Damien Tan

668 citations
16 papers · 462 · h-index 10

Impact in

  • Hepatology top 5%
    • Hepatitis C virus research
    • Hepatitis Viruses Studies and Epidemiology
  • Epidemiology top 10%
    • Hepatitis B Virus Studies
    • Liver Disease Diagnosis and Treatment

Papers in

    • CAR-T cell therapy research 4
    • Cancer Cells and Metastasis 3
    • Pancreatic and Hepatic Oncology Research 2
    • CRISPR and Genetic Engineering 3

Damien Tan

15 papers receiving 455 citations

Peers

Damien Tan
Comparison fields: 5 of 54
  • Hepatology 211
  • Epidemiology 266
  • Immunology 122
  • Oncology 96
  • Developmental Neuroscience 10
Replace S. Khan with:
S. Khan Canada
Hong Seok Kang South Korea
Gavin Whitehouse United Kingdom
Eleonora Cremonesi Switzerland
Keisuke Kosai United States
Immacolata Zampaglione Italy
Cristian G. Beccaría Argentina
Mohammed-Alkhatim Ali United States
Thomas N. Burn United States
Brynn B. Duncan United States
Damien Tan relative to S. Khan Canada S. Khan's profile →
Citations per field
00.5×9.2×
S. Khan · 1×
Citations per year

Countries citing papers authored by Damien Tan

Since Specialization
Citations

This map shows the geographic impact of Damien Tan'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 Damien Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Damien Tan more than expected).

Fields of papers citing papers by Damien Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Damien Tan. 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 Damien Tan. The network helps show where Damien Tan may publish in the future.

Co-authors

The 25 scholars most cited alongside Damien Tan, 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 Damien Tan Line = papers co-authored together Damien Tan links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 2018154
2 2020108
3 201842
4 202038
5 202124
6 201821
7 202020
8 202319
9 202314
10
Evaluation of entropy for monitoring the depth of anesthesia compared with bispectral index: a multicenter clinical trial.
201214
11 20253
12 20232
13 20231
14 20231
15 20101
16 20230

About Damien Tan

Damien Tan is a scholar working on Oncology, Molecular Biology, Epidemiology, Immunology and Genetics, having authored 16 papers that have together received 462 indexed citations. Recurring topics across this work include CAR-T cell therapy research (4 papers), Immune Cell Function and Interaction (4 papers), Cytomegalovirus and herpesvirus research (3 papers), Cancer Cells and Metastasis (3 papers), CRISPR and Genetic Engineering (3 papers), Mathematical Biology Tumor Growth (2 papers), Pancreatic and Hepatic Oncology Research (2 papers) and Immunotherapy and Immune Responses (2 papers). The work is most often cited by research in Hepatology (211 citations), Epidemiology (266 citations), Immunology (122 citations), Oncology (96 citations) and Developmental Neuroscience (10 citations). Damien Tan has collaborated with scholars based in Singapore, United Kingdom and United States. Frequent co-authors include Antonio Bertoletti, Navjyot Hansi, Patrick Kennedy, Upkar S. Gill, Evan W. Newell, Andrea Pavesi, Laura Rivino, Nina Le Bert, Kamini Kunasegaran and Yang Cheng. Their work appears in journals such as Small, Cancer Research, Biomaterials, Molecular Therapy and Journal of Clinical Oncology.

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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