Shumin Wu

1.2k citations
31 papers · 774 · h-index 12

Impact in

Papers in

    • Natural Language Processing Techniques 6
    • Topic Modeling 5
    • Intelligent Tutoring Systems and Adaptive Learning 3
    • Epigenetics and DNA Methylation 4
    • Biomedical Text Mining and Ontologies 3
    • PI3K/AKT/mTOR signaling in cancer 3
    • Genomics and Chromatin Dynamics 2

Shumin Wu

31 papers receiving 748 citations

Peers

Shumin Wu
Comparison fields: 5 of 115
  • Developmental Neuroscience 43
  • Neurology 62
  • Biological Psychiatry 15
  • Molecular Biology 392
  • Virology 23
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Citations per field
00.5×2×3×4×4.6×
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Citations per year

Countries citing papers authored by Shumin Wu

Since Specialization
Citations

This map shows the geographic impact of Shumin Wu'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 Shumin Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shumin Wu more than expected).

Fields of papers citing papers by Shumin Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shumin Wu. 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 Shumin Wu. The network helps show where Shumin Wu may publish in the future.

Co-authors

The 25 scholars most cited alongside Shumin Wu, 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 Shumin Wu Line = papers co-authored together Shumin Wu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016126
2 2020109
3 201386
4 201476
5 201472
6 200855
7 201145
8 200744
9 200633
10
Photodynamic effects of 5-aminolevulinic acid and its hexylester on several cell lines.
200313
11 201513
12
Semantic Mapping Using Automatic Word Alignment and Semantic Role Labeling
201213
13
USER MODEL OF A PERSONAL ASSISTANT IN COLLABORATIVE DESIGN ENVIRONMENTS
200212
14 201210
15 202110
16 20237
17
Reducing unproductive learning activities in serious games for second language acquisition
20087
18 20246
19 20246
20 20195

About Shumin Wu

Shumin Wu is a scholar working on Artificial Intelligence, Molecular Biology, Developmental and Educational Psychology, Management Information Systems and Cancer Research, having authored 31 papers that have together received 774 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (6 papers), Topic Modeling (5 papers), Epigenetics and DNA Methylation (4 papers), Biomedical Text Mining and Ontologies (3 papers), PI3K/AKT/mTOR signaling in cancer (3 papers), Intelligent Tutoring Systems and Adaptive Learning (3 papers), Genomics and Chromatin Dynamics (2 papers) and Educational Games and Gamification (2 papers). The work is most often cited by research in Developmental Neuroscience (43 citations), Neurology (62 citations), Biological Psychiatry (15 citations), Molecular Biology (392 citations) and Virology (23 citations). Shumin Wu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Judd Christopher Rice, W. Lewis Johnson, Miou Zhou, Raymond C. Trievel, Yoshitake Sano, Shan Huang, Hong Wu, Weiming Shen, Hamada H. Ghenniwa and Martha Stone Palmer. Their work appears in journals such as Computers in Industry, Neuron, eLife, Molecular Psychiatry and Cell Reports.

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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