Shoudan Liang

7.7k citations
84 papers · 5.5k indexed · 3 hit papers · h-index 35

Shoudan Liang

79 papers receiving 5.4k citations

Hit Papers

Dnmt3a is essential for hematop...7911986202619992012250500750

Peers

Shoudan Liang
Comparison fields: 5 of 157
  • Condensed Matter Physics 866
  • Aging 111
  • Hematology 642
  • Molecular Biology 3.5k
  • Cancer Research 554
Replace Aaron R. Dinner with:
Aaron R. Dinner United States
Иван Тодоров United States
Yuval Garini Israel
Paolo Provero Italy
Sabine Mai Canada
Marek Kimmel United States
Gustavo Stolovitzky United States
Hiroshi Yamashita Japan
Alfred Zippelius Switzerland
Thomas Manke Germany
Shoudan Liang relative to Aaron R. Dinner United States Aaron R. Dinner's profile →
Citations per field
00.5×3.5×
Aaron R. Dinner · 1×
Citations per year

Countries citing papers authored by Shoudan Liang

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

The 25 scholars most cited alongside Shoudan Liang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shoudan Liang Line = papers co-authored together Shoudan Liang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20230
2 20175
3 201567
4 20152
5 201462
6 201258
7 201219
8 201227
9 20129
10 2011127
11 2011105
12 201190
13 201049
14 201067
15 2010165
16 201081
17 20082
18
Making sense of large-scale gene expression data with simple computational techniques
20002
19 2000109
20
Spatial Autocatalytic Dynamics: An Approach to Modeling Prebiotic Evolution
19991

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), Gene expression and cancer classification (10 papers), Genomics and Chromatin Dynamics (10 papers), RNA modifications and cancer (10 papers), Theoretical and Computational Physics (9 papers), Quantum and electron transport phenomena (8 papers) and Genomics and Phylogenetic Studies (8 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.

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