Hongdo Do

3.8k citations
42 papers · 2.2k indexed · h-index 22

Impact in

    • Cancer Genomics and Diagnostics
  • Oncology top 5%
    • Colorectal Cancer Treatments and Studies
    • Lung Cancer Research Studies

Papers in

Hongdo Do

42 papers receiving 2.1k citations

Peers

Hongdo Do
Comparison fields: 5 of 104
  • Cancer Research 864
  • Oncology 749
  • Pulmonary and Respiratory Medicine 702
  • Pathology and Forensic Medicine 328
  • Molecular Biology 1.2k
Replace Suk Hang Cheng with:
Suk Hang Cheng Hong Kong
Rachel Erlich United States
Abel J. Bronkhorst Germany
Thierry Petit France
Lee A. Albacker United States
C Lederrey Switzerland
Aaron R. Thorner United States
Toru Motokura Japan
Go Yamamoto Japan
Danielle M. Hari United States
Hongdo Do relative to Suk Hang Cheng Hong Kong Suk Hang Cheng's profile →
Citations per field
00.5×1.7×
Suk Hang Cheng · 1×
Citations per year

Countries citing papers authored by Hongdo Do

Since Specialization
Citations

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

Fields of papers citing papers by Hongdo Do

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 42 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014357
2 2014192
3 2017182
4 2008180
5 2014154
6 2017137
7 2012129
8 2012125
9 201381
10 201453
11 200944
12 201344
13 201339
14 201438
15 200835
16 201333
17 201930
18 201327
19 202024
20 201624

About Hongdo Do

Hongdo Do is a scholar working on Transplantation, Cancer Research, Pulmonary and Respiratory Medicine, Molecular Biology and Oncology, having authored 42 papers that have together received 2.2k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (18 papers), Lung Cancer Treatments and Mutations (14 papers), Molecular Biology Techniques and Applications (9 papers), RNA modifications and cancer (6 papers), Epigenetics and DNA Methylation (5 papers), Renal Transplantation Outcomes and Treatments (5 papers), Colorectal Cancer Treatments and Studies (4 papers) and Lung Cancer Research Studies (4 papers). The work is most often cited by research in Cancer Research (864 citations), Oncology (749 citations), Pulmonary and Respiratory Medicine (702 citations), Pathology and Forensic Medicine (328 citations) and Molecular Biology (1.2k citations). Hongdo Do has collaborated with scholars based in Australia, United States and Germany. Frequent co-authors include Alexander Dobrovic, Stephen B. Fox, Paul Mitchell, Stephen Q. Wong, Jason Li, Thomas John, Thomas Mikeska, Christoph Bock, Paul Mitchell and Grant A. McArthur. Their work appears in journals such as Clinical Chemistry, Scientific Reports, Journal of Thoracic Oncology, Lung Cancer and Oncotarget.

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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