R Kang

3.2k total citations · 1 hit paper
8 papers, 2.6k citations indexed

About

R Kang is a scholar working on Epidemiology, Molecular Biology and Cell Biology. According to data from OpenAlex, R Kang has authored 8 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Epidemiology, 4 papers in Molecular Biology and 3 papers in Cell Biology. Recurrent topics in R Kang's work include Autophagy in Disease and Therapy (5 papers), Endoplasmic Reticulum Stress and Disease (2 papers) and Advanced Glycation End Products research (2 papers). R Kang is often cited by papers focused on Autophagy in Disease and Therapy (5 papers), Endoplasmic Reticulum Stress and Disease (2 papers) and Advanced Glycation End Products research (2 papers). R Kang collaborates with scholars based in United States, China and South Korea. R Kang's co-authors include Daolin Tang, Michael T. Lotze, Herbert J. Zeh, Yan Yu, Lei Yang, Li Cao, Ming Zhao, Philip Vernon, Shan Zhu and Yan Zeng and has published in prestigious journals such as Oncogene, Cell Death and Differentiation and Advanced Science.

In The Last Decade

R Kang

6 papers receiving 2.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The Beclin 1 network regulates autophagy and apoptosis

2011 2.0k citations R Kang, Herbert J. Zeh et al. Cell Death and Differentiation profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
R Kang United States	5	1.6k	1.3k	368	325	277	8	2.6k
Mojgan Djavaheri‐Mergny France	28	1.4k 0.9×	1.8k 1.4×	542 1.5×	396 1.2×	345 1.2×	59	3.3k
María I. Vaccaro Argentina	27	1.2k 0.8×	950 0.7×	273 0.7×	454 1.4×	283 1.0×	68	2.3k
Ezgi Tasdemir France	16	2.1k 1.4×	1.9k 1.5×	426 1.2×	538 1.7×	250 0.9×	16	3.4k
Amina Tassa France	9	2.5k 1.6×	1.8k 1.4×	243 0.7×	770 2.4×	249 0.9×	9	3.6k
Dunecan Massey United Kingdom	12	1.4k 0.9×	901 0.7×	145 0.4×	341 1.0×	300 1.1×	30	2.2k
Shun Kageyama Japan	18	1.5k 0.9×	1.7k 1.3×	211 0.6×	520 1.6×	618 2.2×	30	3.0k
Daniel Meley France	9	1.4k 0.9×	1.0k 0.8×	171 0.5×	346 1.1×	164 0.6×	12	2.0k
Kenneth Bowitz Larsen Norway	16	1.9k 1.2×	1.6k 1.3×	160 0.4×	740 2.3×	175 0.6×	22	2.9k
Neil Otto United States	8	2.7k 1.8×	2.1k 1.6×	319 0.9×	759 2.3×	259 0.9×	13	4.0k
Akito Takamura Japan	10	2.8k 1.8×	1.8k 1.4×	360 1.0×	821 2.5×	237 0.9×	13	3.6k

Countries citing papers authored by R Kang

Since Specialization

Citations

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

Fields of papers citing papers by R Kang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of R Kang

This figure shows the co-authorship network connecting the top 25 collaborators of R Kang. A scholar is included among the top collaborators of R Kang 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 R Kang. R Kang 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:

8 of 8 papers shown

1.

Kang, R, Young Jin Choi, Won-Jun Jang, et al.. (2025). Bioengineered Skin Grafts from Patient‐Derived Decellularized Extracellular Matrix and Autologous Cells for Personalized Regenerative. Advanced Science. 12(44). e11889–e11889.

2.

Ma, Min, et al.. (2024). Role of non-coding RNA in lineage plasticity of prostate cancer. Cancer Gene Therapy. 32(1). 1–10. 1 indexed citations

3.

Lee, Ye-Ji, JiHyeon Song, Minseok Kim, et al.. (2024). Pseudo‐3D Topological Alignments Regulate Mechanotransduction and Maturation of Smooth Muscle Cells. Advanced Healthcare Materials. 14(4). e2402492–e2402492.

4.

Hou, Wen‐Chi, Yan Zeng, R Chen, et al.. (2013). Strange attractors: DAMPs and autophagy link tumor cell death and immunity. Cell Death and Disease. 4(12). e966–e966. 149 indexed citations

5.

Yu, Yan, Lei Yang, Ming Zhao, et al.. (2012). Targeting microRNA-30a-mediated autophagy enhances imatinib activity against human chronic myeloid leukemia cells. Leukemia. 26(8). 1752–1760. 172 indexed citations

6.

Kang, R, Herbert J. Zeh, Michael T. Lotze, & Daolin Tang. (2011). The Beclin 1 network regulates autophagy and apoptosis. Cell Death and Differentiation. 18(4). 571–580. 1987 indexed citations breakdown →

7.

Tang, Daolin, Michael T. Lotze, R Kang, & Herbert J. Zeh. (2010). Apoptosis promotes early tumorigenesis. Oncogene. 30(16). 1851–1854. 47 indexed citations

8.

Yang, Minghua, R Kang, Zhenyu Wang, et al.. (2010). HMGB1-induced autophagy promotes chemotherapy resistance in leukemia cells. Leukemia. 25(1). 23–31. 215 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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