Ming‐Chya Wu

27 papers receiving 319 citations

Peers

Ming‐Chya Wu
Comparison fields: 5 of 74
  • Condensed Matter Physics 76
  • Statistical and Nonlinear Physics 59
  • Mathematical Physics 37
  • Statistics and Probability 18
  • Atomic and Molecular Physics, and Optics 56
Replace Wooseop Kwak with:
Wooseop Kwak South Korea
Wen-Jong Ma Taiwan
Yiwen He China
Vittoria Sposini Germany
Blair Simon United States
Samudrajit Thapa Germany
A. Rodrı́guez Spain
Rohit Jain India
Yukito Iba Japan
Thomas Neusius Germany
Ming‐Chya Wu relative to Wooseop Kwak South Korea Wooseop Kwak's profile →
Citations per field
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Wooseop Kwak · 1×
Citations per year

Countries citing papers authored by Ming‐Chya Wu

Since Specialization
Citations

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

Fields of papers citing papers by Ming‐Chya Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200440
2 200334
3 200630
4 200630
5 200227
6 200920
7 200620
8 201112
9 200412
10 200811
11 201010
12 201210
13 20089
14 20088
15 20097
16 20097
17 20107
18
The Caldirola-Kanai Model and Its Equivalent Theories for a Damped Oscillator
19986
19 20084
20 20134

About Ming‐Chya Wu

Ming‐Chya Wu is a scholar working on Molecular Biology, Economics and Econometrics, Condensed Matter Physics, Finance and Materials Chemistry, having authored 29 papers that have together received 323 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (11 papers), Complex Systems and Time Series Analysis (7 papers), Financial Risk and Volatility Modeling (5 papers), RNA and protein synthesis mechanisms (5 papers), Theoretical and Computational Physics (5 papers), Enzyme Structure and Function (4 papers), Stochastic processes and statistical mechanics (3 papers) and Cardiac electrophysiology and arrhythmias (2 papers). The work is most often cited by research in Condensed Matter Physics (76 citations), Statistical and Nonlinear Physics (59 citations), Mathematical Physics (37 citations), Statistics and Probability (18 citations) and Atomic and Molecular Physics, and Optics (56 citations). Ming‐Chya Wu has collaborated with scholars based in Taiwan, United States and Slovakia. Frequent co-authors include Chin‐Kun Hu, N. Sh. Izmailian, Norden E. Huang, Ján Buša, Shura Hayryan, K. B. Oganesyan, J. Skřivǎnek, Jozef Džurina, Ján Plavka and Tian Yow Tsong. Their work appears in journals such as Computer Physics Communications, Physica A Statistical Mechanics and its Applications, Biophysical Chemistry, Journal of the Physical Society of Japan and Journal of Computational 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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