M. Liang
Impact in
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- Metabolism and Genetic Disorders
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- RNA Interference and Gene Delivery
- Advanced biosensing and bioanalysis techniques
- RNA and protein synthesis mechanisms
- RNA Research and Splicing
Papers in
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- Metabolism and Genetic Disorders 2
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- Mitochondrial Function and Pathology 1
- Co-authors
- Tarekegn Geberhiwot (1 shared paper)Ling Jin (1 shared paper)Lerong Li (1 shared paper)Junxiang Luo (1 shared paper)Dwight D. Koeberl (1 shared paper)Gerald S. Lipshutz (1 shared paper)Rajnish Saini (1 shared paper)Andreas Schulze (1 shared paper)
- Journals
- Materials Letters (1 paper)Renewable Energy (1 paper)Journal of Physics D Applied Physics (1 paper)Textile Research Journal (1 paper)Nature (1 paper)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
M. Liang
7 papers receiving 116 citations
M. Liang's Hit Papers
Peers
Comparison fields: 5 of 45
- Clinical Biochemistry 14
- Molecular Biology 76
- Nuclear and High Energy Physics 10
- Genetics 18
- Infectious Diseases 8
Countries citing papers authored by M. Liang
This map shows the geographic impact of M. Liang'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 M. Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Liang more than expected).
Fields of papers citing papers by M. Liang
This network shows the impact of papers produced by M. Liang. 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 M. Liang. The network helps show where M. Liang may publish in the future.
Co-authors
The 25 scholars most cited alongside M. Liang, 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 | Interim analyses of a first-in-human phase 1/2 mRNA trial for propionic acidaemia Hit paper breakdown → | 2024 | 71 |
| 2 | 2024 | 29 | |
| 3 | 2000 | 10 | |
| 4 | 2025 | 5 | |
| 5 | 1967 | 4 | |
| 6 | 2008 | 1 | |
| 7 | 1994 | 1 |
About M. Liang
M. Liang is a scholar working on Clinical Biochemistry, Molecular Biology, Management Information Systems, Atomic and Molecular Physics, and Optics and Rheumatology, having authored 7 papers that have together received 121 indexed citations. Recurring topics across this work include Metabolism and Genetic Disorders (2 papers), Folate and B Vitamins Research (1 paper), Muscle metabolism and nutrition (1 paper), Quantum optics and atomic interactions (1 paper), Mitochondrial Function and Pathology (1 paper), Solidification and crystal growth phenomena (1 paper), Quantum Chromodynamics and Particle Interactions (1 paper) and Optics and Image Analysis (1 paper). The work is most often cited by research in Clinical Biochemistry (14 citations), Molecular Biology (76 citations), Nuclear and High Energy Physics (10 citations), Genetics (18 citations) and Infectious Diseases (8 citations). M. Liang has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Tarekegn Geberhiwot, Ling Jin, Lerong Li, Junxiang Luo, Dwight D. Koeberl, Gerald S. Lipshutz, Rajnish Saini, Andreas Schulze, Vanja Sikirica and Stephanie Grünewald. Their work appears in journals such as Materials Letters, Renewable Energy, Journal of Physics D Applied Physics, Textile Research Journal and Nature.
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.