Vicky Yao
Impact in
- Aging top 1%
- Genetics, Aging, and Longevity in Model Organisms
Papers in
-
- Bioinformatics and Genomic Networks 11
- Gene expression and cancer classification 4
- Single-cell and spatial transcriptomics 2
- Genomics and Chromatin Dynamics 2
- Microbial Metabolic Engineering and Bioproduction 2
- Genetics 3
- Genetic Associations and Epidemiology 2
- Co-authors
- Olga G. Troyanskaya (14 shared papers)Alicja Tadych (5 shared papers)Aaron K. Wong (5 shared papers)Arjun Krishnan (4 shared papers)Chandra L. Theesfeld (2 shared papers)Natalia Volfovsky (1 shared paper)Ran Zhang (1 shared paper)Alex Lash (1 shared paper)
- Journals
- PLoS Genetics (2 papers)Nucleic Acids Research (2 papers)Nature Communications (2 papers)Bioinformatics (1 paper)PLoS Computational Biology (1 paper)
- Partner nations
- United StatesSwedenCanada
In The Last Decade
Vicky Yao
17 papers receiving 1.1k citations
Vicky Yao's Hit Papers
Peers
Comparison fields: 5 of 115
- Aging 180
- Biological Psychiatry 24
- Molecular Biology 558
- Genetics 191
- Endocrine and Autonomic Systems 42
Countries citing papers authored by Vicky Yao
This map shows the geographic impact of Vicky Yao'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 Vicky Yao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Vicky Yao more than expected).
Fields of papers citing papers by Vicky Yao
This network shows the impact of papers produced by Vicky Yao. 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 Vicky Yao. The network helps show where Vicky Yao may publish in the future.
Co-authors
The 25 scholars most cited alongside Vicky Yao, 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 | 2016 | 281 | |
| 2 | Current progress and open challenges for applying deep learning across the biosciences Hit paper breakdown → | 2022 | 202 |
| 3 | 2018 | 143 | |
| 4 | 2020 | 113 | |
| 5 | 2016 | 84 | |
| 6 | 2020 | 73 | |
| 7 | 2018 | 46 | |
| 8 | 2015 | 46 | |
| 9 | 2015 | 20 | |
| 10 | 2018 | 13 | |
| 11 | 2019 | 12 | |
| 12 | 2023 | 6 | |
| 13 | 2018 | 6 | |
| 14 | 2011 | 5 | |
| 15 | 2019 | 5 | |
| 16 | 2025 | 4 | |
| 17 | 2024 | 4 | |
| 18 | 2024 | 0 | |
| 19 | 2023 | 0 |
About Vicky Yao
Vicky Yao is a scholar working on Molecular Biology, Genetics, Aging, Cellular and Molecular Neuroscience and Physiology, having authored 19 papers that have together received 1.1k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (11 papers), Gene expression and cancer classification (4 papers), Genetics, Aging, and Longevity in Model Organisms (3 papers), Neuroscience and Neuropharmacology Research (2 papers), Single-cell and spatial transcriptomics (2 papers), Genomics and Chromatin Dynamics (2 papers), Microbial Metabolic Engineering and Bioproduction (2 papers) and Genetic Associations and Epidemiology (2 papers). The work is most often cited by research in Aging (180 citations), Biological Psychiatry (24 citations), Molecular Biology (558 citations), Genetics (191 citations) and Endocrine and Autonomic Systems (42 citations). Vicky Yao has collaborated with scholars based in United States, Sweden and Canada. Frequent co-authors include Olga G. Troyanskaya, Alicja Tadych, Aaron K. Wong, Arjun Krishnan, Chandra L. Theesfeld, Natalia Volfovsky, Ran Zhang, Alex Lash, Alan Packer and Coleen T. Murphy. Their work appears in journals such as PLoS Genetics, Nucleic Acids Research, Nature Communications, Bioinformatics and PLoS Computational 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.