Eric Yi Liu
Impact in
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- Genetic Mapping and Diversity in Plants and Animals
- Genetic Associations and Epidemiology
- Genetic and phenotypic traits in livestock
- Genomics and Rare Diseases
- Evolution and Genetic Dynamics
- Genomic variations and chromosomal abnormalities
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- Gene expression and cancer classification
Papers in
- Genetics 7
- Genetic Associations and Epidemiology 5
- Genetic Mapping and Diversity in Plants and Animals 4
- Genetic and phenotypic traits in livestock 3
- Genomics and Rare Diseases 3
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- Machine Learning and Algorithms 1
- Co-authors
- Wei Wang (6 shared papers)Yun Li (5 shared papers)Mingyao Li (1 shared paper)Fernando Pardo‐Manuel de Villena (2 shared papers)Gary A. Churchill (1 shared paper)Elissa J. Chesler (1 shared paper)Andrew P. Morgan (1 shared paper)Qi Zhang (1 shared paper)
- Journals
- Bioinformatics (2 papers)Genetic Epidemiology (2 papers)JAMA Network Open (1 paper)Genetics (1 paper)PLoS ONE (1 paper)
- Partner nations
- United StatesGermanySingapore
In The Last Decade
Eric Yi Liu
12 papers receiving 278 citations
Peers
Comparison fields: 5 of 71
- Genetics 170
- Molecular Biology 95
- Artificial Intelligence 41
- Plant Science 44
- Computer Vision and Pattern Recognition 19
Countries citing papers authored by Eric Yi Liu
This map shows the geographic impact of Eric Yi 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 Eric Yi Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric Yi Liu more than expected).
Fields of papers citing papers by Eric Yi Liu
This network shows the impact of papers produced by Eric Yi 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 Eric Yi Liu. The network helps show where Eric Yi Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Eric Yi 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 | 2012 | 82 | |
| 2 | 2014 | 52 | |
| 3 | 2010 | 34 | |
| 4 | 2012 | 29 | |
| 5 | 2012 | 28 | |
| 6 | 2012 | 14 | |
| 7 | 2017 | 13 | |
| 8 | 2011 | 12 | |
| 9 | 2013 | 8 | |
| 10 | 2017 | 6 | |
| 11 | 2008 | 5 | |
| 12 | 2025 | 1 | |
| 13 | 2025 | 0 | |
| 14 | 2025 | 0 | |
| 15 | 2020 | 0 |
About Eric Yi Liu
Eric Yi Liu is a scholar working on Genetics, Artificial Intelligence, Molecular Biology, Computer Networks and Communications and Information Systems, having authored 15 papers that have together received 284 indexed citations. Recurring topics across this work include Genetic Associations and Epidemiology (5 papers), Genetic Mapping and Diversity in Plants and Animals (4 papers), Genetic and phenotypic traits in livestock (3 papers), Genomics and Rare Diseases (3 papers), CRISPR and Genetic Engineering (2 papers), Gene expression and cancer classification (2 papers), Complex Network Analysis Techniques (1 paper) and Machine Learning and Algorithms (1 paper). The work is most often cited by research in Genetics (170 citations), Molecular Biology (95 citations), Artificial Intelligence (41 citations), Plant Science (44 citations) and Computer Vision and Pattern Recognition (19 citations). Eric Yi Liu has collaborated with scholars based in United States, Germany and Singapore. Frequent co-authors include Wei Wang, Yun Li, Mingyao Li, Fernando Pardo‐Manuel de Villena, Gary A. Churchill, Elissa J. Chesler, Andrew P. Morgan, Qi Zhang, Leonard McMillan and Zhishan Guo. Their work appears in journals such as Bioinformatics, Genetic Epidemiology, JAMA Network Open, Genetics and PLoS ONE.
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.