Siyuan Ma
- Molecular Biology top 5%
- Public Health, Environmental and Occupational Health top 5%
- Physiology top 10%
- Infectious Diseases top 10%
- Epidemiology
- Co-authors
- Curtis HuttenhowerHimel MallickEric A. FranzosaLong H. NguyenBoyu RenTimothy L. TickleEmma SchwagerJeremy E. Wilkinson
- Topics
- Gut microbiota and health (7 papers)Gene expression and cancer classification (4 papers)Metabolomics and Mass Spectrometry Studies (3 papers)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Siyuan Ma
26 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 148
- Molecular Biology 1.3k
- Public Health, Environmental and Occupational Health 378
- Physiology 331
- Infectious Diseases 243
- Epidemiology 207
Countries citing papers authored by Siyuan Ma
This map shows the geographic impact of Siyuan Ma'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 Siyuan Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Siyuan Ma more than expected).
Fields of papers citing papers by Siyuan Ma
This network shows the impact of papers produced by Siyuan Ma. 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 Siyuan Ma. The network helps show where Siyuan Ma may publish in the future.
Co-authorship network of co-authors of Siyuan Ma
This figure shows the co-authorship network connecting the top 25 collaborators of Siyuan Ma. A scholar is included among the top collaborators of Siyuan Ma based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Siyuan Ma. Siyuan Ma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 7 | |
| 3 | 0 | |
| 4 | 7 | |
| 5 | 1 | |
| 6 | 11 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 77 | |
| 11 | 40 | |
| 12 | Multivariable association discovery in population-scale meta-omics studiesbreakdown → | 1302 |
| 13 | 39 | |
| 14 | 21 | |
| 15 | Distributed Power Generation in National Rural Electrification Plans: An International and Comparative Evaluation | 23 |
| 16 | 18 | |
| 17 | 64 | |
| 18 | 125 | |
| 19 | 169 | |
| 20 | 63 |
About Siyuan Ma
Siyuan Ma is a scholar working on Computational Mathematics, Energy Engineering and Power Technology and Pollution, having authored 29 papers that have together received 2.1k indexed citations. Recurring topics across this work include Gut microbiota and health (7 papers), Gene expression and cancer classification (4 papers) and Metabolomics and Mass Spectrometry Studies (3 papers). The work is most often cited by research in Biological Psychiatry (68 citations), Periodontics (92 citations) and Molecular Biology (1.3k citations). Siyuan Ma has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Curtis Huttenhower, Himel Mallick, Eric A. Franzosa, Long H. Nguyen, Boyu Ren, Timothy L. Tickle, Emma Schwager, Jeremy E. Wilkinson, Kelsey N. Thompson and Levi Waldron. Their work appears in journals such as Nature Communications, Environmental Science & Technology and Bioinformatics.
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.