Mo Liu
Impact in
- Cancer Research top 2%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Oncology top 5%
- Cancer Cells and Metastasis
Papers in
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- CRISPR and Genetic Engineering 6
- Pluripotent Stem Cells Research 5
-
- Advanced Database Systems and Queries 13
- Co-authors
- Mien‐Chie Hung (10 shared papers)Chun‐Te Chen (6 shared papers)Weiya Xia (8 shared papers)Chia‐Wei Li (2 shared papers)Jer-Yen Yang (2 shared papers)Dihua Yu (2 shared papers)Jennifer L. Hsu (2 shared papers)Sumaiyah K. Rehman (2 shared papers)
- Journals
- Stem Cell Research (5 papers)Nature Cell Biology (3 papers)Molecular Cell (2 papers)Virus Genes (2 papers)Cell Death and Disease (2 papers)
- Partner nations
- ChinaUnited StatesTaiwan
In The Last Decade
Mo Liu
85 papers receiving 2.5k citations
Mo Liu's Hit Papers
Peers
Comparison fields: 5 of 135
- Cancer Research 665
- Oncology 548
- Molecular Biology 1.5k
- Signal Processing 162
- Computer Networks and Communications 226
Countries citing papers authored by Mo Liu
This map shows the geographic impact of Mo 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 Mo Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mo Liu more than expected).
Fields of papers citing papers by Mo Liu
This network shows the impact of papers produced by Mo 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 Mo Liu. The network helps show where Mo Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Mo 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
Showing the 20 most-cited of 88 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | p53 regulates epithelial–mesenchymal transition and stem cell properties through modulating miRNAs Hit paper breakdown → | 2011 | 624 |
| 2 | 2009 | 347 | |
| 3 | 2011 | 197 | |
| 4 | 2009 | 80 | |
| 5 | 2010 | 79 | |
| 6 | 2011 | 77 | |
| 7 | 2016 | 77 | |
| 8 | 2019 | 61 | |
| 9 | 2018 | 60 | |
| 10 | 2013 | 52 | |
| 11 | 2011 | 46 | |
| 12 | 2005 | 43 | |
| 13 | 2011 | 40 | |
| 14 | 2005 | 36 | |
| 15 | 2007 | 36 | |
| 16 | 2022 | 30 | |
| 17 | 2021 | 30 | |
| 18 | 2012 | 28 | |
| 19 | 2011 | 28 | |
| 20 | 2011 | 27 |
About Mo Liu
Mo Liu is a scholar working on Molecular Biology, Computer Networks and Communications, Oncology, Signal Processing and Cancer Research, having authored 88 papers that have together received 2.5k indexed citations. Recurring topics across this work include Advanced Database Systems and Queries (13 papers), Data Management and Algorithms (12 papers), Synthesis and biological activity (7 papers), CRISPR and Genetic Engineering (6 papers), MicroRNA in disease regulation (5 papers), Time Series Analysis and Forecasting (5 papers), Pluripotent Stem Cells Research (5 papers) and Cancer Cells and Metastasis (4 papers). The work is most often cited by research in Cancer Research (665 citations), Oncology (548 citations), Molecular Biology (1.5k citations), Signal Processing (162 citations) and Computer Networks and Communications (226 citations). Mo Liu has collaborated with scholars based in China, United States and Taiwan. Frequent co-authors include Mien‐Chie Hung, Chun‐Te Chen, Weiya Xia, Chia‐Wei Li, Jer-Yen Yang, Dihua Yu, Jennifer L. Hsu, Sumaiyah K. Rehman, Chi-Hong Chao and Heng‐Huan Lee. Their work appears in journals such as Stem Cell Research, Nature Cell Biology, Molecular Cell, Virus Genes and Cell Death and Disease.
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.