Dongchan Yang

1.0k total citations
9 papers, 447 citations indexed

About

Dongchan Yang is a scholar working on Molecular Biology, Immunology and Neurology. According to data from OpenAlex, Dongchan Yang has authored 9 papers receiving a total of 447 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Immunology and 1 paper in Neurology. Recurrent topics in Dongchan Yang's work include Genomics and Chromatin Dynamics (5 papers), Single-cell and spatial transcriptomics (2 papers) and Immune Cell Function and Interaction (2 papers). Dongchan Yang is often cited by papers focused on Genomics and Chromatin Dynamics (5 papers), Single-cell and spatial transcriptomics (2 papers) and Immune Cell Function and Interaction (2 papers). Dongchan Yang collaborates with scholars based in South Korea, United States and Germany. Dongchan Yang's co-authors include Dongsup Kim, Inkyung Jung, Andrew Lee, Junghyun Eom, Suk‐Jo Kang, Eliezer Masliah, Changyoun Kim, Mirang Kim, Tristin Liu and Sora Chee and has published in prestigious journals such as Nucleic Acids Research, Nature Genetics and Nature Biotechnology.

In The Last Decade

Dongchan Yang

8 papers receiving 445 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dongchan Yang South Korea	7	296	104	98	50	31	9	447
Melissa Sorosina Italy	10	162 0.5×	50 0.5×	64 0.7×	94 1.9×	22 0.7×	30	379
Gregory D. Wall United States	3	245 0.8×	74 0.7×	38 0.4×	62 1.2×	36 1.2×	5	373
Ramil Nurtdinov Russia	13	411 1.4×	41 0.4×	149 1.5×	48 1.0×	27 0.9×	21	556
Sveinung Gundersen Norway	8	325 1.1×	70 0.7×	49 0.5×	69 1.4×	57 1.8×	11	461
Junghyun Eom South Korea	5	270 0.9×	93 0.9×	25 0.3×	43 0.9×	25 0.8×	7	336
Rafael Riudavets Puig Norway	5	284 1.0×	51 0.5×	45 0.5×	72 1.4×	52 1.7×	6	420
Ligia Mateiu Belgium	12	285 1.0×	157 1.5×	18 0.2×	46 0.9×	19 0.6×	29	480
Wenmin Zhang China	11	144 0.5×	42 0.4×	93 0.9×	30 0.6×	22 0.7×	20	313
Xueying Liang China	13	163 0.6×	74 0.7×	67 0.7×	32 0.6×	34 1.1×	32	359
Pablo García‐Miranda Spain	13	281 0.9×	45 0.4×	34 0.3×	41 0.8×	19 0.6×	33	486

Countries citing papers authored by Dongchan Yang

Since Specialization

Citations

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

Fields of papers citing papers by Dongchan Yang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dongchan Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Dongchan Yang. A scholar is included among the top collaborators of Dongchan Yang 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 Dongchan Yang. Dongchan Yang 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.

Xu, Yueyuan, et al.. (2026). Trimodal single-cell profiling of transcriptome, epigenome and 3D genome in complex tissues with scHiCAR. Nature Biotechnology.

2.

Park, Jiyeon, Dongchan Yang, Hanseul Yang, et al.. (2023). The transcription factor NFIL3/E4BP4 regulates the developmental stage–specific acquisition of basophil function. Journal of Allergy and Clinical Immunology. 153(1). 132–145. 6 indexed citations

3.

Lee, Andrew, Changyoun Kim, Seong-Wan Park, et al.. (2023). Characterization of altered molecular mechanisms in Parkinson’s disease through cell type–resolved multiomics analyses. Science Advances. 9(15). eabo2467–eabo2467. 34 indexed citations

4.

Yang, Dongchan, et al.. (2022). DeepLUCIA: predicting tissue-specific chromatin loops using Deep Learning-based Universal Chromatin Interaction Annotator. Bioinformatics. 38(14). 3501–3512. 6 indexed citations

5.

Jung, Inkyung, Anthony D. Schmitt, Yarui Diao, et al.. (2019). A compendium of promoter-centered long-range chromatin interactions in the human genome. Nature Genetics. 51(10). 1442–1449. 203 indexed citations

6.

Ryu, Jayoung, et al.. (2019). A new class of constitutively active super-enhancers is associated with fast recovery of 3D chromatin loops. BMC Bioinformatics. 20(S3). 127–127. 21 indexed citations

7.

Yang, Dongchan, Mirang Kim, Jae‐Hoon Choi, et al.. (2018). Inflammation induces two types of inflammatory dendritic cells in inflamed lymph nodes. Experimental & Molecular Medicine. 50(3). e458–e458. 49 indexed citations

8.

Yang, Dongchan, Insu Jang, Jinhyuk Choi, et al.. (2017). 3DIV: A 3D-genome Interaction Viewer and database. Nucleic Acids Research. 46(D1). D52–D57. 74 indexed citations

9.

Kim, Minhyeok, Dongchan Yang, Mirang Kim, et al.. (2017). A late-lineage murine neutrophil precursor population exhibits dynamic changes during demand-adapted granulopoiesis. Scientific Reports. 7(1). 39804–39804. 54 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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