Shu-An Chen

426 citations
8 papers · 353 · h-index 8

Impact in

    • Machine Learning in Bioinformatics
    • RNA and protein synthesis mechanisms
    • Genomics and Phylogenetic Studies
    • Protein Structure and Dynamics
    • Ubiquitin and proteasome pathways
    • vaccines and immunoinformatics approaches

Papers in

    • Machine Learning in Bioinformatics 6
    • Genomics and Phylogenetic Studies 2
    • Protein Structure and Dynamics 2
    • RNA and protein synthesis mechanisms 1
    • Ubiquitin and proteasome pathways 1
    • Microbial Community Ecology and Physiology 1

Shu-An Chen

8 papers receiving 350 citations

Peers

Shu-An Chen
Comparison fields: 5 of 62
  • Molecular Biology 281
  • Microbiology 23
  • Microbiology 2
  • Endocrinology 10
  • Computational Theory and Mathematics 18
Replace G. Keller with:
G. Keller Switzerland
Catherine Rivoire Switzerland
Recep Adiyaman United Kingdom
Obed Ramírez‐Sánchez Mexico
Changge Guan China
Asha I. Jacob United States
Christoph Elfmann Germany
Olga Kunyavskaya Russia
Ayşegül Güvenek United States
Andrew Schoenrock Canada
Shu-An Chen relative to G. Keller Switzerland G. Keller's profile →
Citations per field
00.5×1.5×
G. Keller · 1×
Citations per year

Countries citing papers authored by Shu-An Chen

Since Specialization
Citations

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

Fields of papers citing papers by Shu-An Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shu-An Chen. 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 Shu-An Chen. The network helps show where Shu-An Chen may publish in the future.

Co-authors

The 16 scholars most cited alongside Shu-An Chen, 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 Shu-An Chen Line = papers co-authored together Shu-An Chen links everyone, so they are left out of the graph.

All Works

8 of 8 papers shown
#Work
1 201184
2 201174
3 200874
4 201138
5 201033
6 201125
7 201117
8 20138

About Shu-An Chen

Shu-An Chen is a scholar working on Molecular Biology, Ecology, Biotechnology, Materials Chemistry and Infectious Diseases, having authored 8 papers that have together received 353 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (6 papers), Genomics and Phylogenetic Studies (2 papers), Protein Structure and Dynamics (2 papers), RNA and protein synthesis mechanisms (1 paper), Ubiquitin and proteasome pathways (1 paper), Microbial Metabolism and Applications (1 paper), Enzyme Structure and Function (1 paper) and Microbial Community Ecology and Physiology (1 paper). The work is most often cited by research in Molecular Biology (281 citations), Microbiology (23 citations), Microbiology (2 citations), Endocrinology (10 citations) and Computational Theory and Mathematics (18 citations). Shu-An Chen has collaborated with scholars based in Taiwan, China and Japan. Frequent co-authors include Yu‐Yen Ou, Tzong-Yi Lee, M. Michael Gromiha, Hsin‐Yi Hung, Makiko Suwa, Neil Arvin Bretaña, Cheng-Tsung Lu, Jun Zhang, Jian He and Shu Cai. Their work appears in journals such as PLoS ONE, BMC Bioinformatics, INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY, Journal of Computer-Aided Molecular Design 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.

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