Chang–Gwon Dang

751 total citations
40 papers, 495 citations indexed

About

Chang–Gwon Dang is a scholar working on Genetics, Animal Science and Zoology and Cancer Research. According to data from OpenAlex, Chang–Gwon Dang has authored 40 papers receiving a total of 495 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Genetics, 14 papers in Animal Science and Zoology and 6 papers in Cancer Research. Recurrent topics in Chang–Gwon Dang's work include Genetic and phenotypic traits in livestock (27 papers), Genetic Mapping and Diversity in Plants and Animals (15 papers) and Effects of Environmental Stressors on Livestock (8 papers). Chang–Gwon Dang is often cited by papers focused on Genetic and phenotypic traits in livestock (27 papers), Genetic Mapping and Diversity in Plants and Animals (15 papers) and Effects of Environmental Stressors on Livestock (8 papers). Chang–Gwon Dang collaborates with scholars based in South Korea, Australia and India. Chang–Gwon Dang's co-authors include Seung Hwan Lee, Aditi Sharma, Tae-Jeong Choi, Jun Seop Lee, Hyeong–Cheol Kim, Si-Dong Kim, Byoungho Park, Seung Soo Lee, Soo‐Bong Park and Jong-Joo Kim and has published in prestigious journals such as PLoS ONE, Sensors and Journal of Animal Science.

In The Last Decade

Chang–Gwon Dang

35 papers receiving 478 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Chang–Gwon Dang South Korea 11 379 154 141 84 67 40 495
Tingxian Deng China 12 329 0.9× 128 0.8× 117 0.8× 154 1.8× 156 2.3× 46 537
Gul Won Jang South Korea 13 426 1.1× 195 1.3× 170 1.2× 51 0.6× 176 2.6× 38 624
Zezhao Wang China 15 399 1.1× 171 1.1× 96 0.7× 89 1.1× 90 1.3× 43 503
Hyun‐Tae Lim South Korea 15 364 1.0× 106 0.7× 302 2.1× 42 0.5× 164 2.4× 62 643
Tae-Jeong Choi South Korea 12 466 1.2× 99 0.6× 245 1.7× 139 1.7× 46 0.7× 73 583
Rongrong Ding China 15 465 1.2× 230 1.5× 128 0.9× 39 0.5× 129 1.9× 37 598
Masood Asadi Fozi Iran 11 289 0.8× 44 0.3× 128 0.9× 98 1.2× 58 0.9× 37 377
Mervi Honkatukia Finland 12 350 0.9× 63 0.4× 237 1.7× 57 0.7× 103 1.5× 27 543
Diércles F. Cardoso Brazil 15 525 1.4× 151 1.0× 88 0.6× 168 2.0× 70 1.0× 36 646

Countries citing papers authored by Chang–Gwon Dang

Since Specialization
Citations

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

Fields of papers citing papers by Chang–Gwon Dang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chang–Gwon Dang. 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 Chang–Gwon Dang. The network helps show where Chang–Gwon Dang may publish in the future.

Co-authorship network of co-authors of Chang–Gwon Dang

This figure shows the co-authorship network connecting the top 25 collaborators of Chang–Gwon Dang. A scholar is included among the top collaborators of Chang–Gwon Dang 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 Chang–Gwon Dang. Chang–Gwon Dang 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.
Dang, Chang–Gwon, et al.. (2024). Korean Cattle 3D Reconstruction from Multi-View 3D-Camera System in Real Environment. Sensors. 24(2). 427–427. 3 indexed citations
3.
Park, Mi Na, et al.. (2024). Utilizing 3D Point Cloud Technology with Deep Learning for Automated Measurement and Analysis of Dairy Cows. Sensors. 24(3). 987–987. 9 indexed citations
4.
Seo, Jeong-Woo, et al.. (2024). Estimation of genetic parameters for reproductive traits in Korean dairy cattle. Animal Bioscience. 38(1). 33–40. 1 indexed citations
5.
6.
Haque, Md Azizul, et al.. (2023). Genome-Wide Association Studies for Body Conformation Traits in Korean Holstein Population. Animals. 13(18). 2964–2964. 12 indexed citations
7.
Park, Woncheoul, et al.. (2023). Case report: Investigation of genetic mutations in a case of schistosomus reflexus in a Holstein dairy cattle fetus in Korea. Frontiers in Veterinary Science. 10. 1238544–1238544. 2 indexed citations
8.
Lee, Soo-Hyun, Chang–Gwon Dang, Mi Na Park, et al.. (2022). Comparison of the estimated breeding value and accuracy by imputation reference Beadchip platform and scaling factor of the genomic relationship matrix in Hanwoo cattle. Korean Journal of Agricultural Science. 49(3). 431–440.
9.
Naserkheil, Masoumeh, et al.. (2022). Exploring and Identifying Candidate Genes and Genomic Regions Related to Economically Important Traits in Hanwoo Cattle. Current Issues in Molecular Biology. 44(12). 6075–6092. 7 indexed citations
10.
Dang, Chang–Gwon, et al.. (2022). Case Study: Improving the Quality of Dairy Cow Reconstruction with a Deep Learning-Based Framework. Sensors. 22(23). 9325–9325. 4 indexed citations
11.
12.
Kim, Sang-Wook, et al.. (2021). Genome-Wide Identification of Candidate Genes for Milk Production Traits in Korean Holstein Cattle. Animals. 11(5). 1392–1392. 20 indexed citations
13.
Dang, Chang–Gwon, et al.. (2020). Genetic parameters for milk fatty acid composition of Holstein in Korea. Asian-Australasian Journal of Animal Sciences. 33(10). 1573–1578. 5 indexed citations
14.
Lee, Yun-Mi, Chang–Gwon Dang, You-Sam Kim, et al.. (2019). The effectiveness of genomic selection for milk production traits of Holstein dairy cattle. Asian-Australasian Journal of Animal Sciences. 33(3). 382–389. 14 indexed citations
15.
Markkandan, Kesavan, Dong Jin Lee, Seung‐il Yoo, et al.. (2018). Data on transcriptome profiling of circulating microRNAs in dairy cattle. Data in Brief. 21. 775–778. 1 indexed citations
16.
Dang, Chang–Gwon, et al.. (2016). Analysis of Pedigree Structure and Inbreeding Coefficient for Performance Tested Holstein Cows in Korea. Journal of Agriculture & Life Science. 50(2). 107–116. 1 indexed citations
17.
Sharma, Aditi, et al.. (2015). Stories and Challenges of Genome Wide Association Studies in Livestock — A Review. Asian-Australasian Journal of Animal Sciences. 28(10). 1371–1379. 76 indexed citations
18.
Lee, Seung Hwan, Byoungho Park, Aditi Sharma, et al.. (2014). Hanwoo cattle: origin, domestication, breeding strategies and genomic selection. Journal of Animal Science and Technology. 56(1). 2–2. 103 indexed citations
19.
Lee, Seung Hwan, Bong‐Hwan Choi, Dajeong Lim, et al.. (2013). Genome-Wide Association Study Identifies Major Loci for Carcass Weight on BTA14 in Hanwoo (Korean Cattle). PLoS ONE. 8(10). e74677–e74677. 80 indexed citations
20.
Lee, Jung‐Jae, et al.. (2011). The Effect of Carcass Traits on Economic Values in Hanwoo. Korean Journal for Food Science of Animal Resources. 31(4). 603–608. 9 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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