Hyunseung Yoo

7.0k total citations
24 papers, 763 citations indexed

About

Hyunseung Yoo is a scholar working on Molecular Biology, Computer Networks and Communications and Electrical and Electronic Engineering. According to data from OpenAlex, Hyunseung Yoo has authored 24 papers receiving a total of 763 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 8 papers in Computer Networks and Communications and 7 papers in Electrical and Electronic Engineering. Recurrent topics in Hyunseung Yoo's work include Advanced Data Storage Technologies (7 papers), Semiconductor materials and devices (6 papers) and Genomics and Phylogenetic Studies (4 papers). Hyunseung Yoo is often cited by papers focused on Advanced Data Storage Technologies (7 papers), Semiconductor materials and devices (6 papers) and Genomics and Phylogenetic Studies (4 papers). Hyunseung Yoo collaborates with scholars based in United States, South Korea and Denmark. Hyunseung Yoo's co-authors include Maulik Shukla, Thomas Brettin, Rick Stevens, Fangfang Xia, Robert Olson, James J. Davis, Gordon D. Pusch, Alice R. Wattam, Veronika Vonstein and Svetlana Gerdes and has published in prestigious journals such as Journal of Clinical Oncology, Applied Physics Letters and Scientific Reports.

In The Last Decade

Hyunseung Yoo

23 papers receiving 749 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hyunseung Yoo United States 13 284 117 106 98 84 24 763
Bernd Neumann Germany 18 135 0.5× 40 0.3× 120 1.1× 125 1.3× 66 0.8× 97 1.3k
Laurence Yang United States 26 1.4k 4.9× 42 0.4× 81 0.8× 57 0.6× 46 0.5× 68 1.9k
Licheng Zhao China 18 215 0.8× 140 1.2× 73 0.7× 81 0.8× 159 1.9× 46 1.0k
Wei-Ting Liu Taiwan 18 580 2.0× 91 0.8× 137 1.3× 25 0.3× 28 0.3× 50 1.3k
Dexian Zhang China 21 225 0.8× 154 1.3× 38 0.4× 57 0.6× 30 0.4× 169 1.5k
Michael R. Leuze United States 13 627 2.2× 35 0.3× 90 0.8× 35 0.4× 18 0.2× 32 1.3k
Chuan Yi Tang Taiwan 23 596 2.1× 95 0.8× 270 2.5× 188 1.9× 13 0.2× 145 1.7k
Minyi Li Australia 11 111 0.4× 78 0.7× 49 0.5× 89 0.9× 9 0.1× 44 569
Sabah Jassim United Kingdom 22 393 1.4× 38 0.3× 57 0.5× 33 0.3× 12 0.1× 136 2.2k
Honghai Wang China 23 753 2.7× 79 0.7× 93 0.9× 123 1.3× 11 0.1× 123 2.2k

Countries citing papers authored by Hyunseung Yoo

Since Specialization
Citations

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

Fields of papers citing papers by Hyunseung Yoo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hyunseung Yoo

This figure shows the co-authorship network connecting the top 25 collaborators of Hyunseung Yoo. A scholar is included among the top collaborators of Hyunseung Yoo 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 Hyunseung Yoo. Hyunseung Yoo 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.
Clyde, Austin, Xuefeng Liu, Thomas Brettin, et al.. (2023). AI-accelerated protein-ligand docking for SARS-CoV-2 is 100-fold faster with no significant change in detection. Scientific Reports. 13(1). 2105–2105. 16 indexed citations
2.
Zhu, Yitan, Thomas Brettin, Fangfang Xia, et al.. (2021). Publisher Correction: Converting tabular data into images for deep learning with convolutional neural networks. Scientific Reports. 11(1). 14036–14036. 7 indexed citations
3.
Liu, Zhengchun, Ahsan Ali, Péter Kenesei, et al.. (2021). Bridging Data Center AI Systems with Edge Computing for Actionable Information Retrieval. 15–23. 16 indexed citations
4.
Zhu, Yitan, Thomas Brettin, Fangfang Xia, et al.. (2021). Converting tabular data into images for deep learning with convolutional neural networks. Scientific Reports. 11(1). 11325–11325. 116 indexed citations
5.
Nguyen, Marcus, Derya Aytan-Aktug, Thomas Brettin, et al.. (2021). A genomic data resource for predicting antimicrobial resistance from laboratory-derived antimicrobial susceptibility phenotypes. Briefings in Bioinformatics. 22(6). 18 indexed citations
6.
Zhu, Yitan, Thomas Brettin, Yvonne A. Evrard, et al.. (2020). Enhanced Co-Expression Extrapolation (COXEN) Gene Selection Method for Building Anti-Cancer Drug Response Prediction Models. Genes. 11(9). 1070–1070. 9 indexed citations
7.
Zhu, Yitan, Thomas Brettin, Yvonne A. Evrard, et al.. (2020). Ensemble transfer learning for the prediction of anti-cancer drug response. Scientific Reports. 10(1). 18040–18040. 49 indexed citations
8.
Wozniak, Justin M., Hyunseung Yoo, Jamaludin Mohd‐Yusof, et al.. (2020). High-bypass Learning: Automated Detection of Tumor Cells That Significantly Impact Drug Response. 1–10. 5 indexed citations
9.
Hintze, Bradley J., Maulik Shukla, Thomas Brettin, et al.. (2019). Genomic Analysis of Metastatic Solid Tumors in Veterans: Findings From the VHA National Precision Oncology Program. JCO Precision Oncology. 3(3). 1–13. 12 indexed citations
10.
Nguyen, Marcus, Thomas Brettin, S. Wesley Long, et al.. (2018). Developing an in silico minimum inhibitory concentration panel test for Klebsiella pneumoniae. Scientific Reports. 8(1). 421–421. 123 indexed citations
11.
Wattam, Alice R., Thomas Brettin, James J. Davis, et al.. (2017). Assembly, Annotation, and Comparative Genomics in PATRIC, the All Bacterial Bioinformatics Resource Center. Methods in molecular biology. 1704. 79–101. 76 indexed citations
12.
Choi, Woo Young, et al.. (2016). Influence of Intercell Trapped Charge on Vertical NAND Flash Memory. IEEE Electron Device Letters. 38(2). 164–167. 19 indexed citations
13.
Davis, James J., Svetlana Gerdes, Gary J. Olsen, et al.. (2016). PATtyFams: Protein Families for the Microbial Genomes in the PATRIC Database. Frontiers in Microbiology. 7. 118–118. 161 indexed citations
14.
Yoo, Hyunseung, et al.. (2013). Modeling and optimization of the chip level program disturbance of 3D NAND Flash memory. 147–150. 17 indexed citations
15.
Aritome, S., S. J. Whang, Ki-Hong Lee, et al.. (2012). A novel three-dimensional dual control-gate with surrounding floating-gate (DC-SF) NAND flash cell. Solid-State Electronics. 79. 166–171. 7 indexed citations
16.
Choi, Eun-Seok, et al.. (2011). A Novel 3D Cell Array Architecture for Terra-Bit NAND Flash Memory. 1–4. 17 indexed citations
17.
Whang, S. J., Ki-Hong Lee, Minsoo Kim, et al.. (2010). Novel 3-dimensional Dual Control-gate with Surrounding Floating-gate (DC-SF) NAND flash cell for 1Tb file storage application. 29.7.1–29.7.4. 63 indexed citations
18.
Kim, Jong‐Hun, Hyunho Noh, Z. G. Khim, et al.. (2008). Electrostatic force microscopy study about the hole trap in thin nitride/oxide/semiconductor structure. Applied Physics Letters. 92(13). 6 indexed citations
19.
Kim, Jeonghyun, et al.. (2008). Integrated tunnel monitoring system using wireless automated data collection technology. 337–342. 7 indexed citations
20.
Yoo, Hyunseung. (2007). An Analysis of the Frictional Energy on the Rubber Block. Journal of the Korean Society for Aeronautical & Space Sciences. 35(7). 619–626. 1 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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