Sunmo Yang

3.9k total citations · 1 hit paper
28 papers, 2.1k citations indexed

About

Sunmo Yang is a scholar working on Molecular Biology, Genetics and Surgery. According to data from OpenAlex, Sunmo Yang has authored 28 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Molecular Biology, 6 papers in Genetics and 3 papers in Surgery. Recurrent topics in Sunmo Yang's work include Bioinformatics and Genomic Networks (13 papers), Gene expression and cancer classification (7 papers) and Genomics and Phylogenetic Studies (6 papers). Sunmo Yang is often cited by papers focused on Bioinformatics and Genomic Networks (13 papers), Gene expression and cancer classification (7 papers) and Genomics and Phylogenetic Studies (6 papers). Sunmo Yang collaborates with scholars based in South Korea, United States and Germany. Sunmo Yang's co-authors include Insuk Lee, Chan Yeong Kim, Hyojin Kim, Muyoung Lee, Sung‐Ho Lee, Byunghee Kang, Sohyun Hwang, Hyeon-Nae Jeon, Heonjong Han and Michael Chung and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and Scientific Reports.

In The Last Decade

Sunmo Yang

26 papers receiving 2.1k citations

Hit Papers

TRRUST v2: an expanded reference database of human and mo... 2017 2026 2020 2023 2017 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sunmo Yang South Korea 15 1.4k 342 236 203 176 28 2.1k
Chan Yeong Kim South Korea 13 1.3k 0.9× 338 1.0× 234 1.0× 202 1.0× 145 0.8× 18 1.9k
Manhong Dai United States 13 1.3k 1.0× 301 0.9× 199 0.8× 116 0.6× 269 1.5× 22 2.0k
Gang Feng China 20 1.3k 0.9× 230 0.7× 179 0.8× 111 0.5× 303 1.7× 45 2.0k
Guohui Ding China 24 1.2k 0.8× 428 1.3× 116 0.5× 148 0.7× 126 0.7× 89 2.0k
Yongchun Zuo China 31 2.1k 1.5× 317 0.9× 152 0.6× 241 1.2× 140 0.8× 127 2.8k
Sang Cheol Kim South Korea 28 1.1k 0.8× 402 1.2× 200 0.8× 257 1.3× 170 1.0× 92 2.3k
Constantin Georgescu United States 22 1.3k 0.9× 322 0.9× 358 1.5× 153 0.8× 150 0.9× 74 2.3k
Sung‐Ho Lee South Korea 16 1.4k 1.0× 293 0.9× 256 1.1× 174 0.9× 115 0.7× 36 2.1k
Martina Kutmon Netherlands 17 1.4k 1.0× 325 1.0× 190 0.8× 150 0.7× 218 1.2× 51 2.1k
Stephanie D. Byrum United States 27 1.9k 1.3× 245 0.7× 185 0.8× 169 0.8× 210 1.2× 116 2.6k

Countries citing papers authored by Sunmo Yang

Since Specialization
Citations

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

Fields of papers citing papers by Sunmo Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sunmo Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Sunmo Yang. A scholar is included among the top collaborators of Sunmo 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 Sunmo Yang. Sunmo Yang 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.
Lee, Sung-Ho, et al.. (2025). A high-quality genomic catalog of the human oral microbiome broadens its phylogeny and clinical insights. Cell Host & Microbe. 33(11). 1977–1994.e8.
2.
Kim, W. Ray, Chan Yeong Kim, Yong‐ho Lee, et al.. (2025). A human gut metagenome-assembled genome catalogue spanning 41 countries supports genome-scale metabolic models. Nature Microbiology. 11(1). 317–334.
3.
Kim, Chan Yeong, et al.. (2024). MRGM: an enhanced catalog of mouse gut microbial genomes substantially broadening taxonomic and functional landscapes. Gut Microbes. 16(1). 2393791–2393791. 4 indexed citations
4.
Kim, Chan Yeong, Muyoung Lee, Sunmo Yang, et al.. (2021). Human reference gut microbiome catalog including newly assembled genomes from under-represented Asian metagenomes. Genome Medicine. 13(1). 134–134. 65 indexed citations
5.
Kim, Chan Yeong, Sunmo Yang, Eiru Kim, et al.. (2021). HumanNet v3: an improved database of human gene networks for disease research. Nucleic Acids Research. 50(D1). D632–D639. 78 indexed citations
6.
Lee, Sung‐Ho, Tak Lee, Sunmo Yang, & Insuk Lee. (2020). BarleyNet: A Network-Based Functional Omics Analysis Server for Cultivated Barley, Hordeum vulgare L.. Frontiers in Plant Science. 11. 98–98. 14 indexed citations
8.
Lee, Tak, Sung‐Ho Lee, Sunmo Yang, & Insuk Lee. (2019). MaizeNet: a co‐functional network for network‐assisted systems genetics in Zea mays. The Plant Journal. 99(3). 571–582. 14 indexed citations
9.
10.
Han, Heonjong, Sangyoung Lee, Hyojin Kim, et al.. (2017). TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions. Nucleic Acids Research. 46(D1). D380–D386. 1238 indexed citations breakdown →
11.
Shim, Jung Eun, Sunmo Yang, Tak Lee, et al.. (2017). GWAB: a web server for the network-based boosting of human genome-wide association data. Nucleic Acids Research. 45(W1). W154–W161. 20 indexed citations
12.
Yang, Sunmo, Chan Yeong Kim, Sohyun Hwang, et al.. (2016). COEXPEDIA: exploring biomedical hypotheses via co-expressions associated with medical subject headings (MeSH). Nucleic Acids Research. 45(D1). D389–D396. 81 indexed citations
13.
Shim, Hongseok, Ji Hyun Kim, Chan Yeong Kim, et al.. (2016). Function-driven discovery of disease genes in zebrafish using an integrated genomics big data resource. Nucleic Acids Research. 44(20). gkw897–gkw897. 17 indexed citations
14.
Hwang, Sohyun, Chan Yeong Kim, Sun‐Gou Ji, et al.. (2016). Network-assisted investigation of virulence and antibiotic-resistance systems in Pseudomonas aeruginosa. Scientific Reports. 6(1). 26223–26223. 24 indexed citations
15.
Lee, Tak, Taeyun Oh, Sunmo Yang, et al.. (2015). RiceNet v2: an improved network prioritization server for rice genes. Nucleic Acids Research. 43(W1). W122–W127. 61 indexed citations
16.
Kim, Eiru, Sohyun Hwang, Hyojin Kim, et al.. (2015). MouseNet v2: a database of gene networks for studying the laboratory mouse and eight other model vertebrates. Nucleic Acids Research. 44(D1). D848–D854. 28 indexed citations
17.
Shin, Junha, Sunmo Yang, Eiru Kim, et al.. (2015). FlyNet: a versatile network prioritization server for theDrosophilacommunity. Nucleic Acids Research. 43(W1). W91–W97. 13 indexed citations
18.
Lee, Tak, Sunmo Yang, Eiru Kim, et al.. (2014). AraNet v2: an improved database of co-functional gene networks for the study of Arabidopsis thaliana and 27 other nonmodel plant species. Nucleic Acids Research. 43(D1). D996–D1002. 128 indexed citations
19.
Hwang, Sohyun, Eiru Kim, Sunmo Yang, Edward M. Marcotte, & Insuk Lee. (2014). MORPHIN: a web tool for human disease research by projecting model organism biology onto a human integrated gene network. Nucleic Acids Research. 42(W1). W147–W153. 13 indexed citations
20.
Yang, Sunmo, et al.. (2005). Development of a rule-based inference model for human sensibility engineering system. Journal of Mechanical Science and Technology. 19(3). 743–755. 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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