Daniel J. Laverty
Impact in
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- Cell Image Analysis Techniques
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- DNA Repair Mechanisms
- DNA and Nucleic Acid Chemistry
- CRISPR and Genetic Engineering
Papers in
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- DNA Repair Mechanisms 11
- Single-cell and spatial transcriptomics 3
- CRISPR and Genetic Engineering 3
- Cancer therapeutics and mechanisms 2
- DNA and Nucleic Acid Chemistry 2
- Oncology 7
- Cancer-related Molecular Pathways 3
- PARP inhibition in cancer therapy 2
- Co-authors
- Leo Li‐Ying Chan (4 shared papers)Dmitry Kuksin (4 shared papers)Marc M. Greenberg (5 shared papers)Jean Qiu (3 shared papers)Zachary D. Nagel (7 shared papers)Cortt G. Piett (2 shared papers)Roopali Gandhi (2 shared papers)Hillary Hei (2 shared papers)
- Journals
- Journal of the American Chemical Society (2 papers)Biochemistry (2 papers)Journal of Industrial Microbiology & Biotechnology (1 paper)Progress in Biophysics and Molecular Biology (1 paper)Nature Communications (1 paper)
- Partner nations
- United StatesChinaSwitzerland
In The Last Decade
Daniel J. Laverty
17 papers receiving 201 citations
Peers
Comparison fields: 5 of 67
- Biophysics 20
- Molecular Biology 136
- Oncology 42
- Cancer Research 22
- Genetics 15
Countries citing papers authored by Daniel J. Laverty
This map shows the geographic impact of Daniel J. Laverty'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 Daniel J. Laverty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel J. Laverty more than expected).
Fields of papers citing papers by Daniel J. Laverty
This network shows the impact of papers produced by Daniel J. Laverty. 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 Daniel J. Laverty. The network helps show where Daniel J. Laverty may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel J. Laverty, 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 | 2014 | 52 | |
| 2 | 2012 | 26 | |
| 3 | 2021 | 16 | |
| 4 | 2024 | 14 | |
| 5 | 2021 | 14 | |
| 6 | 2017 | 13 | |
| 7 | 2021 | 11 | |
| 8 | 2024 | 10 | |
| 9 | 2023 | 10 | |
| 10 | 2013 | 10 | |
| 11 | 2018 | 10 | |
| 12 | 2020 | 7 | |
| 13 | 2017 | 7 | |
| 14 | 2018 | 4 | |
| 15 | 2021 | 3 | |
| 16 | 2023 | 1 | |
| 17 | 2013 | 1 |
About Daniel J. Laverty
Daniel J. Laverty is a scholar working on Molecular Biology, Oncology, Biophysics, Genetics and Cancer Research, having authored 17 papers that have together received 209 indexed citations. Recurring topics across this work include DNA Repair Mechanisms (11 papers), Single-cell and spatial transcriptomics (3 papers), Cell Image Analysis Techniques (3 papers), CRISPR and Genetic Engineering (3 papers), Cancer-related Molecular Pathways (3 papers), Cancer therapeutics and mechanisms (2 papers), PARP inhibition in cancer therapy (2 papers) and DNA and Nucleic Acid Chemistry (2 papers). The work is most often cited by research in Biophysics (20 citations), Molecular Biology (136 citations), Oncology (42 citations), Cancer Research (22 citations) and Genetics (15 citations). Daniel J. Laverty has collaborated with scholars based in United States, China and Switzerland. Frequent co-authors include Leo Li‐Ying Chan, Dmitry Kuksin, Marc M. Greenberg, Jean Qiu, Zachary D. Nagel, Cortt G. Piett, Roopali Gandhi, Hillary Hei, Tim Smith and Sylvie Doublié. Their work appears in journals such as Journal of the American Chemical Society, Biochemistry, Journal of Industrial Microbiology & Biotechnology, Progress in Biophysics and Molecular Biology and Nature Communications.
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.