Chia‐Ru Chung

1.4k total citations
56 papers, 754 citations indexed

About

Chia‐Ru Chung is a scholar working on Molecular Biology, Microbiology and Clinical Biochemistry. According to data from OpenAlex, Chia‐Ru Chung has authored 56 papers receiving a total of 754 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 16 papers in Microbiology and 14 papers in Clinical Biochemistry. Recurrent topics in Chia‐Ru Chung's work include Antimicrobial Peptides and Activities (15 papers), Bacterial Identification and Susceptibility Testing (14 papers) and Machine Learning in Bioinformatics (12 papers). Chia‐Ru Chung is often cited by papers focused on Antimicrobial Peptides and Activities (15 papers), Bacterial Identification and Susceptibility Testing (14 papers) and Machine Learning in Bioinformatics (12 papers). Chia‐Ru Chung collaborates with scholars based in Taiwan, China and United States. Chia‐Ru Chung's co-authors include Tzong-Yi Lee, Jorng‐Tzong Horng, Li-Ching Wu, Hsin‐Yao Wang, Jang‐Jih Lu, Ying‐Chih Chiang, Lantian Yao, Eric Hsiao‐Kuang Wu, Jiahui Guan and Shih‐Ching Yeh and has published in prestigious journals such as Nucleic Acids Research, Journal of Molecular Biology and Analytical Chemistry.

In The Last Decade

Chia‐Ru Chung

56 papers receiving 745 citations

Peers

Chia‐Ru Chung
Comparison fields: 5 of 110
  • Molecular Biology 435
  • Microbiology 230
  • Clinical Biochemistry 139
  • Artificial Intelligence 63
  • Cognitive Neuroscience 60
Replace Gary Liu with:
Gary Liu United States
Petr Hájek Czechia
Wei Cao China
Xiaohui Ding China
Alexandre Drouin Canada
Harjeet Kaur India
Yixi Chen China
Andrew M. Stern United States
Yuxuan Hu China
Gary Liu United States View profile →
Citations per field, relative to Chia‐Ru Chung
Chia‐Ru Chung · 1×
Citations per year, relative to Chia‐Ru Chung
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Countries citing papers authored by Chia‐Ru Chung

Since Specialization
Citations

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

Fields of papers citing papers by Chia‐Ru Chung

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chia‐Ru Chung. 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 Chia‐Ru Chung. The network helps show where Chia‐Ru Chung may publish in the future.

Co-authorship network of co-authors of Chia‐Ru Chung

This figure shows the co-authorship network connecting the top 25 collaborators of Chia‐Ru Chung. A scholar is included among the top collaborators of Chia‐Ru Chung 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 Chia‐Ru Chung. Chia‐Ru Chung 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
# Work Indexed citations
1 2
2 4
3 19
4 10
5 17
6 7
7 4
8 11
9 11
10 21
11 6
12 9
13 2
14 20
15 19
16 27
17 15
18 7
19 4
20 19

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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