Sun Cho

17 papers receiving 284 citations

Sun Cho's Hit Papers

Detection of ovarian cancer via the spectral fingerprinting of quantum-defect-modified carbon nanotubes in serum by machine learning 2022 · 151 citations
1510+1+2Years since publication50100150

Peers

Sun Cho
Comparison fields: 5 of 69
  • Molecular Medicine 23
  • Hematology 46
  • Endocrinology 19
  • Bioengineering 9
  • Molecular Biology 96
Replace Marta Sevieri with:
Marta Sevieri Italy
Genki Nakamura Japan
Patricia Gravel Switzerland
Trisha Tucholski United States
William E. Fondrie United States
Pranavanand Nyshadham United States
Melinda S. Hanes United States
Daniel Carbajo Spain
David Bienvenue United States
Nick Davis United States
Sun Cho relative to Marta Sevieri Italy Marta Sevieri's profile →
Citations per field
00.5×10×14×
Marta Sevieri · 1×
Citations per year

Countries citing papers authored by Sun Cho

Since Specialization
Citations

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

Fields of papers citing papers by Sun Cho

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

19 of 19 papers shown
#Work
1
Detection of ovarian cancer via the spectral fingerprinting of quantum-defect-modified carbon nanotubes in serum by machine learning
Hit paper breakdown →
2022151
2 201939
3 201724
4 200722
5 200412
6 20158
7 20187
8 20195
9 20194
10
Survey of Expressed Sequence Tags from Tissue-Specific cDNA Libraries in Hemibarbus mylodon, an Endangered Fish Species
20073
11 20213
12 20202
13 20172
14 20221
15 20231
16 20201
17 20141
18 20260
19 20210

About Sun Cho

Sun Cho is a scholar working on Oncology, Molecular Biology, Hematology, Cardiology and Cardiovascular Medicine and Epidemiology, having authored 19 papers that have together received 286 indexed citations. Recurring topics across this work include Inflammatory Biomarkers in Disease Prognosis (4 papers), Multiple Myeloma Research and Treatments (2 papers), Advanced Proteomics Techniques and Applications (1 paper), Animal Genetics and Reproduction (1 paper), S100 Proteins and Annexins (1 paper), Vasculitis and related conditions (1 paper), Adenosine and Purinergic Signaling (1 paper) and Hematopoietic Stem Cell Transplantation (1 paper). The work is most often cited by research in Molecular Medicine (23 citations), Hematology (46 citations), Endocrinology (19 citations), Bioengineering (9 citations) and Molecular Biology (96 citations). Sun Cho has collaborated with scholars based in United States and South Korea. Frequent co-authors include Katie Thoren, Daniel A. Heller, Anand Jagota, Lakshmi V. Ramanathan, J. Justin Mulvey, Hong‐Bin Luo, Yoona Yang, Ming Zheng, YuHuang Wang and Peng Wang. Their work appears in journals such as Oncology Reports, Nature Biomedical Engineering, Blood, Clinica Chimica Acta and Clinical Biochemistry.

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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