Ted Natoli

1.7k citations
10 papers · 495 · 1 hit paper · h-index 6

Impact in

  • Biophysics top 5%
    • Cell Image Analysis Techniques
    • Cancer, Hypoxia, and Metabolism
    • Cancer Genomics and Diagnostics

Papers in

Ted Natoli

9 papers receiving 490 citations

Ted Natoli's Hit Papers

A metastasis map of human cancer cell lines 2020 · 272 citations
2720+2+4Years since publication50100150200250

Peers

Ted Natoli
Comparison fields: 5 of 85
  • Biophysics 54
  • Cancer Research 139
  • Molecular Biology 328
  • Oncology 123
  • Aging 7
Replace Jia-Yun Chen with:
Jia-Yun Chen China
Amanpreet Kaur Finland
Emanuel Gonçalves United Kingdom
Hayley E. Francies United Kingdom
Maximilian Billmann Germany
Mike Firth United Kingdom
Sander Mertens Netherlands
Luwei Liu United States
Betina Kerstin Lundholt Denmark
Tea Pemovska Finland
Ted Natoli relative to Jia-Yun Chen China Jia-Yun Chen's profile →
Citations per field
00.5×1.6×
Jia-Yun Chen · 1×
Citations per year

Countries citing papers authored by Ted Natoli

Since Specialization
Citations

This map shows the geographic impact of Ted 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 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 Natoli more than expected).

Fields of papers citing papers by Ted Natoli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

10 of 10 papers shown
#Work
1
A metastasis map of human cancer cell lines
Hit paper breakdown →
2020272
2 2017128
3 202255
4 201918
5 20198
6 20227
7 20223
8 20183
9 20211
10 20210

About Ted Natoli

Ted Natoli is a scholar working on Molecular Biology, Computational Theory and Mathematics, Pulmonary and Respiratory Medicine, Spectroscopy and Cancer Research, having authored 10 papers that have together received 495 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (3 papers), Computational Drug Discovery Methods (3 papers), Ferroptosis and cancer prognosis (2 papers), Bioinformatics and Genomic Networks (2 papers), Gene expression and cancer classification (2 papers), Cancer Genomics and Diagnostics (1 paper), Cell Image Analysis Techniques (1 paper) and Diabetes Management and Research (1 paper). The work is most often cited by research in Biophysics (54 citations), Cancer Research (139 citations), Molecular Biology (328 citations), Oncology (123 citations) and Aging (7 citations). Ted Natoli has collaborated with scholars based in United States, Switzerland and India. Frequent co-authors include Todd R. Golub, Aravind Subramanian, Andrew Tang, Matthew G. Vander Heiden, Clary B. Clish, L Petronio, Rakesh K. Jain, Kwanghun Chung, Cong Zhu and Vamsi Mangena. Their work appears in journals such as Toxicological Sciences, PLoS Biology, Genes & Diseases, Bioinformatics and Nature.

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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