Jay Shendure
- Genetics top 0.01%
- Genomics and Rare Diseases 26
- Cancer Research top 0.05%
- Molecular Biology top 0.02%
- RNA and protein synthesis mechanisms 55
- Genomics and Chromatin Dynamics 54
- Single-cell and spatial transcriptomics 51
- Genomics and Phylogenetic Studies 51
- CRISPR and Genetic Engineering 44
- RNA Research and Splicing 38
- RNA modifications and cancer 31
- Aging top 0.2%
- Biophysics top 0.1%
- Co-authors
- Hanlee P. JiMartin KircherGregory M. CooperDaniela WittenBrian J. O’RoakCole TrapnellRiza M. DazaCholi Lee
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Jay Shendure
291 papers receiving 51.6k citations
Hit Papers
Peers
Comparison fields: 5 of 207
- Genetics 17.1k
- Cancer Research 8.2k
- Molecular Biology 36.0k
- Aging 598
- Biophysics 1.4k
Countries citing papers authored by Jay Shendure
This map shows the geographic impact of Jay Shendure'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 Jay Shendure with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Shendure more than expected).
Fields of papers citing papers by Jay Shendure
This network shows the impact of papers produced by Jay Shendure. 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 Jay Shendure. The network helps show where Jay Shendure may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jay Shendure, 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 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 5 | |
| 4 | 2022 | 45 | |
| 5 | 2022 | 16 | |
| 6 | 2021 | 36 | |
| 7 | 2021 | 16 | |
| 8 | 2021 | 170 | |
| 9 | 2019 | 129 | |
| 10 | 2019 | 198 | |
| 11 | 2019 | 19 | |
| 12 | 2018 | 50 | |
| 13 | 2017 | 380 | |
| 14 | Whole-organism lineage tracing by combinatorial and cumulative genome editingbreakdown → | 2016 | 477 |
| 15 | 2016 | 218 | |
| 16 | 2016 | 81 | |
| 17 | 2013 | 29 | |
| 18 | 2013 | 127 | |
| 19 | Analysis of Genetic Inheritance in a Family Quartet by Whole-Genome Sequencingbreakdown → | 2010 | 722 |
| 20 | Accurate Multiplex Polony Sequencing of an Evolved Bacterial Genomebreakdown → | 2005 | 860 |
About Jay Shendure
Jay Shendure is a scholar working on Aging, Molecular Biology and Genetics, having authored 297 papers that have together received 52.4k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (55 papers), Genomics and Chromatin Dynamics (54 papers), Single-cell and spatial transcriptomics (51 papers), Genomics and Phylogenetic Studies (51 papers), CRISPR and Genetic Engineering (44 papers), RNA Research and Splicing (38 papers), RNA modifications and cancer (31 papers) and Genomics and Rare Diseases (26 papers). The work is most often cited by research in Genetics (17.1k citations), Cancer Research (8.2k citations) and Molecular Biology (36.0k citations). Jay Shendure has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Hanlee P. Ji, Martin Kircher, Gregory M. Cooper, Daniela Witten, Brian J. O’Roak, Cole Trapnell, Riza M. Daza, Choli Lee, Andrew C. Adey and Deborah A. Nickerson. Their work appears in journals such as Nature, Science, Nature Biotechnology, Nature Genetics and Nature Communications.
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.