Maya Gurnani
- Molecular Biology
- Oncology
- Genetics top 10%
- Biotechnology top 5%
- Infectious Diseases top 10%
- Co-authors
- Loretta L. NielsenGerald HajianJanet DellBin ShiPhilip LipariAnthony CacciapuotiRonald D. TylerCarolyn Discafani
- Topics
- Virus-based gene therapy research (10 papers)Cancer Research and Treatments (9 papers)Cancer-related Molecular Pathways (6 papers)
- Cited by
- BiotechnologyOncologyGenetics
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
Maya Gurnani
16 papers receiving 481 citations
Peers
Comparison fields: 5 of 71
- Molecular Biology 227
- Oncology 220
- Genetics 192
- Biotechnology 125
- Infectious Diseases 123
Countries citing papers authored by Maya Gurnani
This map shows the geographic impact of Maya Gurnani'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 Maya Gurnani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maya Gurnani more than expected).
Fields of papers citing papers by Maya Gurnani
This network shows the impact of papers produced by Maya Gurnani. 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 Maya Gurnani. The network helps show where Maya Gurnani may publish in the future.
Co-authorship network of co-authors of Maya Gurnani
This figure shows the co-authorship network connecting the top 25 collaborators of Maya Gurnani. A scholar is included among the top collaborators of Maya Gurnani 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 Maya Gurnani. Maya Gurnani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 6 | |
| 3 | 24 | |
| 4 | 56 | |
| 5 | 45 | |
| 6 | Derivation and initial characterization of a mouse mammary tumor cell line carrying the polyomavirus middle T antigen: utility in the development of novel cancer therapeutics. | 13 |
| 7 | 28 | |
| 8 | Combination therapy with the farnesyl protein transferase inhibitor SCH66336 and SCH58500 (p53 adenovirus) in preclinical cancer models. | 26 |
| 9 | 27 | |
| 10 | 93 | |
| 11 | Adenovirus-mediated p53 gene therapy and paclitaxel have synergistic efficacy in models of human head and neck, ovarian, prostate, and breast cancer. | 103 |
| 12 | 31 | |
| 13 | In wap-ras transgenic mice, tumor phenotype but not cyclophosphamide-sensitivity is affected by genetic background. | 13 |
| 14 | Development of a nude mouse model of ras-mediated neoplasia using WR21 cells from a transgenic mouse salivary tumor. | 3 |
| 15 | Evaluation of the wap-ras transgenic mouse as a model system for testing anticancer drugs. | 11 |
| 16 | Histopathology of salivary and mammary gland tumors in transgenic mice expressing a human Ha-ras oncogene. | 40 |
About Maya Gurnani
Maya Gurnani is a scholar working on Biotechnology, Genetics and Oncology, having authored 16 papers that have together received 523 indexed citations. Recurring topics across this work include Virus-based gene therapy research (10 papers), Cancer Research and Treatments (9 papers) and Cancer-related Molecular Pathways (6 papers). The work is most often cited by research in Biotechnology (125 citations), Oncology (220 citations) and Genetics (192 citations). Maya Gurnani has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Loretta L. Nielsen, Gerald Hajian, Janet Dell, Bin Shi, Philip Lipari, Anthony Cacciapuoti, Ronald D. Tyler, Carolyn Discafani, Paul M. McNicholas and Andrew S. Chau. Their work appears in journals such as Nature Communications, Antimicrobial Agents and Chemotherapy and American Journal Of Pathology.
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.