Chul Sik Kim

145 total papers · 2.0k total citations
97 papers, 1.6k citations indexed

About

Chul Sik Kim is a scholar working on Endocrinology, Diabetes and Metabolism, Molecular Biology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Chul Sik Kim has authored 97 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Endocrinology, Diabetes and Metabolism, 30 papers in Molecular Biology and 21 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Chul Sik Kim's work include Diabetes, Cardiovascular Risks, and Lipoproteins (15 papers), Cardiovascular Health and Disease Prevention (12 papers) and Diabetes Treatment and Management (11 papers). Chul Sik Kim is often cited by papers focused on Diabetes, Cardiovascular Risks, and Lipoproteins (15 papers), Cardiovascular Health and Disease Prevention (12 papers) and Diabetes Treatment and Management (11 papers). Chul Sik Kim collaborates with scholars based in South Korea, United States and Ethiopia. Chul Sik Kim's co-authors include Jun Goo Kang, Moon Gi Choi, Sung-Hee Ihm, Chul Woo Ahn, Si Hyoung Kim, Bong Soo, Dae Jung Kim, Seong Jin Lee, Hyung Joon Yoo and Soo Lim and has published in prestigious journals such as Biomaterials, The Journal of Clinical Endocrinology & Metabolism and Diabetes Care.

In The Last Decade

Chul Sik Kim

94 papers receiving 1.6k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Chul Sik Kim	659	477	289	256	230	97	1.6k
Yi‐Jen Hung	462 0.7×	464 1.0×	282 1.0×	306 1.2×	219 1.0×	114	1.9k
Fernando Gerchman	676 1.0×	347 0.7×	296 1.0×	281 1.1×	220 1.0×	83	1.9k
Weiqiong Gu	530 0.8×	467 1.0×	280 1.0×	372 1.5×	287 1.2×	63	1.6k
Marisa Passarelli	695 1.1×	465 1.0×	477 1.7×	266 1.0×	200 0.9×	104	1.8k
Cristina Bianchi	810 1.2×	373 0.8×	439 1.5×	197 0.8×	239 1.0×	95	1.7k
Óscar Pérez‐Méndez	544 0.8×	408 0.9×	426 1.5×	286 1.1×	326 1.4×	126	1.9k
Sergio Martínez‐Hervás	430 0.7×	374 0.8×	438 1.5×	285 1.1×	223 1.0×	116	1.6k
Gary Ko	559 0.8×	391 0.8×	265 0.9×	181 0.7×	262 1.1×	50	1.6k
Anna Tavridou	523 0.8×	361 0.8×	371 1.3×	226 0.9×	434 1.9×	70	2.0k
Suk Chon	799 1.2×	497 1.0×	287 1.0×	195 0.8×	126 0.5×	115	2.0k

Countries citing papers authored by Chul Sik Kim

Since Specialization

Citations

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

Fields of papers citing papers by Chul Sik Kim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chul Sik Kim. 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 Chul Sik Kim. The network helps show where Chul Sik Kim may publish in the future.

Co-authorship network of co-authors of Chul Sik Kim

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

All Works

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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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