Ted E. Natoli
Impact in
- Cancer Research top 10%
- Cancer Genomics and Diagnostics
- Biophysics top 5%
- Cell Image Analysis Techniques
Papers in
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- Cancer Genomics and Diagnostics 3
-
- Advanced Proteomics Techniques and Applications 2
- Co-authors
- Todd R. Golub (2 shared papers)Aravind N. Subramanian (5 shared papers)Xin Jin (1 shared paper)Jennifer A. Roth (1 shared paper)Kwanghun Chung (1 shared paper)Amy Deik (1 shared paper)Ahmed Ali (1 shared paper)Vamsi Mangena (1 shared paper)
- Journals
- Cell Systems (2 papers)Cancer Cell (2 papers)Nature (1 paper)ACS Chemical Biology (1 paper)Environmental Health Perspectives (1 paper)
- Partner nations
- United StatesIndia
In The Last Decade
Ted E. Natoli
15 papers receiving 1.1k citations
Ted E. Natoli's Hit Papers
Peers
Comparison fields: 5 of 102
- Cancer Research 265
- Biophysics 89
- Molecular Biology 694
- Oncology 220
- Aging 11
Countries citing papers authored by Ted E. Natoli
This map shows the geographic impact of Ted E. Natoli'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 Ted E. Natoli with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ted E. Natoli more than expected).
Fields of papers citing papers by Ted E. Natoli
This network shows the impact of papers produced by Ted E. Natoli. 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 Ted E. Natoli. The network helps show where Ted E. Natoli may publish in the future.
Co-authors
The 25 scholars most cited alongside Ted E. Natoli, 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 | A metastasis map of human cancer cell lines Hit paper breakdown → | 2020 | 325 |
| 2 | 2016 | 169 | |
| 3 | 2017 | 133 | |
| 4 | 2016 | 130 | |
| 5 | Chronic inflammation, neutrophil activity, and autoreactivity splits long COVID Hit paper breakdown → | 2023 | 95 |
| 6 | 2014 | 75 | |
| 7 | 2022 | 69 | |
| 8 | 2018 | 68 | |
| 9 | 2019 | 18 | |
| 10 | 2017 | 18 | |
| 11 | 2022 | 12 | |
| 12 | 2022 | 11 | |
| 13 | 2019 | 10 | |
| 14 | 2022 | 3 | |
| 15 | 2021 | 1 |
About Ted E. Natoli
Ted E. Natoli is a scholar working on Cancer Research, Spectroscopy, Molecular Biology, Pulmonary and Respiratory Medicine and Computational Theory and Mathematics, having authored 15 papers that have together received 1.1k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (3 papers), Advanced Proteomics Techniques and Applications (2 papers), Computational Drug Discovery Methods (2 papers), Protein Degradation and Inhibitors (2 papers), Single-cell and spatial transcriptomics (2 papers), Lung Cancer Treatments and Mutations (2 papers), CRISPR and Genetic Engineering (1 paper) and COVID-19 Clinical Research Studies (1 paper). The work is most often cited by research in Cancer Research (265 citations), Biophysics (89 citations), Molecular Biology (694 citations), Oncology (220 citations) and Aging (11 citations). Ted E. Natoli has collaborated with scholars based in United States and India. Frequent co-authors include Todd R. Golub, Aravind N. Subramanian, Xin Jin, Jennifer A. Roth, Kwanghun Chung, Amy Deik, Ahmed Ali, Vamsi Mangena, Li Wang and Matthew G. Vander Heiden. Their work appears in journals such as Cell Systems, Cancer Cell, Nature, ACS Chemical Biology and Environmental Health Perspectives.
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.