Gaelen T. Hess
- Aging top 5%
- Molecular Biology top 5%
- RNA and protein synthesis mechanisms 8
- CRISPR and Genetic Engineering 7
- Advanced biosensing and bioanalysis techniques 4
- Glycosylation and Glycoproteins Research 2
- Biochemical and Structural Characterization 2
- Immunology top 5%
- interferon and immune responses 2
- Genetics top 5%
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- Bacteriophages and microbial interactions 2
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- Transgenic Plants and Applications 2
- Co-authors
- Michael C. BassikAmy LiKyuho HanDavid W. MorgensEdwin E. JengLingyin LiChristopher RitchieStephen B. Montgomery
- Partner nations
- United StatesSpainGermany
In The Last Decade
Gaelen T. Hess
21 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 111
- Business and International Management 79
- Aging 66
- Molecular Biology 2.1k
- Immunology 466
- Genetics 436
Countries citing papers authored by Gaelen T. Hess
This map shows the geographic impact of Gaelen T. Hess'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 Gaelen T. Hess with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gaelen T. Hess more than expected).
Fields of papers citing papers by Gaelen T. Hess
This network shows the impact of papers produced by Gaelen T. Hess. 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 Gaelen T. Hess. The network helps show where Gaelen T. Hess may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gaelen T. Hess, 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 | 2024 | 1 | |
| 2 | 2022 | 14 | |
| 3 | 2022 | 43 | |
| 4 | 2021 | 89 | |
| 5 | 2020 | 137 | |
| 6 | 2020 | 79 | |
| 7 | 2019 | 16 | |
| 8 | 2019 | 237 | |
| 9 | 2018 | 133 | |
| 10 | 2017 | 211 | |
| 11 | Synergistic drug combinations for cancer identified in a CRISPR screen for pairwise genetic interactionsbreakdown → | 2017 | 368 |
| 12 | 2017 | 175 | |
| 13 | 2017 | 144 | |
| 14 | 2017 | 195 | |
| 15 | Directed evolution using dCas9-targeted somatic hypermutation in mammalian cellsbreakdown → | 2016 | 352 |
| 16 | 2016 | 75 | |
| 17 | 2013 | 42 | |
| 18 | 2012 | 98 | |
| 19 | 2007 | 50 | |
| 20 | 2007 | 6 |
About Gaelen T. Hess
Gaelen T. Hess is a scholar working on Molecular Biology, Immunology and Biotechnology, having authored 21 papers that have together received 2.5k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (8 papers), CRISPR and Genetic Engineering (7 papers), Advanced biosensing and bioanalysis techniques (4 papers), Glycosylation and Glycoproteins Research (2 papers), interferon and immune responses (2 papers), Bacteriophages and microbial interactions (2 papers), Biochemical and Structural Characterization (2 papers) and Transgenic Plants and Applications (2 papers). The work is most often cited by research in Business and International Management (79 citations), Aging (66 citations) and Molecular Biology (2.1k citations). Gaelen T. Hess has collaborated with scholars based in United States, Spain and Germany. Frequent co-authors include Michael C. Bassik, Amy Li, Kyuho Han, David W. Morgens, Edwin E. Jeng, Lingyin Li, Christopher Ritchie, Stephen B. Montgomery, David Yao and Josh Tycko. Their work appears in journals such as Nature, Cell and Proceedings of the National Academy of Sciences.
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.