Phillip Williams
Impact in
- Genetics top 1%
- Virus-based gene therapy research
- Animal Genetics and Reproduction
- Immunology top 2%
- Immunotherapy and Immune Responses
Papers in
-
- Carbon Nanotubes in Composites 15
- Graphene research and applications 4
-
- RNA Interference and Gene Delivery 7
- CRISPR and Genetic Engineering 7
- Co-authors
- Jon A. Wolff (10 shared papers)Chong Wang (1 shared paper)Robert W. Malone (1 shared paper)Gyula Acsádi (1 shared paper)Ágnes Jáni (1 shared paper)Philip L. Felgner (1 shared paper)Martin E. Dowty (2 shared papers)Guofeng Zhang (4 shared papers)
- Journals
- Human Gene Therapy (3 papers)Surgery (2 papers)The American Journal of Surgical Pathology (2 papers)Applied Physics Letters (2 papers)Physical Review Letters (2 papers)
- Partner nations
- United StatesCanadaAustralia
In The Last Decade
Phillip Williams
84 papers receiving 5.7k citations
Phillip Williams's Hit Papers
Peers
Comparison fields: 5 of 172
- Genetics 1.6k
- Immunology 1.1k
- Molecular Biology 3.0k
- Structural Biology 56
- Infectious Diseases 641
Countries citing papers authored by Phillip Williams
This map shows the geographic impact of Phillip 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 Phillip Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Phillip Williams more than expected).
Fields of papers citing papers by Phillip Williams
This network shows the impact of papers produced by Phillip 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 Phillip Williams. The network helps show where Phillip Williams may publish in the future.
Co-authors
The 25 scholars most cited alongside Phillip 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
Showing the 20 most-cited of 92 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Direct Gene Transfer into Mouse Muscle in Vivo Hit paper breakdown → | 1990 | 3202 |
| 2 | 1992 | 234 | |
| 3 | 1995 | 214 | |
| 4 | 2012 | 213 | |
| 5 | 1992 | 166 | |
| 6 | 1988 | 157 | |
| 7 | 2004 | 136 | |
| 8 | 2001 | 120 | |
| 9 | 2001 | 118 | |
| 10 | 2022 | 98 | |
| 11 | 2002 | 97 | |
| 12 | 2007 | 90 | |
| 13 | 2002 | 88 | |
| 14 | 1995 | 76 | |
| 15 | 2010 | 65 | |
| 16 | 2003 | 64 | |
| 17 | 2012 | 61 | |
| 18 | 1997 | 55 | |
| 19 | 1995 | 54 | |
| 20 | 1993 | 54 |
About Phillip Williams
Phillip Williams is a scholar working on Materials Chemistry, Molecular Biology, Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering and Surgery, having authored 92 papers that have together received 6.0k indexed citations. Recurring topics across this work include Carbon Nanotubes in Composites (15 papers), RNA Interference and Gene Delivery (7 papers), Mechanical and Optical Resonators (7 papers), CRISPR and Genetic Engineering (7 papers), Virus-based gene therapy research (6 papers), Space Exploration and Technology (5 papers), Force Microscopy Techniques and Applications (5 papers) and Graphene research and applications (4 papers). The work is most often cited by research in Genetics (1.6k citations), Immunology (1.1k citations), Molecular Biology (3.0k citations), Structural Biology (56 citations) and Infectious Diseases (641 citations). Phillip Williams has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Jon A. Wolff, Chong Wang, Robert W. Malone, Gyula Acsádi, Ágnes Jáni, Philip L. Felgner, Martin E. Dowty, Guofeng Zhang, Shoushu Jiao and S. Washburn. Their work appears in journals such as Human Gene Therapy, Surgery, The American Journal of Surgical Pathology, Applied Physics Letters and Physical Review Letters.
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.