Yo Sup Moon

1.1k citations
5 papers · 732 · 1 hit paper · h-index 5

Impact in

Papers in

    • Gene expression and cancer classification 3
    • Bioinformatics and Genomic Networks 2
    • Metabolomics and Mass Spectrometry Studies 2
    • Melanoma and MAPK Pathways 1
    • Microbial Community Ecology and Physiology 1

Yo Sup Moon

5 papers receiving 723 citations

Yo Sup Moon's Hit Papers

Evolutionary dynamics of cancer in response to targeted combination therapy 2013 · 433 citations
4330+4+8Years since publication100200300400

Peers

Yo Sup Moon
Comparison fields: 5 of 105
  • Modeling and Simulation 90
  • Cancer Research 178
  • Cell Biology 127
  • Biophysics 37
  • Oncology 163
Replace Orit Lavi with:
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Yafei Wang China
Steven N. Steinway United States
Antje‐Christine Walz Switzerland
С. В. Вторушин Russia
Erin L. Sausville United States
Satwik Rajaram United States
Arijit Chakravarty United States
Pau Creixell United States
Mohamed Hassanein United States
Yo Sup Moon relative to Orit Lavi United States Orit Lavi's profile →
Citations per field
00.5×2.8×
Orit Lavi · 1×
Citations per year

Countries citing papers authored by Yo Sup Moon

Since Specialization
Citations

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

Fields of papers citing papers by Yo Sup Moon

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yo Sup Moon. 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 Yo Sup Moon. The network helps show where Yo Sup Moon may publish in the future.

Co-authors

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

All Works

5 of 5 papers shown
#Work
1
Evolutionary dynamics of cancer in response to targeted combination therapy
Hit paper breakdown →
2013433
2 2013214
3 202140
4 202235
5 201510

About Yo Sup Moon

Yo Sup Moon is a scholar working on Molecular Biology, Ecology, Cell Biology, Immunology and Modeling and Simulation, having authored 5 papers that have together received 732 indexed citations. Recurring topics across this work include Gene expression and cancer classification (3 papers), Bioinformatics and Genomic Networks (2 papers), Metabolomics and Mass Spectrometry Studies (2 papers), Microfluidic and Bio-sensing Technologies (1 paper), Cancer Genomics and Diagnostics (1 paper), Melanoma and MAPK Pathways (1 paper), Microbial Community Ecology and Physiology (1 paper) and Mathematical Biology Tumor Growth (1 paper). The work is most often cited by research in Modeling and Simulation (90 citations), Cancer Research (178 citations), Cell Biology (127 citations), Biophysics (37 citations) and Oncology (163 citations). Yo Sup Moon has collaborated with scholars based in United States, New Zealand and United Kingdom. Frequent co-authors include Amin Yaqubie, Johannes G. Reiter, Bert Vogelstein, Martin A. Nowak, Tibor Antal, Luis A. Díaz, Ivana Božić, Nicole Kelly, Paul B. Chapman and Evan J. Lipson. Their work appears in journals such as eLife, Science Translational Medicine, PLoS Computational Biology, PeerJ and Bioinformatics.

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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