Jennifer J. Young
- Cancer Research top 2%
- MicroRNA in disease regulation 2
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- Computational Drug Discovery Methods 2
- Molecular Biology top 5%
- RNA Interference and Gene Delivery 2
- Advanced biosensing and bioanalysis techniques 2
- Oncology top 10%
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- Blood properties and coagulation 3
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- Cellular Mechanics and Interactions 3
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- Telomeres, Telomerase, and Senescence 3
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- Machine Learning in Materials Science 2
- Co-authors
- Tamer T. ÖnderRobert A. WeinbergJo VandesompeleFrank SpelemanJulie Teruya‐FeldsteinFrank WestermannPieter MestdaghHarsha Prabhala
- Journals
- Proceedings of the National Academy of Sciences (1 paper)Blood (1 paper)Nature Cell Biology (1 paper)
- Partner nations
- United StatesBelgiumGermany
In The Last Decade
Jennifer J. Young
21 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 123
- Cancer Research 911
- Computational Theory and Mathematics 411
- Molecular Biology 1.5k
- Oncology 290
- Immunology 137
Countries citing papers authored by Jennifer J. Young
This map shows the geographic impact of Jennifer J. Young'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 Jennifer J. Young with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jennifer J. Young more than expected).
Fields of papers citing papers by Jennifer J. Young
This network shows the impact of papers produced by Jennifer J. Young. 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 Jennifer J. Young. The network helps show where Jennifer J. Young may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jennifer J. Young, 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 | 2021 | 68 | |
| 2 | 2021 | 4 | |
| 3 | 2021 | 10 | |
| 4 | ZINC20—A Free Ultralarge-Scale Chemical Database for Ligand Discoverybreakdown → | 2020 | 556 |
| 5 | 2019 | 26 | |
| 6 | 2016 | 1 | |
| 7 | 2015 | 2 | |
| 8 | 2013 | 6 | |
| 9 | 2012 | 12 | |
| 10 | 2011 | 7 | |
| 11 | 2011 | 3 | |
| 12 | miR-9, a MYC/MYCN-activated microRNA, regulates E-cadherin and cancer metastasis | 2010 | 1 |
| 13 | 2010 | 8 | |
| 14 | 2010 | 102 | |
| 15 | 2010 | 26 | |
| 16 | miR-9, a MYC/MYCN-activated microRNA, regulates E-cadherin and cancer metastasisbreakdown → | 2010 | 1108 |
| 17 | 2010 | 36 | |
| 18 | 2009 | 41 | |
| 19 | 2008 | 145 | |
| 20 | 2007 | 12 |
About Jennifer J. Young
Jennifer J. Young is a scholar working on Gastroenterology, Cell Biology and Virology, having authored 21 papers that have together received 2.2k indexed citations. Recurring topics across this work include Blood properties and coagulation (3 papers), Cellular Mechanics and Interactions (3 papers), Telomeres, Telomerase, and Senescence (3 papers), Machine Learning in Materials Science (2 papers), Computational Drug Discovery Methods (2 papers), RNA Interference and Gene Delivery (2 papers), MicroRNA in disease regulation (2 papers) and Advanced biosensing and bioanalysis techniques (2 papers). The work is most often cited by research in Cancer Research (911 citations), Computational Theory and Mathematics (411 citations) and Molecular Biology (1.5k citations). Jennifer J. Young has collaborated with scholars based in United States, Belgium and Germany. Frequent co-authors include Tamer T. Önder, Robert A. Weinberg, Jo Vandesompele, Frank Speleman, Julie Teruya‐Feldstein, Frank Westermann, Pieter Mestdagh, Harsha Prabhala, Daniel Muth and Scott Valastyan. Their work appears in journals such as Proceedings of the National Academy of Sciences, Blood and Nature Cell Biology.
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.