John J. Y. Lee

2.3k citations
10 papers · 345 indexed · 1 hit paper · h-index 6
Topics
Cancer Genomics and Diagnostics (3 papers)Computational Drug Discovery Methods (2 papers)Cell Image Analysis Techniques (2 papers)

In The Last Decade

John J. Y. Lee

10 papers receiving 336 citations

Hit Papers

Predicting Drug Response and Synergy Using a Deep Learnin...2020202620222024202050100150200250

Peers

John J. Y. Lee
Comparison fields: 5 of 67
  • Molecular Biology 195
  • Computational Theory and Mathematics 134
  • Cancer Research 59
  • Artificial Intelligence 45
  • Materials Chemistry 36
Replace Kyle S. Sanchez with:
Kyle S. Sanchez United States
George Alexandru Adam Canada
Mingkun Lu China
Somayah Albaradei Saudi Arabia
Peiran Jiang China
Yuqi Wen China
Evangelos Hytopoulos United States
Kristina Preuer Austria
Suleiman A. Khan Finland
Daniil Polykovskiy Russia
John J. Y. Lee relative to Kyle S. Sanchez United States Kyle S. Sanchez's profile →
Citations per field
00.5×1.5×
Kyle S. Sanchez · 1×
Citations per year

Countries citing papers authored by John J. Y. Lee

Since Specialization
Citations

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

Fields of papers citing papers by John J. Y. Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John J. Y. Lee. 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 John J. Y. Lee. The network helps show where John J. Y. Lee may publish in the future.

Co-authorship network of co-authors of John J. Y. Lee

This figure shows the co-authorship network connecting the top 25 collaborators of John J. Y. Lee. A scholar is included among the top collaborators of John J. Y. Lee based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with John J. Y. Lee. John J. Y. Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
#WorkIndexed citations
1 1
2 20
3 5
4 1
5 3
6 9
7
Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cellsbreakdown →
285
8 1
9 7
10 13

About John J. Y. Lee

John J. Y. Lee is a scholar working on Aging, Biophysics and Cancer Research, having authored 10 papers that have together received 345 indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (3 papers), Computational Drug Discovery Methods (2 papers) and Cell Image Analysis Techniques (2 papers). The work is most often cited by research in Health Informatics (17 citations), Computational Theory and Mathematics (134 citations) and Biophysics (26 citations). John J. Y. Lee has collaborated with scholars based in Canada, United States and South Korea. Frequent co-authors include Trey Ideker, Samson Fong, Jisoo Park, Jason F. Kreisberg, Brent M. Kuenzi, Kyle S. Sanchez, Jianzhu Ma, Wayne Tymchak, Jennifer Rutledge and Abhay Divekar. Their work appears in journals such as Nature Communications, Nature Genetics and Cancer Cell.

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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