Danielle L. Peacock

1.1k citations
9 papers · 838 indexed · h-index 7
Topics
Cancer, Hypoxia, and Metabolism (6 papers)Radiomics and Machine Learning in Medical Imaging (3 papers)Mathematical Biology Tumor Growth (3 papers)

In The Last Decade

Danielle L. Peacock

9 papers receiving 829 citations

Peers

Danielle L. Peacock
Comparison fields: 5 of 79
  • Molecular Biology 490
  • Cancer Research 295
  • Oncology 187
  • Immunology 156
  • Modeling and Simulation 141
Replace Valter Croci with:
Valter Croci Italy
Anil Korkut United States
Mariangela Russo Italy
Phyllis Wachsberger United States
Edward Curry United Kingdom
Anja Sieber Germany
Bertram Klinger Germany
Jose Lobo United States
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Marlous Hoogstraat Netherlands
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Citations per field
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Citations per year

Countries citing papers authored by Danielle L. Peacock

Since Specialization
Citations

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

Fields of papers citing papers by Danielle L. Peacock

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Danielle L. Peacock. 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 Danielle L. Peacock. The network helps show where Danielle L. Peacock may publish in the future.

Co-authorship network of co-authors of Danielle L. Peacock

This figure shows the co-authorship network connecting the top 25 collaborators of Danielle L. Peacock. A scholar is included among the top collaborators of Danielle L. Peacock 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 Danielle L. Peacock. Danielle L. Peacock is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
#WorkIndexed citations
1 336
2 2
3 43
4 48
5 167
6 13
7 172
8 55
9
A mathematical model for glioma growth and invasion links biological aggressiveness assessed by MRI with hypoxia assessed by FMISO-PET
2

About Danielle L. Peacock

Danielle L. Peacock is a scholar working on Modeling and Simulation, Cancer Research and Genetics, having authored 9 papers that have together received 838 indexed citations. Recurring topics across this work include Cancer, Hypoxia, and Metabolism (6 papers), Radiomics and Machine Learning in Medical Imaging (3 papers) and Mathematical Biology Tumor Growth (3 papers). The work is most often cited by research in Modeling and Simulation (141 citations), Cancer Research (295 citations) and Genetics (134 citations). Danielle L. Peacock has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Tiffany N. Seagroves, Luciana P. Schwab, Thomas P. Lynch, Mauricio J. Reginato, Valerie L. Sodi, John N. Falcone, Christina M. Ferrer, David J. Vocadlo, Jesse Ingels and Keisha Smith. Their work appears in journals such as Molecular Cell, Cancer Research and American Journal Of Pathology.

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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