Ryan A. Pak
Impact in
- Aging top 5%
- Molecular Biology top 10%
- CRISPR and Genetic Engineering
- Single-cell and spatial transcriptomics
- RNA and protein synthesis mechanisms
- Pluripotent Stem Cells Research
- RNA Research and Splicing
- Gene Regulatory Network Analysis
- Advanced biosensing and bioanalysis techniques
Papers in
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- CRISPR and Genetic Engineering 3
- Advanced biosensing and bioanalysis techniques 2
- Ubiquitin and proteasome pathways 1
- RNA Interference and Gene Delivery 1
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- Microtubule and mitosis dynamics 1
- Co-authors
- Jonathan S. Weissman (4 shared papers)Luke A. Gilbert (3 shared papers)Yuwen Chen (2 shared papers)Max A. Horlbeck (2 shared papers)Jacqueline E. Villalta (2 shared papers)Britt Adamson (2 shared papers)Martin Kampmann (2 shared papers)Jacob E. Corn (1 shared paper)
- Journals
- Proceedings of the National Academy of Sciences (2 papers)eLife (2 papers)Cell (1 paper)Neuron (1 paper)
- Partner nations
- United States
In The Last Decade
Ryan A. Pak
6 papers receiving 1.4k citations
Ryan A. Pak's Hit Papers
Peers
Comparison fields: 5 of 74
- Aging 58
- Molecular Biology 1.1k
- Biophysics 75
- Business and International Management 23
- Cancer Research 133
Countries citing papers authored by Ryan A. Pak
This map shows the geographic impact of Ryan A. Pak'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 Ryan A. Pak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryan A. Pak more than expected).
Fields of papers citing papers by Ryan A. Pak
This network shows the impact of papers produced by Ryan A. Pak. 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 Ryan A. Pak. The network helps show where Ryan A. Pak may publish in the future.
Co-authors
The 25 scholars most cited alongside Ryan A. Pak, 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 | A Multiplexed Single-Cell CRISPR Screening Platform Enables Systematic Dissection of the Unfolded Protein Response Hit paper breakdown → | 2016 | 721 |
| 2 | Compact and highly active next-generation libraries for CRISPR-mediated gene repression and activation Hit paper breakdown → | 2016 | 547 |
| 3 | 2016 | 65 | |
| 4 | 2022 | 62 | |
| 5 | 2022 | 17 | |
| 6 | 2024 | 12 |
About Ryan A. Pak
Ryan A. Pak is a scholar working on Molecular Biology, Cell Biology, Genetics, Neurology and Cardiology and Cardiovascular Medicine, having authored 6 papers that have together received 1.4k indexed citations. Recurring topics across this work include CRISPR and Genetic Engineering (3 papers), Advanced biosensing and bioanalysis techniques (2 papers), Blood properties and coagulation (1 paper), Ubiquitin and proteasome pathways (1 paper), Amyotrophic Lateral Sclerosis Research (1 paper), Neurogenetic and Muscular Disorders Research (1 paper), Microtubule and mitosis dynamics (1 paper) and RNA Interference and Gene Delivery (1 paper). The work is most often cited by research in Aging (58 citations), Molecular Biology (1.1k citations), Biophysics (75 citations), Business and International Management (23 citations) and Cancer Research (133 citations). Ryan A. Pak has collaborated with scholars based in United States. Frequent co-authors include Jonathan S. Weissman, Luke A. Gilbert, Yuwen Chen, Max A. Horlbeck, Jacqueline E. Villalta, Britt Adamson, Martin Kampmann, Jacob E. Corn, Chong Yon Park and Alexander P. Fields. Their work appears in journals such as Proceedings of the National Academy of Sciences, eLife, Cell and Neuron.
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.