Danielle M. Williams
Impact in
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- Alzheimer's disease research and treatments
Papers in
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- Biochemical and Structural Characterization 3
- 14-3-3 protein interactions 2
- Phytochemical compounds biological activities 2
- Protein Structure and Dynamics 2
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- Advanced Glycation End Products research 2
- Co-authors
- John A. Carver (5 shared papers)Tara L. Pukala (2 shared papers)Lynne Regan (5 shared papers)Heath Ecroyd (3 shared papers)Francis C. Dehle (1 shared paper)Ian Musgrave (1 shared paper)Yanqin Liu (1 shared paper)David C. Thorn (2 shared papers)
- Journals
- ACS Applied Nano Materials (1 paper)PLoS ONE (1 paper)Tectonophysics (1 paper)Biopolymers (1 paper)CNS Spectrums (1 paper)
- Partner nations
- United StatesUnited KingdomAustralia
In The Last Decade
Danielle M. Williams
16 papers receiving 485 citations
Peers
Comparison fields: 5 of 95
- Molecular Medicine 21
- Physiology 99
- Biomaterials 51
- Food Science 69
- Biochemistry 21
Countries citing papers authored by Danielle M. Williams
This map shows the geographic impact of Danielle M. Williams'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 M. Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Danielle M. Williams more than expected).
Fields of papers citing papers by Danielle M. Williams
This network shows the impact of papers produced by Danielle M. Williams. 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 M. Williams. The network helps show where Danielle M. Williams may publish in the future.
Co-authors
The 25 scholars most cited alongside Danielle M. Williams, 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 | 2013 | 108 | |
| 2 | 2008 | 69 | |
| 3 | 2016 | 45 | |
| 4 | 2007 | 38 | |
| 5 | 2018 | 36 | |
| 6 | 2015 | 36 | |
| 7 | 2013 | 36 | |
| 8 | 2011 | 27 | |
| 9 | 2016 | 20 | |
| 10 | 2011 | 14 | |
| 11 | 2007 | 13 | |
| 12 | 2018 | 13 | |
| 13 | 2021 | 12 | |
| 14 | 2017 | 11 | |
| 15 | 2018 | 6 | |
| 16 | 2000 | 5 |
About Danielle M. Williams
Danielle M. Williams is a scholar working on Molecular Biology, Clinical Biochemistry, Biomaterials, Geophysics and Radiology, Nuclear Medicine and Imaging, having authored 16 papers that have together received 489 indexed citations. Recurring topics across this work include Biochemical and Structural Characterization (3 papers), Alzheimer's disease research and treatments (2 papers), 14-3-3 protein interactions (2 papers), Phytochemical compounds biological activities (2 papers), Protein Structure and Dynamics (2 papers), Advanced Glycation End Products research (2 papers), Garlic and Onion Studies (2 papers) and Monoclonal and Polyclonal Antibodies Research (2 papers). The work is most often cited by research in Molecular Medicine (21 citations), Physiology (99 citations), Biomaterials (51 citations), Food Science (69 citations) and Biochemistry (21 citations). Danielle M. Williams has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include John A. Carver, Tara L. Pukala, Lynne Regan, Heath Ecroyd, Francis C. Dehle, Ian Musgrave, Yanqin Liu, David C. Thorn, Glyn L. Devlin and Peter Hoffmann. Their work appears in journals such as ACS Applied Nano Materials, PLoS ONE, Tectonophysics, Biopolymers and CNS Spectrums.
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.