44 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 94 | |
| 2 | Tumor Treating Fields dually activate STING and AIM2 inflammasomes to induce adjuvant immunity in glioblastoma | 2022 | 93 |
| 3 | 2023 | 44 | |
| 4 | 2023 | 37 | |
| 5 | 2009 | 31 | |
| 6 | 2012 | 27 | |
| 7 | 2009 | 21 | |
| 8 | 2019 | 19 | |
| 9 | 2023 | 17 | |
| 10 | 2016 | 16 | |
| 11 | 2022 | 15 | |
| 12 | 2022 | 13 | |
| 13 | 2017 | 12 | |
| 14 | 2014 | 11 | |
| 15 | 2024 | 9 | |
| 16 | 2004 | 8 | |
| 17 | 2023 | 5 | |
| 18 | 2022 | 5 | |
| 19 | 2015 | 5 | |
| 20 | [Effect of platelet-rich plasma on proliferation and osteogenic differentiation of bone marrow stem cells in China goats]. | 2007 | 4 |
About Dan Jin
Dan Jin is a scholar working on Molecular Biology, Immunology, Oncology, Pulmonary and Respiratory Medicine and Cancer Research, having authored 44 papers that have together received 516 indexed citations. Recurring topics across this work include interferon and immune responses (5 papers), Cancer Genomics and Diagnostics (4 papers), Single-cell and spatial transcriptomics (3 papers), Immunotherapy and Immune Responses (3 papers), Nanoparticle-Based Drug Delivery (3 papers), Acute Myeloid Leukemia Research (3 papers), Cancer Research and Treatments (3 papers) and RNA Interference and Gene Delivery (2 papers). The work is most often cited by research in Genetics (101 citations), Orthopedics and Sports Medicine (39 citations), Cancer Research (55 citations), Immunology (73 citations) and Biochemistry (19 citations). Dan Jin has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Diane L. Trinh, Mathew Sebastian, Marco A. Marra, Véronique Leblanc, Tarun E. Hutchinson, David Tran, Ashley Ghiaseddin, Maryam Rahman, Anda‐Alexandra Calinescu and Tianyi Liu. Their work appears in journals such as Neuro-Oncology, Urolithiasis, Blood, PLoS ONE and Cancer 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.