Doyeon Ha

442 citations
5 papers · 307 · 1 hit paper · h-index 5

Impact in

Papers in

    • Bioinformatics and Genomic Networks 2
    • Single-cell and spatial transcriptomics 1
    • vaccines and immunoinformatics approaches 1
    • Cancer Immunotherapy and Biomarkers 2
    • CAR-T cell therapy research 1

Doyeon Ha

5 papers receiving 303 citations

Doyeon Ha's Hit Papers

Network-based machine learning approach to predict immunotherapy response in cancer patients 2022 · 126 citations
1260+1+2Years since publication4080120

Peers

Doyeon Ha
Comparison fields: 5 of 66
  • Health Informatics 9
  • Oncology 136
  • Cancer Research 66
  • Computational Theory and Mathematics 41
  • Biophysics 14
Replace Masturah Bte Mohd Abdul Rashid with:
Masturah Bte Mohd Abdul Rashid Singapore
Matthew McCoy United States
JungHo Kong South Korea
Manuel Nietert Germany
Liren Jiang China
Musalula Sinkala Zambia
Bonnie Hei Man Liu Hong Kong
Sylvia Chien United States
Sofia Nomikou United States
Doyeon Ha relative to Masturah Bte Mohd Abdul Rashid Singapore Masturah Bte Mohd Abdul Rashid's profile →
Citations per field
00.5×1.5×1.9×
Masturah Bte Mohd Abdul Rashid · 1×
Citations per year

Countries citing papers authored by Doyeon Ha

Since Specialization
Citations

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

Fields of papers citing papers by Doyeon Ha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 8 scholars most cited alongside Doyeon Ha, 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 Doyeon Ha Line = papers co-authored together Doyeon Ha links everyone, so they are left out of the graph.

All Works

5 of 5 papers shown

About Doyeon Ha

Doyeon Ha is a scholar working on Molecular Biology, Oncology, Computational Theory and Mathematics, Pathology and Forensic Medicine and Pharmacology, having authored 5 papers that have together received 307 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (2 papers), Computational Drug Discovery Methods (2 papers), Cancer Immunotherapy and Biomarkers (2 papers), Single-cell and spatial transcriptomics (1 paper), CAR-T cell therapy research (1 paper), Cancer Genomics and Diagnostics (1 paper), Genetic factors in colorectal cancer (1 paper) and vaccines and immunoinformatics approaches (1 paper). The work is most often cited by research in Health Informatics (9 citations), Oncology (136 citations), Cancer Research (66 citations), Computational Theory and Mathematics (41 citations) and Biophysics (14 citations). Doyeon Ha has collaborated with scholars based in South Korea and France. Frequent co-authors include Sanguk Kim, Kunyoo Shin, Donghyo Kim, Seong Kyu Han, Heetak Lee, JungHo Kong, Juhun Lee and Sin‐Hyeog Im. Their work appears in journals such as Nature Communications, Science Advances, BMB Reports and Nucleic Acids Research.

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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