Jonathan S. Weissman
Impact in
- Aging top 0.05%
- Molecular Biology top 0.01%
- RNA and protein synthesis mechanisms
- CRISPR and Genetic Engineering
- RNA Research and Splicing
- RNA modifications and cancer
- Fungal and yeast genetics research
- Prion Diseases and Protein Misfolding
Papers in
-
- RNA and protein synthesis mechanisms 89
- CRISPR and Genetic Engineering 65
- RNA Research and Splicing 44
- RNA modifications and cancer 44
- Fungal and yeast genetics research 32
- Prion Diseases and Protein Misfolding 28
- Single-cell and spatial transcriptomics 24
- Cell Biology 55
- Endoplasmic Reticulum Stress and Disease 42
Jonathan S. Weissman
289 papers receiving 77.9k citations
Hit Papers
Peers
Comparison fields: 5 of 201
- Aging 2.3k
- Molecular Biology 67.8k
- Cell Biology 12.2k
- Business and International Management 1.2k
- Cancer Research 7.0k
Countries citing papers authored by Jonathan S. Weissman
This map shows the geographic impact of Jonathan S. Weissman'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 Jonathan S. Weissman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan S. Weissman more than expected).
Fields of papers citing papers by Jonathan S. Weissman
This network shows the impact of papers produced by Jonathan S. Weissman. 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 Jonathan S. Weissman. The network helps show where Jonathan S. Weissman may publish in the future.
Co-authors
The 25 scholars most cited alongside Jonathan S. Weissman, 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 | 2025 | 3 | |
| 2 | 2024 | 2 | |
| 3 | 2023 | 12 | |
| 4 | 2022 | 29 | |
| 5 | 2020 | 24 | |
| 6 | 2020 | 54 | |
| 7 | 2019 | 42 | |
| 8 | 2018 | 60 | |
| 9 | 2017 | 112 | |
| 10 | 2016 | 155 | |
| 11 | 2016 | 27 | |
| 12 | CRISPRi-based genome-scale identification of functional long noncoding RNA loci in human cells Hit paper breakdown → | 2016 | 530 |
| 13 | 2015 | 101 | |
| 14 | 2015 | 229 | |
| 15 | 2015 | 187 | |
| 16 | 2015 | 333 | |
| 17 | Decoding Human Cytomegalovirus Hit paper breakdown → | 2012 | 454 |
| 18 | 2011 | 233 | |
| 19 | Genome-Wide Analysis in Vivo of Translation with Nucleotide Resolution Using Ribosome Profiling Hit paper breakdown → | 2009 | 2763 |
| 20 | An ER-Mitochondria Tethering Complex Revealed by a Synthetic Biology Screen Hit paper breakdown → | 2009 | 1013 |
About Jonathan S. Weissman
Jonathan S. Weissman is a scholar working on Molecular Biology, Cell Biology, Neurology, Cancer Research and Biophysics, having authored 292 papers that have together received 78.7k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (89 papers), CRISPR and Genetic Engineering (65 papers), RNA Research and Splicing (44 papers), RNA modifications and cancer (44 papers), Endoplasmic Reticulum Stress and Disease (42 papers), Fungal and yeast genetics research (32 papers), Prion Diseases and Protein Misfolding (28 papers) and Single-cell and spatial transcriptomics (24 papers). The work is most often cited by research in Aging (2.3k citations), Molecular Biology (67.8k citations), Cell Biology (12.2k citations), Business and International Management (1.2k citations) and Cancer Research (7.0k citations). Jonathan S. Weissman has collaborated with scholars based in United States, Germany and Israel. Frequent co-authors include Nicholas T. Ingolia, Luke A. Gilbert, Lei S. Qi, Sina Ghaemmaghami, Sean R. Collins, Matthew H. Larson, Wendell A. Lim, Erin K. O’Shea, Russell W. Howson and Won‐Ki Huh. Their work appears in journals such as Cell, Science, Nature, eLife and Molecular Cell.
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.