Danielle Maeser
Impact in
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
- Cancer, Lipids, and Metabolism
- Cancer Genomics and Diagnostics
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- Ferroptosis and cancer prognosis
Papers in
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- Single-cell and spatial transcriptomics 5
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- Cell Image Analysis Techniques 5
- Co-authors
- R. Stephanie Huang (7 shared papers)Robert F. Gruener (7 shared papers)Ankush Patel (1 shared paper)Yingbo Huang (2 shared papers)Adam M. Lee (3 shared papers)Anand G. Patel (1 shared paper)Tomoyuki Koga (2 shared papers)Frank B. Furnari (2 shared papers)
- Journals
- Cancers (2 papers)Cancer Research (2 papers)Pharmaceuticals (1 paper)Briefings in Bioinformatics (1 paper)Neuro-Oncology (1 paper)
- Partner nations
- United StatesEgypt
In The Last Decade
Danielle Maeser
9 papers receiving 998 citations
Danielle Maeser's Hit Papers
Peers
Comparison fields: 5 of 62
- Cancer Research 423
- Pulmonary and Respiratory Medicine 597
- Oncology 317
- Immunology 175
- Molecular Biology 558
Countries citing papers authored by Danielle Maeser
This map shows the geographic impact of Danielle Maeser'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 Maeser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle Maeser more than expected).
Fields of papers citing papers by Danielle Maeser
This network shows the impact of papers produced by Danielle Maeser. 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 Maeser. The network helps show where Danielle Maeser may publish in the future.
Co-authors
The 11 scholars most cited alongside Danielle Maeser, 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 | oncoPredict: an R package for predicting in vivo or cancer patient drug response and biomarkers from cell line screening data Hit paper breakdown → | 2021 | 971 |
| 2 | 2024 | 15 | |
| 3 | 2023 | 7 | |
| 4 | 2024 | 3 | |
| 5 | 2024 | 3 | |
| 6 | 2024 | 2 | |
| 7 | 2023 | 1 | |
| 8 | Sunlight Exposure, Vitamin D Synthesis, and Multiple Sclerosis in the Northern and Southern Regions of the United States | 2018 | 1 |
| 9 | 2021 | 1 | |
| 10 | 2021 | 0 |
About Danielle Maeser
Danielle Maeser is a scholar working on Molecular Biology, Biophysics, Genetics, Pulmonary and Respiratory Medicine and Neurology, having authored 10 papers that have together received 1.0k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (5 papers), Cell Image Analysis Techniques (5 papers), Glioma Diagnosis and Treatment (3 papers), Cancer Genomics and Diagnostics (2 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers), Prostate Cancer Treatment and Research (1 paper), Spaceflight effects on biology (1 paper) and Immune cells in cancer (1 paper). The work is most often cited by research in Cancer Research (423 citations), Pulmonary and Respiratory Medicine (597 citations), Oncology (317 citations), Immunology (175 citations) and Molecular Biology (558 citations). Danielle Maeser has collaborated with scholars based in United States and Egypt. Frequent co-authors include R. Stephanie Huang, Robert F. Gruener, Ankush Patel, Yingbo Huang, Adam M. Lee, Anand G. Patel, Tomoyuki Koga, Frank B. Furnari, David A. Largaespada and Clark C. Chen. Their work appears in journals such as Cancers, Cancer Research, Pharmaceuticals, Briefings in Bioinformatics and Neuro-Oncology.
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.