Jang‐Hyun Oh

1.0k total citations
10 papers, 754 citations indexed

About

Jang‐Hyun Oh is a scholar working on Molecular Biology, Oncology and Infectious Diseases. According to data from OpenAlex, Jang‐Hyun Oh has authored 10 papers receiving a total of 754 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 4 papers in Oncology and 3 papers in Infectious Diseases. Recurrent topics in Jang‐Hyun Oh's work include Peptidase Inhibition and Analysis (4 papers), Ubiquitin and proteasome pathways (4 papers) and Signaling Pathways in Disease (3 papers). Jang‐Hyun Oh is often cited by papers focused on Peptidase Inhibition and Analysis (4 papers), Ubiquitin and proteasome pathways (4 papers) and Signaling Pathways in Disease (3 papers). Jang‐Hyun Oh collaborates with scholars based in United States, South Korea and Sudan. Jang‐Hyun Oh's co-authors include Alexander Varshavsky, Cheol‐Sang Hwang, Won‐Ki Huh, Hyung‐Soon Yim, Shun‐Jia Chen, Gi‐eun Rhie, Sa-Ouk Kang, Brandon Wadas, Heonki Kim and Hanna Cho and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Jang‐Hyun Oh

10 papers receiving 749 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jang‐Hyun Oh United States	9	540	249	186	143	101	10	754
Yannick Mahé France	12	1.1k 2.0×	312 1.3×	178 1.0×	155 1.1×	135 1.3×	13	1.4k
Sven O. Dahms Germany	18	437 0.8×	104 0.4×	164 0.9×	46 0.3×	39 0.4×	31	810
H. Bart van den Hazel Denmark	10	556 1.0×	99 0.4×	92 0.5×	102 0.7×	91 0.9×	10	726
Luc van Dyck Belgium	11	946 1.8×	176 0.7×	79 0.4×	99 0.7×	108 1.1×	18	1.2k
Wenchuan Leng China	15	395 0.7×	80 0.3×	95 0.5×	220 1.5×	82 0.8×	24	695
J. Jacob Strouse United States	11	215 0.4×	85 0.3×	118 0.6×	72 0.5×	38 0.4×	15	505
D R Johnson United States	11	718 1.3×	67 0.3×	73 0.4×	68 0.5×	94 0.9×	12	907
Parag P. Sadhale India	18	1.1k 2.1×	78 0.3×	77 0.4×	56 0.4×	173 1.7×	39	1.3k
Xiang S. Ye United States	13	562 1.0×	100 0.4×	78 0.4×	62 0.4×	174 1.7×	17	748
John A. Buglino United States	14	762 1.4×	65 0.3×	111 0.6×	100 0.7×	37 0.4×	18	986

Countries citing papers authored by Jang‐Hyun Oh

Since Specialization

Citations

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

Fields of papers citing papers by Jang‐Hyun Oh

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jang‐Hyun Oh. 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 Jang‐Hyun Oh. The network helps show where Jang‐Hyun Oh may publish in the future.

Co-authorship network of co-authors of Jang‐Hyun Oh

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

All Works

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10 of 10 papers shown

Oh, Jang‐Hyun, et al.. (2020). Five enzymes of the Arg/N-degron pathway form a targeting complex: The concept of superchanneling. Proceedings of the National Academy of Sciences. 117(20). 10778–10788. 21 indexed citations

Chen, Shun‐Jia, et al.. (2017). An N-end rule pathway that recognizes proline and destroys gluconeogenic enzymes. Science. 355(6323). 157 indexed citations

Oh, Jang‐Hyun, Shun‐Jia Chen, & Alexander Varshavsky. (2017). A reference-based protein degradation assay without global translation inhibitors. Journal of Biological Chemistry. 292(52). 21457–21465. 14 indexed citations

Oh, Jang‐Hyun, et al.. (2017). Control of Hsp90 chaperone and its clients by N-terminal acetylation and the N-end rule pathway. Proceedings of the National Academy of Sciences. 114(22). 43 indexed citations

Oh, Jang‐Hyun, et al.. (2015). Ssn6 has dual roles in Candida albicans filament development through the interaction with Rpd31. FEBS Letters. 589(4). 513–520. 22 indexed citations

Piatkov, Konstantin, Jang‐Hyun Oh, Yuan Liu, & Alexander Varshavsky. (2014). Calpain-generated natural protein fragments as short-lived substrates of the N-end rule pathway. Proceedings of the National Academy of Sciences. 111(9). E817–26. 75 indexed citations

Kim, Heonki, et al.. (2013). The N-Terminal Methionine of Cellular Proteins as a Degradation Signal. Cell. 156(1-2). 158–169. 127 indexed citations

Hwang, Cheol‐Sang, Jang‐Hyun Oh, Won‐Ki Huh, Hyung‐Soon Yim, & Sa‐Ouk Kang. (2003). Ssn6, an important factor of morphological conversion and virulence in Candida albicans. Molecular Microbiology. 47(4). 1029–1043. 58 indexed citations

Hwang, Cheol‐Sang, Gi‐eun Rhie, Jang‐Hyun Oh, et al.. (2002). Copper- and zinc-containing superoxide dismutase (Cu/ZnSOD) is required for the protection of Candida albicans against oxidative stresses and the expression of its full virulence. Microbiology. 148(11). 3705–3713. 235 indexed citations

10.

Kee, Younghoon, et al.. (1999). Purification and characterization of recombinant hepatitis C virus replicase. Journal of Microbiology and Biotechnology. 9(6). 881–884. 2 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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