Liang-Bi Chen

6.1k total citations · 1 hit paper
223 papers, 4.3k citations indexed

About

Liang-Bi Chen is a scholar working on Plant Science, Electrical and Electronic Engineering and Molecular Biology. According to data from OpenAlex, Liang-Bi Chen has authored 223 papers receiving a total of 4.3k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Plant Science, 40 papers in Electrical and Electronic Engineering and 36 papers in Molecular Biology. Recurrent topics in Liang-Bi Chen's work include Plant Molecular Biology Research (22 papers), Plant Stress Responses and Tolerance (20 papers) and Water Quality Monitoring Technologies (16 papers). Liang-Bi Chen is often cited by papers focused on Plant Molecular Biology Research (22 papers), Plant Stress Responses and Tolerance (20 papers) and Water Quality Monitoring Technologies (16 papers). Liang-Bi Chen collaborates with scholars based in Taiwan, China and United States. Liang-Bi Chen's co-authors include Wan‐Jung Chang, Sheng Luan, Manzhong Liang, Dandan Mao, Xing Wang Deng, Dong-Ping Li, Hang He, Lianfu Tian, Dongping Li and Guangming He and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Plant Cell and Current Biology.

In The Last Decade

Liang-Bi Chen

203 papers receiving 4.1k citations

Hit Papers

Global Epigenetic and Transcriptional Trends among Two Ri... 2010 2026 2015 2020 2010 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Liang-Bi Chen Taiwan 33 2.4k 1.3k 355 355 332 223 4.3k
Peng Chen China 32 919 0.4× 1.1k 0.8× 390 1.1× 123 0.3× 177 0.5× 210 4.0k
Yang Li China 35 1.1k 0.5× 280 0.2× 590 1.7× 91 0.3× 412 1.2× 200 3.9k
Ning Ye China 33 533 0.2× 1.2k 1.0× 866 2.4× 236 0.7× 164 0.5× 239 3.7k
Τao Zhu China 30 800 0.3× 778 0.6× 77 0.2× 104 0.3× 561 1.7× 233 3.2k
Soo In Lee South Korea 31 1.7k 0.7× 1.3k 1.0× 104 0.3× 88 0.2× 313 0.9× 230 3.6k
Wensheng Wang China 40 3.3k 1.4× 2.7k 2.1× 146 0.4× 815 2.3× 45 0.1× 168 5.8k
Simon Pearson United Kingdom 30 2.6k 1.1× 282 0.2× 201 0.6× 95 0.3× 221 0.7× 128 4.5k
Wen‐Hui Lin China 28 1.3k 0.5× 960 0.7× 66 0.2× 135 0.4× 180 0.5× 122 2.8k
Changying Li United States 42 3.3k 1.4× 455 0.4× 227 0.6× 166 0.5× 215 0.6× 182 5.3k
Han Li China 33 1.3k 0.6× 1.6k 1.2× 76 0.2× 205 0.6× 86 0.3× 207 3.9k

Countries citing papers authored by Liang-Bi Chen

Since Specialization
Citations

This map shows the geographic impact of Liang-Bi Chen'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 Liang-Bi Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liang-Bi Chen more than expected).

Fields of papers citing papers by Liang-Bi Chen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Liang-Bi Chen. 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 Liang-Bi Chen. The network helps show where Liang-Bi Chen may publish in the future.

Co-authorship network of co-authors of Liang-Bi Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Liang-Bi Chen. A scholar is included among the top collaborators of Liang-Bi Chen 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 Liang-Bi Chen. Liang-Bi Chen 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
1.
Hadid, Wael, et al.. (2025). Sustainability Reporting and External Assurance: Evidence From UK Listed Firms. Business Strategy and the Environment. 35(2). 1684–1711.
2.
Kuo, Szu‐Yu, et al.. (2025). Cad-Transformer: A CNN–Transformer Hybrid Framework for Automatic Appearance Defect Classification of Shipping Containers. IEEE Transactions on Instrumentation and Measurement. 74. 1–21. 2 indexed citations
4.
Chen, Liang-Bi, et al.. (2024). An Orchid Classification Scheme Using Deep Learning for Automated Packaging in Production Lines. IEEE Consumer Electronics Magazine. 14(1). 65–76. 1 indexed citations
5.
Hu, Wu-Chih, et al.. (2024). A Method for Abnormal Behavior Recognition in Aquaculture Fields Using Deep Learning. Canadian Journal of Electrical and Computer Engineering. 47(3). 118–126. 3 indexed citations
6.
Wang, Feng, et al.. (2023). OsJRL40, a Jacalin-Related Lectin Gene, Promotes Salt Stress Tolerance in Rice. International Journal of Molecular Sciences. 24(8). 7441–7441. 11 indexed citations
7.
Chang, Wan‐Jung, et al.. (2020). A Mobile Device-Based Hairy Scalp Diagnosis System Using Deep Learning Techniques. 145–146. 9 indexed citations
8.
Jiang, Nan, Xinhui Zhao, Jun Fu, et al.. (2020). Identification of the blast resistance gene Picl(t) from Chaling common wild rice (Oryza rufipogon Griff.). Journal of Phytopathology. 168(4). 211–219. 2 indexed citations
9.
Wang, Kai, Shilong Xu, Wei‐Cheng Wang, et al.. (2019). Characterization of grain cadmium concentration in indica hybrid rice. Frontiers of Agricultural Science and Engineering. 7(4). 523–523. 1 indexed citations
10.
Su, Jian-Ping, et al.. (2018). An Intelligent Scalp Inspection and Diagnosis System for Caring Hairy Scalp Health. 507–508. 9 indexed citations
12.
Chen, Liang-Bi, Chia‐Wei Tsai, Wan‐Jung Chang, Yuh-Ming Cheng, & Katherine Shu-Min Li. (2016). A real-time mobile emergency assistance system for helping deaf-mute people/elderly singletons. 45–46. 7 indexed citations
13.
Mao, Dandan, Jian Chen, Lianfu Tian, et al.. (2014). Arabidopsis Transporter MGT6 Mediates Magnesium Uptake and Is Required for Growth under Magnesium Limitation. The Plant Cell. 26(5). 2234–2248. 96 indexed citations
14.
Dai, Xiaojun, et al.. (2014). Effects of cytoplasm on the fertility of thermo-sensitive genetic male sterile (TGMS) lines of rice. Australian Journal of Crop Science. 8(7). 999–1004. 1 indexed citations
15.
Huang, Xi, Xinhao Ouyang, Panyu Yang, et al.. (2013). Conversion from CUL4-based COP1–SPA E3 apparatus to UVR8–COP1–SPA complexes underlies a distinct biochemical function of COP1 under UV-B. Proceedings of the National Academy of Sciences. 110(41). 16669–16674. 154 indexed citations
16.
Li, Weilin, et al.. (2013). Identification of the Different Aroma Compounds between Conventional and Freeze Dried Wuyi Rock Tea (Dangui) using Headspace Solid Phase Microextraction. Food Science and Technology Research. 19(5). 805–811. 17 indexed citations
17.
Chen, Liang-Bi, Yen‐Ling Chen, & Ing-Jer Huang. (2011). A Real-Time Power Analysis Platform for Power-Aware Embedded System Development. Journal of information science and engineering. 27(3). 1165–1182. 8 indexed citations
18.
Chen, Liang-Bi, et al.. (2009). Determination of Acrylamide in Foods by Solid Phase Microextraction-Gas Chromatography. Food Science and Biotechnology. 18(4). 895–899. 7 indexed citations
19.
Liang, Manzhong, et al.. (2004). Genetic analysis of TGMS rice shuangdi pei eS with eui gene. Zuo wu xue bao. 30(8). 811–815. 1 indexed citations
20.
Chen, Liang-Bi, et al.. (2004). Effect of temperature on change in starch accumulation and activity of fru-1,6-P_(2)ase during grain filling stage. Nongye xiandaihua yanjiu. 25(4). 310–312. 1 indexed citations

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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