Kyle S. Sanchez
Impact in
- Health Informatics top 10%
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- Computational Drug Discovery Methods
Papers in
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- Bioinformatics and Genomic Networks 2
- Genetics, Bioinformatics, and Biomedical Research 2
- Genomics and Chromatin Dynamics 1
- Epigenetics and DNA Methylation 1
- Cancer-related gene regulation 1
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- Computational Drug Discovery Methods 4
- Co-authors
- Trey Ideker (6 shared papers)Jason F. Kreisberg (6 shared papers)Samson Fong (4 shared papers)Brent M. Kuenzi (4 shared papers)Jisoo Park (2 shared papers)Jianzhu Ma (2 shared papers)John J. Y. Lee (2 shared papers)Katherine Licon (4 shared papers)
- Journals
- Nature Genetics (2 papers)Cancer Research (2 papers)Molecular Cancer Therapeutics (1 paper)Cancer Cell (1 paper)
- Partner nations
- United States
In The Last Decade
Kyle S. Sanchez
6 papers receiving 448 citations
Kyle S. Sanchez's Hit Papers
Peers
Comparison fields: 5 of 69
- Health Informatics 13
- Computational Theory and Mathematics 122
- Cancer Research 82
- Biophysics 24
- Molecular Biology 248
Countries citing papers authored by Kyle S. Sanchez
This map shows the geographic impact of Kyle S. Sanchez'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 Kyle S. Sanchez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kyle S. Sanchez more than expected).
Fields of papers citing papers by Kyle S. Sanchez
This network shows the impact of papers produced by Kyle S. Sanchez. 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 Kyle S. Sanchez. The network helps show where Kyle S. Sanchez may publish in the future.
Co-authors
The 25 scholars most cited alongside Kyle S. Sanchez, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells Hit paper breakdown → | 2020 | 308 |
| 2 | 2018 | 88 | |
| 3 | 2018 | 50 | |
| 4 | 2024 | 6 | |
| 5 | 2020 | 2 | |
| 6 | 2021 | 1 |
About Kyle S. Sanchez
Kyle S. Sanchez is a scholar working on Molecular Biology, Computational Theory and Mathematics, Biophysics, Otorhinolaryngology and Aging, having authored 6 papers that have together received 455 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (4 papers), Cell Image Analysis Techniques (3 papers), Bioinformatics and Genomic Networks (2 papers), Genetics, Bioinformatics, and Biomedical Research (2 papers), Genomics and Chromatin Dynamics (1 paper), Epigenetics and DNA Methylation (1 paper), Head and Neck Cancer Studies (1 paper) and Cancer-related gene regulation (1 paper). The work is most often cited by research in Health Informatics (13 citations), Computational Theory and Mathematics (122 citations), Cancer Research (82 citations), Biophysics (24 citations) and Molecular Biology (248 citations). Kyle S. Sanchez has collaborated with scholars based in United States. Frequent co-authors include Trey Ideker, Jason F. Kreisberg, Samson Fong, Brent M. Kuenzi, Jisoo Park, Jianzhu Ma, John J. Y. Lee, Katherine Licon, Ana Bojorquez-Gomez and John Paul Shen. Their work appears in journals such as Nature Genetics, Cancer Research, Molecular Cancer Therapeutics 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.