Shoudan Liang
- Molecular Biology top 2%
- Condensed Matter Physics top 2%
- Hematology top 1%
- Genetics top 5%
- Cancer Research top 5%
- Co-authors
- Roland SomogyiStefanie FuhrmanYue LuJean‐Pierre J. IssaLeo P. KadanoffChao TangJaroslav Jelı́nekDavid Bensimon
- Topics
- Epigenetics and DNA Methylation (24 papers)Physics of Superconductivity and Magnetism (11 papers)Gene expression and cancer classification (10 papers)
- Journals
- Proceedings of the National Academy of SciencesPhysical Review LettersJournal of Biological Chemistry
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Shoudan Liang
79 papers receiving 5.4k citations
Hit Papers
Peers
Comparison fields: 5 of 157
- Molecular Biology 3.5k
- Condensed Matter Physics 866
- Hematology 642
- Genetics 620
- Cancer Research 554
Countries citing papers authored by Shoudan Liang
This map shows the geographic impact of Shoudan 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 Shoudan Liang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shoudan Liang more than expected).
Fields of papers citing papers by Shoudan Liang
This network shows the impact of papers produced by Shoudan 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 Shoudan Liang. The network helps show where Shoudan Liang may publish in the future.
Co-authorship network of co-authors of Shoudan Liang
This figure shows the co-authorship network connecting the top 25 collaborators of Shoudan Liang. A scholar is included among the top collaborators of Shoudan Liang 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 Shoudan Liang. Shoudan Liang 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 | 5 | |
| 3 | 67 | |
| 4 | 2 | |
| 5 | 62 | |
| 6 | 58 | |
| 7 | 19 | |
| 8 | 27 | |
| 9 | 9 | |
| 10 | 127 | |
| 11 | 105 | |
| 12 | 90 | |
| 13 | 49 | |
| 14 | 67 | |
| 15 | 165 | |
| 16 | 81 | |
| 17 | 2 | |
| 18 | Making sense of large-scale gene expression data with simple computational techniques | 2 |
| 19 | 109 | |
| 20 | Spatial Autocatalytic Dynamics: An Approach to Modeling Prebiotic Evolution | 1 |
About Shoudan Liang
Shoudan Liang is a scholar working on Condensed Matter Physics, Molecular Biology and Hematology, having authored 84 papers that have together received 5.5k indexed citations. Recurring topics across this work include Epigenetics and DNA Methylation (24 papers), Physics of Superconductivity and Magnetism (11 papers) and Gene expression and cancer classification (10 papers). The work is most often cited by research in Condensed Matter Physics (866 citations), Aging (111 citations) and Hematology (642 citations). Shoudan Liang has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Roland Somogyi, Stefanie Fuhrman, Yue Lu, Jean‐Pierre J. Issa, Leo P. Kadanoff, Chao Tang, Jaroslav Jelı́nek, David Bensimon, Boris I. Shraiman and Manoj P. Samanta. Their work appears in journals such as Proceedings of the National Academy of Sciences, Physical Review Letters and Journal of Biological Chemistry.
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.