Hua‐Sheng Chiu

2.6k citations
24 papers · 1.1k indexed · 1 hit paper · h-index 12
Topics
Cancer-related molecular mechanisms research (8 papers)RNA and protein synthesis mechanisms (8 papers)Machine Learning in Bioinformatics (7 papers)
Partner nations
United StatesTaiwanChina

In The Last Decade

Hua‐Sheng Chiu

22 papers receiving 1.0k citations

Hit Papers

An Extensive MicroRNA-Mediated Network of RNA-RNA Interac...20112026201620212011100200300400500

Peers

Hua‐Sheng Chiu
Comparison fields: 5 of 90
  • Molecular Biology 954
  • Cancer Research 690
  • Oncology 40
  • Immunology 34
  • Genetics 32
Replace Tao Pan with:
Tao Pan China
Aldema Sas‐Chen Israel
Joëlle Vermeulen Belgium
Sarah D. Diermeier New Zealand
Shyam Sirasanagandla United States
Daniel D’Andrea Italy
Michal Domanski Denmark
Y. Hey United Kingdom
Patricio Yankilevich Argentina
Judit Jané‐Valbuena United States
Hua‐Sheng Chiu relative to Tao Pan China Tao Pan's profile →
Citations per field
00.5×3.5×
Tao Pan · 1×
Citations per year

Countries citing papers authored by Hua‐Sheng Chiu

Since Specialization
Citations

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

Fields of papers citing papers by Hua‐Sheng Chiu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hua‐Sheng Chiu. 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 Hua‐Sheng Chiu. The network helps show where Hua‐Sheng Chiu may publish in the future.

Co-authorship network of co-authors of Hua‐Sheng Chiu

This figure shows the co-authorship network connecting the top 25 collaborators of Hua‐Sheng Chiu. A scholar is included among the top collaborators of Hua‐Sheng Chiu 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 Hua‐Sheng Chiu. Hua‐Sheng Chiu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 1
2 0
3 2
4 28
5 3
6 13
7 10
8 28
9 83
10 33
11 42
12 88
13
An Extensive MicroRNA-Mediated Network of RNA-RNA Interactions Regulates Established Oncogenic Pathways in Glioblastomabreakdown →
580
14 38
15 55
16 23
17 4
18 1
19
Discovering Statistically Significant Clusters by Using Iterative Genetic Algorithms in Gene Expression Data.
1
20 24

About Hua‐Sheng Chiu

Hua‐Sheng Chiu is a scholar working on Cancer Research, Rehabilitation and Molecular Biology, having authored 24 papers that have together received 1.1k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (8 papers), RNA and protein synthesis mechanisms (8 papers) and Machine Learning in Bioinformatics (7 papers). The work is most often cited by research in Cancer Research (690 citations), Molecular Biology (954 citations) and Aging (4 citations). Hua‐Sheng Chiu has collaborated with scholars based in United States, Taiwan and China. Frequent co-authors include Pavel Sumazin, Andrea Califano, Xuerui Yang, Mukesh Bansal, David Llobet‐Navàs, José Silva, Archana Iyer, Wei‐Jen Chung, Presha Rajbhandari and Paolo Guarnieri. Their work appears in journals such as Cell, Nucleic Acids Research and Molecular Cell.

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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