Gabriel Waksman
- Molecular Biology top 0.2%
- Genetics top 0.1%
- Endocrinology top 0.02%
- Ecology top 0.5%
- Molecular Medicine top 0.1%
- Co-authors
- Scott J. HultgrenRémi FronzesHan RemautTimothy M. LohmanJerome S. PinknerTiago R. D. CostaPeter J. ChristieJ. Michael Bradshaw
- Topics
- Bacterial Genetics and Biotechnology (71 papers)Escherichia coli research studies (49 papers)Enzyme Structure and Function (45 papers)
- Partner nations
- United KingdomUnited StatesFrance
In The Last Decade
Gabriel Waksman
218 papers receiving 17.6k citations
Hit Papers
Peers
Comparison fields: 5 of 157
- Molecular Biology 11.2k
- Genetics 4.6k
- Endocrinology 3.8k
- Ecology 2.4k
- Molecular Medicine 1.8k
Countries citing papers authored by Gabriel Waksman
This map shows the geographic impact of Gabriel Waksman'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 Gabriel Waksman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gabriel Waksman more than expected).
Fields of papers citing papers by Gabriel Waksman
This network shows the impact of papers produced by Gabriel Waksman. 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 Gabriel Waksman. The network helps show where Gabriel Waksman may publish in the future.
Co-authorship network of co-authors of Gabriel Waksman
This figure shows the co-authorship network connecting the top 25 collaborators of Gabriel Waksman. A scholar is included among the top collaborators of Gabriel Waksman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Gabriel Waksman. Gabriel Waksman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 0 | |
| 3 | 7 | |
| 4 | 8 | |
| 5 | 57 | |
| 6 | Cryo-EM structure of a type IV secretion systembreakdown → | 72 |
| 7 | 5 | |
| 8 | 42 | |
| 9 | 43 | |
| 10 | 15 | |
| 11 | 9 | |
| 12 | 73 | |
| 13 | 39 | |
| 14 | 32 | |
| 15 | Insights from the energetics binding at the domain-ligand of the Src SH2 domain of water interface | 1 |
| 16 | 69 | |
| 17 | 9 | |
| 18 | 103 | |
| 19 | DNA helicases, motors that move along nucleic acids: lessons from the SF1 helicase superfamily. | 3 |
| 20 | 18 |
About Gabriel Waksman
Gabriel Waksman is a scholar working on Endocrinology, Molecular Medicine and Genetics, having authored 221 papers that have together received 18.0k indexed citations. Recurring topics across this work include Bacterial Genetics and Biotechnology (71 papers), Escherichia coli research studies (49 papers) and Enzyme Structure and Function (45 papers). The work is most often cited by research in Endocrinology (3.8k citations), Molecular Medicine (1.8k citations) and Genetics (4.6k citations). Gabriel Waksman has collaborated with scholars based in United Kingdom, United States and France. Frequent co-authors include Scott J. Hultgren, Rémi Fronzes, Han Remaut, Timothy M. Lohman, Jerome S. Pinkner, Tiago R. D. Costa, Peter J. Christie, J. Michael Bradshaw, Sergey Korolev and Jeffrey I. Gordon. Their work appears in journals such as Nature, Science and Cell.
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.