Taedong Yun

1.1k total citations
9 papers, 224 citations indexed

About

Taedong Yun is a scholar working on Genetics, Molecular Biology and Discrete Mathematics and Combinatorics. According to data from OpenAlex, Taedong Yun has authored 9 papers receiving a total of 224 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Genetics, 4 papers in Molecular Biology and 3 papers in Discrete Mathematics and Combinatorics. Recurrent topics in Taedong Yun's work include Genetic Associations and Epidemiology (4 papers), Advanced Graph Theory Research (2 papers) and Epigenetics and DNA Methylation (2 papers). Taedong Yun is often cited by papers focused on Genetic Associations and Epidemiology (4 papers), Advanced Graph Theory Research (2 papers) and Epigenetics and DNA Methylation (2 papers). Taedong Yun collaborates with scholars based in United States, United Kingdom and Netherlands. Taedong Yun's co-authors include Andrew Carroll, Cory Y. McLean, Pi-Chuan Chang, Michael Lin, Helen Li, Alexey Kolesnikov, Howard H. Yang, Waleed Ammar, Anastasiya Belyaeva and William J. Rowell and has published in prestigious journals such as Nature Communications, Nature Genetics and Nature Biotechnology.

In The Last Decade

Taedong Yun

5 papers receiving 224 citations

Peers

Taedong Yun

MB

GENET

PS

CR

ECOLO

Liudmila S. Mainzer United States

Aoife Doherty United Kingdom

Snædís Kristmundsdóttir Iceland

Michael T. Kalmbach United States

Zhi Yan United States

Jacob R. Heldenbrand United States

Kristina Gagalova Canada

Sairam Behera United States

Ruchi Chaudhary United States

Liudmila S. Mainzer United States

Taedong Yun

139 ×1.2

MB

107 ×1.1

GENET

49 ×1.3

PS

39 ×1.4

CR

12 ×0.8

ECOLO

Citations per year, relative to Taedong Yun Taedong Yun (= 1×) peers Liudmila S. Mainzer

Countries citing papers authored by Taedong Yun

Since Specialization

Citations

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

Fields of papers citing papers by Taedong Yun

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Taedong Yun

This figure shows the co-authorship network connecting the top 25 collaborators of Taedong Yun. A scholar is included among the top collaborators of Taedong Yun 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 Taedong Yun. Taedong Yun is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

9 of 9 papers shown

1.

Yun, Taedong, Jacqueline Baras Shreibati, Dongbing Lai, et al.. (2025). Applying multimodal AI to physiological waveforms improves genetic prediction of cardiovascular traits. The American Journal of Human Genetics. 112(7). 1562–1579.

2.

Yun, Taedong, Zachary R. McCaw, Robert Luben, et al.. (2024). Unsupervised representation learning on high-dimensional clinical data improves genomic discovery and prediction. Nature Genetics. 56(8). 1604–1613. 13 indexed citations

3.

Chen, Nae-Chyun, Alexey Kolesnikov, Sidharth Goel, et al.. (2023). Improving variant calling using population data and deep learning. BMC Bioinformatics. 24(1). 197–197. 10 indexed citations

4.

Baid, Gunjan, Daniel E. Cook, Kishwar Shafin, et al.. (2022). DeepConsensus improves the accuracy of sequences with a gap-aware sequence transformer. Nature Biotechnology. 41(2). 232–238. 89 indexed citations

5.

McCaw, Zachary R., Thomas Colthurst, Taedong Yun, et al.. (2022). DeepNull models non-linear covariate effects to improve phenotypic prediction and association power. Nature Communications. 13(1). 241–241. 18 indexed citations

6.

Yun, Taedong, Helen Li, Pi-Chuan Chang, et al.. (2020). Accurate, scalable cohort variant calls using DeepVariant and GLnexus. Bioinformatics. 36(24). 5582–5589. 94 indexed citations

7.

Yun, Taedong, et al.. (2013). Rainbow Graphs and Switching Classes. SIAM Journal on Discrete Mathematics. 27(2). 1106–1111.

8.

Yun, Taedong, et al.. (2013). Balanced labellings of affine permutations. Discrete Mathematics & Theoretical Computer Science. DMTCS Proceedings vol. AS,...(Proceedings).

9.

Yun, Taedong, et al.. (2011). Rainbow Graphs and Switching Classes. SIAM Journal on Control and Optimization.

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.

Explore authors with similar magnitude of impact