Starr Hazard
Impact in
- Aging top 10%
-
- Protein Kinase Regulation and GTPase Signaling
- Receptor Mechanisms and Signaling
- Glycosylation and Glycoproteins Research
Papers in
-
- Protein Kinase Regulation and GTPase Signaling 4
- Receptor Mechanisms and Signaling 3
- Metabolism, Diabetes, and Cancer 2
- Glycosylation and Glycoproteins Research 2
- PI3K/AKT/mTOR signaling in cancer 2
- Machine Learning in Bioinformatics 1
- Surgery 4
- Cholesterol and Lipid Metabolism 3
- Co-authors
- Stephen M. Lanier (3 shared papers)Shailendra B. Patel (3 shared papers)Michael L. Bernard (2 shared papers)Yuri K. Peterson (3 shared papers)Stephen G. Graber (2 shared papers)Peter Chung (1 shared paper)Mary J. Cismowski (1 shared paper)Aya Takesono (1 shared paper)
- Journals
- Journal of Biological Chemistry (5 papers)Journal of Lipid Research (1 paper)Biomaterials (1 paper)Pflügers Archiv - European Journal of Physiology (1 paper)Bioorganic & Medicinal Chemistry (1 paper)
- Partner nations
- United StatesSouth KoreaMyanmar
In The Last Decade
Starr Hazard
11 papers receiving 741 citations
Peers
Comparison fields: 5 of 89
- Aging 23
- Molecular Biology 490
- Cell Biology 109
- Immunology 123
- Immunology and Allergy 35
Countries citing papers authored by Starr Hazard
This map shows the geographic impact of Starr Hazard'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 Starr Hazard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Starr Hazard more than expected).
Fields of papers citing papers by Starr Hazard
This network shows the impact of papers produced by Starr Hazard. 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 Starr Hazard. The network helps show where Starr Hazard may publish in the future.
Co-authors
The 25 scholars most cited alongside Starr Hazard, 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 | 1999 | 242 | |
| 2 | 2000 | 117 | |
| 3 | 2006 | 82 | |
| 4 | 2006 | 80 | |
| 5 | 2001 | 66 | |
| 6 | 2001 | 56 | |
| 7 | 2002 | 46 | |
| 8 | 2006 | 28 | |
| 9 | 2014 | 17 | |
| 10 | 2005 | 11 | |
| 11 | 2006 | 4 |
About Starr Hazard
Starr Hazard is a scholar working on Molecular Biology, Surgery, Oncology, Immunology and Cellular and Molecular Neuroscience, having authored 11 papers that have together received 749 indexed citations. Recurring topics across this work include Protein Kinase Regulation and GTPase Signaling (4 papers), Cholesterol and Lipid Metabolism (3 papers), Drug Transport and Resistance Mechanisms (3 papers), Receptor Mechanisms and Signaling (3 papers), Metabolism, Diabetes, and Cancer (2 papers), Glycosylation and Glycoproteins Research (2 papers), PI3K/AKT/mTOR signaling in cancer (2 papers) and Machine Learning in Bioinformatics (1 paper). The work is most often cited by research in Aging (23 citations), Molecular Biology (490 citations), Cell Biology (109 citations), Immunology (123 citations) and Immunology and Allergy (35 citations). Starr Hazard has collaborated with scholars based in United States, South Korea and Myanmar. Frequent co-authors include Stephen M. Lanier, Shailendra B. Patel, Michael L. Bernard, Yuri K. Peterson, Stephen G. Graber, Peter Chung, Mary J. Cismowski, Aya Takesono, Catalina Ribas and Emir Duzic. Their work appears in journals such as Journal of Biological Chemistry, Journal of Lipid Research, Biomaterials, Pflügers Archiv - European Journal of Physiology and Bioorganic & Medicinal Chemistry.
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.