Jay Shendure
Impact in
- Genetics top 0.01%
- Genomics and Rare Diseases
- Genomic variations and chromosomal abnormalities
- Cancer Research top 0.05%
- Cancer Genomics and Diagnostics
Papers in
-
- RNA and protein synthesis mechanisms 54
- Genomics and Chromatin Dynamics 52
- Single-cell and spatial transcriptomics 51
- Genomics and Phylogenetic Studies 48
- CRISPR and Genetic Engineering 44
- RNA Research and Splicing 34
- RNA modifications and cancer 28
- Genetics 94
- Genomics and Rare Diseases 27
- Co-authors
- Hanlee P. Ji (1 shared paper)Martin Kircher (25 shared papers)Gregory M. Cooper (7 shared papers)Daniela Witten (5 shared papers)Brian J. O’Roak (14 shared papers)Cole Trapnell (30 shared papers)Riza M. Daza (31 shared papers)Choli Lee (37 shared papers)
- Journals
- Nature (19 papers)Science (17 papers)Nature Genetics (16 papers)Nature Biotechnology (15 papers)Nature Communications (14 papers)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Jay Shendure
297 papers receiving 55.0k citations
Jay Shendure's Hit Papers
Peers
Comparison fields: 5 of 211
- Genetics 16.7k
- Cancer Research 7.8k
- Molecular Biology 35.2k
- Aging 608
- Biophysics 1.3k
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-authors
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
Showing the 20 most-cited of 305 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A general framework for estimating the relative pathogenicity of human genetic variants Hit paper breakdown → | 2014 | 3741 |
| 2 | Next-generation DNA sequencing Hit paper breakdown → | 2008 | 3240 |
| 3 | The single-cell transcriptional landscape of mammalian organogenesis Hit paper breakdown → | 2019 | 2361 |
| 4 | CADD: predicting the deleteriousness of variants throughout the human genome Hit paper breakdown → | 2018 | 2008 |
| 5 | Targeted capture and massively parallel sequencing of 12 human exomes Hit paper breakdown → | 2009 | 1419 |
| 6 | Exome sequencing identifies the cause of a mendelian disorder Hit paper breakdown → | 2009 | 1400 |
| 7 | Exome sequencing as a tool for Mendelian disease gene discovery Hit paper breakdown → | 2011 | 1206 |
| 8 | Cell-free DNA Comprises an In Vivo Nucleosome Footprint that Informs Its Tissues-Of-Origin Hit paper breakdown → | 2016 | 997 |
| 9 | Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions Hit paper breakdown → | 2013 | 990 |
| 10 | Accurate Multiplex Polony Sequencing of an Evolved Bacterial Genome Hit paper breakdown → | 2005 | 983 |
| 11 | Comprehensive single-cell transcriptional profiling of a multicellular organism Hit paper breakdown → | 2017 | 929 |
| 12 | Target-enrichment strategies for next-generation sequencing Hit paper breakdown → | 2010 | 923 |
| 13 | Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing Hit paper breakdown → | 2015 | 882 |
| 14 | Exome sequencing in sporadic autism spectrum disorders identifies severe de novo mutations Hit paper breakdown → | 2011 | 870 |
| 15 | Analysis of Genetic Inheritance in a Family Quartet by Whole-Genome Sequencing Hit paper breakdown → | 2010 | 785 |
| 16 | A three-dimensional model of the yeast genome Hit paper breakdown → | 2010 | 782 |
| 17 | DNA sequencing at 40: past, present and future Hit paper breakdown → | 2017 | 716 |
| 18 | Classification and characterization of microsatellite instability across 18 cancer types Hit paper breakdown → | 2016 | 707 |
| 19 | Analysis of 6,515 exomes reveals the recent origin of most human protein-coding variants Hit paper breakdown → | 2012 | 668 |
| 20 | Joint profiling of chromatin accessibility and gene expression in thousands of single cells Hit paper breakdown → | 2018 | 621 |
About Jay Shendure
Jay Shendure is a scholar working on Molecular Biology, Genetics, Cancer Research, Plant Science and Pulmonary and Respiratory Medicine, having authored 305 papers that have together received 56.1k indexed citations. Recurring topics across this work include RNA and protein synthesis mechanisms (54 papers), Genomics and Chromatin Dynamics (52 papers), Single-cell and spatial transcriptomics (51 papers), Genomics and Phylogenetic Studies (48 papers), CRISPR and Genetic Engineering (44 papers), RNA Research and Splicing (34 papers), RNA modifications and cancer (28 papers) and Genomics and Rare Diseases (27 papers). The work is most often cited by research in Genetics (16.7k citations), Cancer Research (7.8k citations), Molecular Biology (35.2k citations), Aging (608 citations) and Biophysics (1.3k 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 Adey and Deborah A. Nickerson. Their work appears in journals such as Nature, Science, Nature Genetics, Nature Biotechnology 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.