Ming‐Tat Ko

9.7k citations
48 papers · 6.3k indexed · 2 hit papers · h-index 15
Topics
Advanced Graph Theory Research (11 papers)Complexity and Algorithms in Graphs (8 papers)Protein Structure and Dynamics (7 papers)
Partner nations
TaiwanJapanSingapore

In The Last Decade

Ming‐Tat Ko

45 papers receiving 6.1k citations

Hit Papers

cytoHubba: identifying hub objects and ...20002026200820172014200010002.0k3.0k4.0k

Peers

Ming‐Tat Ko
Comparison fields: 5 of 173
  • Molecular Biology 3.0k
  • Computer Vision and Pattern Recognition 1.0k
  • Cancer Research 1000
  • Pulmonary and Respiratory Medicine 902
  • Immunology 577
Replace Doheon Lee with:
Doheon Lee South Korea
Donna K. Slonim United States
Francisco Azuaje United Kingdom
Xiao‐Ming Xu China
Sorin Drăghici United States
Olli Yli‐Harja Finland
C. D. Bloomfield United States
Kenneth N. Ross United States
Mignon L. Loh United States
Jean Yang Australia
Ming‐Tat Ko relative to Doheon Lee South Korea Doheon Lee's profile →
Citations per field
00.5×4.3×
Doheon Lee · 1×
Citations per year

Countries citing papers authored by Ming‐Tat Ko

Since Specialization
Citations

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

Fields of papers citing papers by Ming‐Tat Ko

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming‐Tat Ko

This figure shows the co-authorship network connecting the top 25 collaborators of Ming‐Tat Ko. A scholar is included among the top collaborators of Ming‐Tat Ko 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 Ming‐Tat Ko. Ming‐Tat Ko 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
cytoHubba: identifying hub objects and sub-networks from complex interactomebreakdown →
4141
2 2
3 1
4 37
5 222
6 285
7 42
8 10
9 53
10 56
11 9
12 31
13 2
14 5
15 8
16 12
17 23
18 83
19 22
20 2

About Ming‐Tat Ko

Ming‐Tat Ko is a scholar working on Computer Graphics and Computer-Aided Design, Computer Networks and Communications and Computational Theory and Mathematics, having authored 48 papers that have together received 6.3k indexed citations. Recurring topics across this work include Advanced Graph Theory Research (11 papers), Complexity and Algorithms in Graphs (8 papers) and Protein Structure and Dynamics (7 papers). The work is most often cited by research in Cancer Research (1000 citations), Computer Vision and Pattern Recognition (1.0k citations) and Molecular Biology (3.0k citations). Ming‐Tat Ko has collaborated with scholars based in Taiwan, Japan and Singapore. Frequent co-authors include Chin-Wen Ho, Chung‐Yen Lin, Shu-Hwa Chen, Hong-Yuan Mark Liao, Li‐Fen Chen, Ja‐Chen Lin, Gwo‐Jong Yu, Jenn‐Kang Hwang, Yung-Hao Wong and Chia‐Huei Chu. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and Gene.

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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