Suhani Vora
Impact in
- Aging top 2%
- Genetics, Aging, and Longevity in Model Organisms
Papers in
-
- CRISPR and Genetic Engineering 5
- RNA Interference and Gene Delivery 3
- RNA regulation and disease 2
- RNA and protein synthesis mechanisms 1
-
- Advanced Vision and Imaging 2
- Advanced Image and Video Retrieval Techniques 2
- Co-authors
- George M. Church (5 shared papers)Alejandro Chavez (4 shared papers)Marcelle Tuttle (4 shared papers)Ron Weiss (3 shared papers)James J. Collins (3 shared papers)Samira Kiani (3 shared papers)Benjamin W. Pruitt (3 shared papers)Dmitry Ter‐Ovanesyan (3 shared papers)
- Journals
- Nature Methods (2 papers)FEBS Journal (1 paper)PLoS ONE (1 paper)Cell (1 paper)DSpace@MIT (Massachusetts Institute of Technology) (1 paper)
- Partner nations
- United StatesCanadaGermany
In The Last Decade
Suhani Vora
9 papers receiving 1.9k citations
Suhani Vora's Hit Papers
Peers
Comparison fields: 5 of 98
- Aging 159
- Business and International Management 113
- Molecular Biology 1.7k
- Computer Graphics and Computer-Aided Design 65
- Cancer Research 193
Countries citing papers authored by Suhani Vora
This map shows the geographic impact of Suhani Vora'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 Suhani Vora with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suhani Vora more than expected).
Fields of papers citing papers by Suhani Vora
This network shows the impact of papers produced by Suhani Vora. 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 Suhani Vora. The network helps show where Suhani Vora may publish in the future.
Co-authors
The 25 scholars most cited alongside Suhani Vora, 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 | Highly efficient Cas9-mediated transcriptional programming Hit paper breakdown → | 2015 | 1245 |
| 2 | 2015 | 256 | |
| 3 | 2018 | 243 | |
| 4 | 2022 | 85 | |
| 5 | 2016 | 62 | |
| 6 | 2023 | 40 | |
| 7 | 2016 | 7 | |
| 8 | Future Semantic Segmentation Using 3D Structure | 2018 | 4 |
| 9 | Cas9 gRNA engineering for genome editing, activation and repression | 2015 | 1 |
About Suhani Vora
Suhani Vora is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Ecology and Computational Mechanics, having authored 9 papers that have together received 1.9k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (5 papers), RNA Interference and Gene Delivery (3 papers), Advanced Vision and Imaging (2 papers), Advanced Image and Video Retrieval Techniques (2 papers), RNA regulation and disease (2 papers), Computer Graphics and Visualization Techniques (2 papers), 3D Shape Modeling and Analysis (1 paper) and RNA and protein synthesis mechanisms (1 paper). The work is most often cited by research in Aging (159 citations), Business and International Management (113 citations), Molecular Biology (1.7k citations), Computer Graphics and Computer-Aided Design (65 citations) and Cancer Research (193 citations). Suhani Vora has collaborated with scholars based in United States, Canada and Germany. Frequent co-authors include George M. Church, Alejandro Chavez, Marcelle Tuttle, Ron Weiss, James J. Collins, Samira Kiani, Benjamin W. Pruitt, Dmitry Ter‐Ovanesyan, Norbert Perrimon and Christopher D. Guzman. Their work appears in journals such as Nature Methods, FEBS Journal, PLoS ONE, Cell and DSpace@MIT (Massachusetts Institute of Technology).
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.