Cheng Ling

861 total citations · 1 hit paper
36 papers, 582 citations indexed

About

Cheng Ling is a scholar working on Molecular Biology, Plant Science and Genetics. According to data from OpenAlex, Cheng Ling has authored 36 papers receiving a total of 582 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 14 papers in Plant Science and 9 papers in Genetics. Recurrent topics in Cheng Ling's work include Genomics and Phylogenetic Studies (19 papers), Genetic diversity and population structure (8 papers) and Insect-Plant Interactions and Control (7 papers). Cheng Ling is often cited by papers focused on Genomics and Phylogenetic Studies (19 papers), Genetic diversity and population structure (8 papers) and Insect-Plant Interactions and Control (7 papers). Cheng Ling collaborates with scholars based in China, United Kingdom and Japan. Cheng Ling's co-authors include Arong Luo, Chao‐Dong Zhu, Simon Y. W. Ho, Khaled Benkrid, Yongfu Qiu, Jingyang Gao, Guoguang Zhao, Donghong Sun, Meng Yang and Ali Akoglu and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Access.

In The Last Decade

Cheng Ling

34 papers receiving 575 citations

Hit Papers

Comparison of Methods for Molecular Species Delimitation ... 2018 2026 2020 2023 2018 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Comparison of Methods for Molecular Species Delimitation Across a Range of Speciation Scenarios
    2018 309 citations Arong Luo, Cheng Ling et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cheng Ling China 9 248 186 142 138 114 36 582
Théo Trouillon France 3 170 0.7× 390 2.1× 127 0.9× 117 0.8× 146 1.3× 4 714
Teodor Georgiev Bulgaria 14 148 0.6× 142 0.8× 56 0.4× 172 1.2× 143 1.3× 59 593
Serita M. Nelesen United States 7 437 1.8× 229 1.2× 173 1.2× 114 0.8× 89 0.8× 10 758
Robert D. Edwards United States 14 122 0.5× 104 0.6× 76 0.5× 199 1.4× 115 1.0× 38 677
Karen Cranston United States 12 257 1.0× 180 1.0× 104 0.7× 138 1.0× 62 0.5× 20 532
Katja Schulz United States 5 155 0.6× 82 0.4× 44 0.3× 132 1.0× 127 1.1× 8 437
Chibiao Chen Singapore 5 113 0.5× 478 2.6× 80 0.6× 131 0.9× 279 2.4× 7 771
Richard T. Lapoint United States 10 236 1.0× 178 1.0× 106 0.7× 238 1.7× 117 1.0× 14 669
Jialiang Li China 13 226 0.9× 220 1.2× 141 1.0× 174 1.3× 64 0.6× 47 512
Anton Güntsch Germany 15 249 1.0× 48 0.3× 124 0.9× 141 1.0× 272 2.4× 65 730

Countries citing papers authored by Cheng Ling

Since Specialization
Citations

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

Fields of papers citing papers by Cheng Ling

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cheng Ling. 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 Cheng Ling. The network helps show where Cheng Ling may publish in the future.

Co-authorship network of co-authors of Cheng Ling

This figure shows the co-authorship network connecting the top 25 collaborators of Cheng Ling. A scholar is included among the top collaborators of Cheng Ling 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 Cheng Ling. Cheng Ling 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.
2.
Shen, Juan, et al.. (2024). Fine mapping and breeding application of two brown planthopper resistance genes derived from landrace rice. PLoS ONE. 19(4). e0297945–e0297945. 5 indexed citations
3.
Zhang, Mengyu, Jiang‐Yuan Zhao, Lele Li, et al.. (2023). Chitinolyticbacter albus sp. Nov., A Novel Chitin-Degrading Bacterium Isolated from Ancient Wood Rhizosphere Soil. Current Microbiology. 80(7). 225–225. 1 indexed citations
4.
Ling, Cheng, Jiang‐Yuan Zhao, Lele Li, et al.. (2023). Pseudomonas subflava sp. nov., a new Gram-negative bacterium isolated from Guishan in Yunnan province, south–west China. Antonie van Leeuwenhoek. 116(6). 557–564. 2 indexed citations
5.
Tang, Jing, Jiang‐Yuan Zhao, Lele Li, et al.. (2022). Cohnella mopanensis sp. nov., a new Gram-negative bacterium isolated from soil in Xinping Mountain National Forest Park. Archives of Microbiology. 204(8). 492–492. 2 indexed citations
6.
Zhao, Jiang‐Yuan, Lele Li, Cheng Ling, et al.. (2022). Brevibacillus daliensis sp. nov., Isolated From Soil in Machangqing Nature Reserve. Current Microbiology. 80(1). 32–32. 1 indexed citations
7.
8.
Ling, Cheng, et al.. (2021). Improved phenotyping procedure for evaluating resistance in rice against gall midge (Orseolia oryzae, Wood-Mason). Plant Methods. 17(1). 121–121. 4 indexed citations
9.
Wang, Xinyi, Yi Mo, Li Yang, et al.. (2020). Genetic analysis and fine mapping of the gall midge resistance gene Gm5 in rice (Oryza sativa L.). Theoretical and Applied Genetics. 133(6). 2021–2033. 6 indexed citations
10.
Ling, Cheng, et al.. (2020). Cnngeno: A high-precision deep learning based strategy for the calling of structural variation genotype. Computational Biology and Chemistry. 94. 107417–107417. 4 indexed citations
11.
Yang, Li, Yi Mo, Zhihua Li, et al.. (2019). Characterization and application of a gall midge resistance gene (Gm6) from Oryza sativa ‘Kangwenqingzhan’. Theoretical and Applied Genetics. 133(2). 579–591. 6 indexed citations
12.
13.
Gao, Jingyang, et al.. (2018). GPU Parallelism of Phylogenetic Likelihood Estimates for Protein Data. 13. 632–639.
14.
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Ling, Cheng, et al.. (2017). CNNdel: Calling Structural Variations on Low Coverage Data Based on Convolutional Neural Networks. BioMed Research International. 2017. 1–8. 3 indexed citations
16.
Luo, Arong, Haiqiang Lan, Cheng Ling, et al.. (2015). A simulation study of sample size for DNA barcoding. Ecology and Evolution. 5(24). 5869–5879. 32 indexed citations
17.
Ling, Cheng, et al.. (2013). MrBayes tgMC3: A Tight GPU Implementation of MrBayes. PLoS ONE. 8(4). e60667–e60667. 8 indexed citations
18.
Qiu, Yongfu, et al.. (2013). Identification of a new locus conferring antixenosis to the brown planthopper in rice cultivar Swarnalata (Oryza sativa L.). Genetics and Molecular Research. 12(3). 3201–3211. 12 indexed citations
19.
Benkrid, Khaled, et al.. (2012). High Performance Biological Pairwise Sequence Alignment: FPGA versus GPU versus Cell BE versus GPP. SHILAP Revista de lepidopterología. 2012. 1–15. 36 indexed citations
20.
Ling, Cheng & Khaled Benkrid. (2010). Design and implementation of a CUDA-compatible GPU-based core for gapped BLAST algorithm. Procedia Computer Science. 1(1). 495–504. 23 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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