Dan Hicklin
- Cancer Research top 5%
- Immunology and Allergy top 5%
- Molecular Biology top 5%
- Angiogenesis and VEGF in Cancer 8
- Hematology top 5%
- Acute Myeloid Leukemia Research 2
- Chronic Myeloid Leukemia Treatments 2
- Cell Biology top 5%
- Zebrafish Biomedical Research Applications 3
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- Axon Guidance and Neuronal Signaling 3
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- Monoclonal and Polyclonal Antibodies Research 3
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- Colorectal Cancer Treatments and Studies 2
- HER2/EGFR in Cancer Research 2
Dan Hicklin
20 papers receiving 1.8k citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Cancer Research 423
- Immunology and Allergy 120
- Molecular Biology 1.3k
- Hematology 212
- Cell Biology 295
Countries citing papers authored by Dan Hicklin
This map shows the geographic impact of Dan Hicklin'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 Dan Hicklin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Hicklin more than expected).
Fields of papers citing papers by Dan Hicklin
This network shows the impact of papers produced by Dan Hicklin. 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 Dan Hicklin. The network helps show where Dan Hicklin may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dan Hicklin, 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 | 2021 | 3 | |
| 2 | 2021 | 4 | |
| 3 | 2010 | 0 | |
| 4 | SCH 727965, a novel cyclin-dependent kinase inhibitor, has potent anti-tumor acitivity in a wide-spectrum of human tumor xenograft models | 2008 | 1 |
| 5 | 2007 | 47 | |
| 6 | 2006 | 162 | |
| 7 | 2006 | 3 | |
| 8 | 2006 | 1 | |
| 9 | 2005 | 4 | |
| 10 | 2005 | 3 | |
| 11 | Identification and characterization of a fully human antibody directed against epidermal growth factor receptor for cancer therapy | 2004 | 14 |
| 12 | 2004 | 1 | |
| 13 | 2004 | 1 | |
| 14 | 2004 | 6 | |
| 15 | 2003 | 155 | |
| 16 | 2002 | 301 | |
| 17 | 2002 | 387 | |
| 18 | Antivascular endothelial growth factor receptor (fetal liver kinase 1) monoclonal antibody inhibits tumor angiogenesis and growth of several mouse and human tumors.breakdown → | 1999 | 557 |
| 19 | 1996 | 17 | |
| 20 | 1994 | 167 |
About Dan Hicklin
Dan Hicklin is a scholar working on Toxicology, Hematology and Cell Biology, having authored 21 papers that have together received 1.9k indexed citations. Recurring topics across this work include Angiogenesis and VEGF in Cancer (8 papers), Axon Guidance and Neuronal Signaling (3 papers), Zebrafish Biomedical Research Applications (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), Acute Myeloid Leukemia Research (2 papers), Colorectal Cancer Treatments and Studies (2 papers), Chronic Myeloid Leukemia Treatments (2 papers) and HER2/EGFR in Cancer Research (2 papers). The work is most often cited by research in Cancer Research (423 citations), Immunology and Allergy (120 citations) and Molecular Biology (1.3k citations). Dan Hicklin has collaborated with scholars based in United States, Japan and Germany. Frequent co-authors include Luc de Witte, Yiwen Li, Bronislaw Pytowski, Peter Böhlen, Andrea T. Hooper, Marie Prewett, James C. Overholser, JC Huber, Ángel Santiago and William O’Connor. Their work appears in journals such as Cancer Research, Journal of Clinical Investigation, Molecular Cancer Therapeutics, Blood and Journal of Clinical 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.