Zhi‐Ping Liu

3.9k citations
87 papers · 2.6k indexed · 1 hit paper · h-index 23
Topics
Bioinformatics and Genomic Networks (25 papers)Gene expression and cancer classification (17 papers)Machine Learning in Bioinformatics (13 papers)
Partner nations
ChinaUnited StatesJapan

In The Last Decade

Zhi‐Ping Liu

78 papers receiving 2.6k citations

Hit Papers

Detecting early-warning signals for sudden deterioration ...20122026201620212012100200300400

Peers

Zhi‐Ping Liu
Comparison fields: 5 of 159
  • Molecular Biology 1.6k
  • Cancer Research 435
  • Immunology 344
  • Pulmonary and Respiratory Medicine 235
  • Genetics 182
Replace Minji Jeon with:
Minji Jeon South Korea
David Tuck United States
C. Evangelista United States
Philipp E. Geyer Germany
Nicola Waddell Australia
Sun Kim South Korea
Gang Feng China
James C. Costello United States
Pei Fen Kuan United States
Raivo Kolde Estonia
Zhi‐Ping Liu relative to Minji Jeon South Korea Minji Jeon's profile →
Citations per field
00.5×9.9×
Minji Jeon · 1×
Citations per year

Countries citing papers authored by Zhi‐Ping Liu

Since Specialization
Citations

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

Fields of papers citing papers by Zhi‐Ping Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Zhi‐Ping Liu. 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 Zhi‐Ping Liu. The network helps show where Zhi‐Ping Liu may publish in the future.

Co-authorship network of co-authors of Zhi‐Ping Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Zhi‐Ping Liu. A scholar is included among the top collaborators of Zhi‐Ping Liu 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 Zhi‐Ping Liu. Zhi‐Ping Liu 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 0
2 0
3 3
4 1
5 1
6 0
7 17
8 27
9 8
10 2
11 13
12 1
13 3
14 8
15 58
16 13
17 24
18 5
19 254
20 30

About Zhi‐Ping Liu

Zhi‐Ping Liu is a scholar working on Computational Mathematics, Molecular Biology and Health Informatics, having authored 87 papers that have together received 2.6k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (25 papers), Gene expression and cancer classification (17 papers) and Machine Learning in Bioinformatics (13 papers). The work is most often cited by research in Cancer Research (435 citations), Molecular Biology (1.6k citations) and Immunology (344 citations). Zhi‐Ping Liu has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Luonan Chen, Hulin Wu, Meiyi Li, Hongyu Miao, Rui Liu, Kazuyuki Aihara, Uttiya Basu, Jiguang Wang, Junghyun Lim and Gerson Rothschild. Their work appears in journals such as Cell, Nucleic Acids Research and Journal of Biological 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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