Ruby Liu
Impact in
-
- Intensive Care Unit Cognitive Disorders
- Neurology top 10%
- Long-Term Effects of COVID-19
- Neuroinflammation and Neurodegeneration Mechanisms
Papers in
- Genetics 9
- Genomics and Rare Diseases 6
- Genomic variations and chromosomal abnormalities 4
- Genetics and Neurodevelopmental Disorders 2
-
- Muscle Physiology and Disorders 3
- Congenital heart defects research 2
- Co-authors
- Sabine P. Yeung (2 shared papers)Mark Haggard (2 shared papers)Lucy G. Cheke (2 shared papers)Muzaffer Kaşer (2 shared papers)Madhuri Hegde (14 shared papers)Babi Ramesh Reddy Nallamilli (10 shared papers)Zeqiang Ma (4 shared papers)Abhinav Mathur (6 shared papers)
- Journals
- Genetics in Medicine (3 papers)Frontiers in Aging Neuroscience (2 papers)Molecular Genetics and Metabolism (2 papers)Human Mutation (1 paper)JAMA Network Open (1 paper)
- Partner nations
- United StatesUnited KingdomNetherlands
In The Last Decade
Ruby Liu
16 papers receiving 232 citations
Peers
Comparison fields: 5 of 51
- Critical Care and Intensive Care Medicine 51
- Neurology 114
- Neurology 34
- Biological Psychiatry 8
- Clinical Psychology 55
Countries citing papers authored by Ruby Liu
This map shows the geographic impact of Ruby Liu'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 Ruby Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ruby Liu more than expected).
Fields of papers citing papers by Ruby Liu
This network shows the impact of papers produced by Ruby Liu. 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 Ruby Liu. The network helps show where Ruby Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Ruby Liu, 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 | 2022 | 89 | |
| 2 | 2022 | 41 | |
| 3 | 2020 | 34 | |
| 4 | 2021 | 31 | |
| 5 | 2023 | 11 | |
| 6 | 2023 | 10 | |
| 7 | 2023 | 8 | |
| 8 | 2023 | 3 | |
| 9 | 2025 | 2 | |
| 10 | 2024 | 1 | |
| 11 | 2024 | 1 | |
| 12 | 2024 | 1 | |
| 13 | 2022 | 1 | |
| 14 | 2024 | 1 | |
| 15 | 2021 | 1 | |
| 16 | 2024 | 1 | |
| 17 | 2023 | 0 |
About Ruby Liu
Ruby Liu is a scholar working on Genetics, Molecular Biology, Physiology, Neurology and Cardiology and Cardiovascular Medicine, having authored 17 papers that have together received 236 indexed citations. Recurring topics across this work include Genomics and Rare Diseases (6 papers), Genomic variations and chromosomal abnormalities (4 papers), Muscle Physiology and Disorders (3 papers), Long-Term Effects of COVID-19 (2 papers), Erythrocyte Function and Pathophysiology (2 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers), Genetics and Neurodevelopmental Disorders (2 papers) and Congenital heart defects research (2 papers). The work is most often cited by research in Critical Care and Intensive Care Medicine (51 citations), Neurology (114 citations), Neurology (34 citations), Biological Psychiatry (8 citations) and Clinical Psychology (55 citations). Ruby Liu has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Sabine P. Yeung, Mark Haggard, Lucy G. Cheke, Muzaffer Kaşer, Madhuri Hegde, Babi Ramesh Reddy Nallamilli, Zeqiang Ma, Abhinav Mathur, Suresh Shenoy and Christopher Harman. Their work appears in journals such as Genetics in Medicine, Frontiers in Aging Neuroscience, Molecular Genetics and Metabolism, Human Mutation and JAMA Network Open.
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.