Ruby Liu
Impact in
- Neurology top 10%
- Long-Term Effects of COVID-19
- Neuroinflammation and Neurodegeneration Mechanisms
-
- Intensive Care Unit Cognitive Disorders
Papers in
- Genetics 11
- Genomics and Rare Diseases 8
- Genetics and Neurodevelopmental Disorders 2
- Genomic variations and chromosomal abnormalities 2
-
- Long-Term Effects of COVID-19 2
- Neuroinflammation and Neurodegeneration Mechanisms 2
- Co-authors
- Mark P. Haggard (2 shared papers)Lucy G. Cheke (2 shared papers)Muzaffer Kaşer (2 shared papers)Sabine P. Yeung (2 shared papers)Madhuri Hegde (14 shared papers)Babi Ramesh Reddy Nallamilli (10 shared papers)Abhinav Mathur (6 shared papers)Zeqiang Ma (4 shared papers)
- Journals
- Genetics in Medicine (4 papers)Frontiers in Aging Neuroscience (2 papers)Molecular Genetics and Metabolism (2 papers)Journal of Molecular Diagnostics (2 papers)Prenatal Diagnosis (1 paper)
- Partner nations
- United StatesUnited KingdomNetherlands
In The Last Decade
Ruby Liu
19 papers receiving 302 citations
Peers
Comparison fields: 5 of 47
- Neurology 127
- Critical Care and Intensive Care Medicine 36
- Neurology 29
- Genetics 79
- Biological Psychiatry 5
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 | 104 | |
| 2 | 2022 | 51 | |
| 3 | 2020 | 40 | |
| 4 | 2021 | 35 | |
| 5 | 2023 | 18 | |
| 6 | 2023 | 18 | |
| 7 | 2025 | 17 | |
| 8 | 2023 | 16 | |
| 9 | 2023 | 3 | |
| 10 | 2025 | 3 | |
| 11 | 2024 | 2 | |
| 12 | 2021 | 1 | |
| 13 | 2024 | 1 | |
| 14 | 2023 | 1 | |
| 15 | 2024 | 1 | |
| 16 | 2024 | 1 | |
| 17 | 2024 | 1 | |
| 18 | 2022 | 1 | |
| 19 | 2024 | 1 |
About Ruby Liu
Ruby Liu is a scholar working on Genetics, Neurology, Cancer Research, Neurology and Molecular Biology, having authored 19 papers that have together received 315 indexed citations. Recurring topics across this work include Genomics and Rare Diseases (8 papers), Muscle Physiology and Disorders (3 papers), Cancer Genomics and Diagnostics (2 papers), Genetics and Neurodevelopmental Disorders (2 papers), Long-Term Effects of COVID-19 (2 papers), Neuroinflammation and Neurodegeneration Mechanisms (2 papers), Genomic variations and chromosomal abnormalities (2 papers) and Parvovirus B19 Infection Studies (1 paper). The work is most often cited by research in Neurology (127 citations), Critical Care and Intensive Care Medicine (36 citations), Neurology (29 citations), Genetics (79 citations) and Biological Psychiatry (5 citations). Ruby Liu has collaborated with scholars based in United States, United Kingdom and Netherlands. Frequent co-authors include Mark P. Haggard, Lucy G. Cheke, Muzaffer Kaşer, Sabine P. Yeung, Madhuri Hegde, Babi Ramesh Reddy Nallamilli, Abhinav Mathur, Zeqiang Ma, Suresh G. Shenoy and C. Alexander Valencia. Their work appears in journals such as Genetics in Medicine, Frontiers in Aging Neuroscience, Molecular Genetics and Metabolism, Journal of Molecular Diagnostics and Prenatal Diagnosis.
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.