Sang Gu Kang

3.6k total citations · 2 hit papers
67 papers, 2.6k citations indexed

About

Sang Gu Kang is a scholar working on Plant Science, Molecular Biology and Biochemistry. According to data from OpenAlex, Sang Gu Kang has authored 67 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Plant Science, 21 papers in Molecular Biology and 7 papers in Biochemistry. Recurrent topics in Sang Gu Kang's work include Phytochemicals and Antioxidant Activities (7 papers), Plant Gene Expression Analysis (6 papers) and Computational Drug Discovery Methods (5 papers). Sang Gu Kang is often cited by papers focused on Phytochemicals and Antioxidant Activities (7 papers), Plant Gene Expression Analysis (6 papers) and Computational Drug Discovery Methods (5 papers). Sang Gu Kang collaborates with scholars based in South Korea, India and Bangladesh. Sang Gu Kang's co-authors include Shiv Bharadwaj, Kyung Eun Lee, Pradeep Kumar, Madhu Kamle, Dipendra Kumar Mahato, Tapan Kumar Mohanta, Umesh Yadava, Vivek Dhar Dwivedi, Sheetal Devi and Mahendra Singh and has published in prestigious journals such as PLoS ONE, Scientific Reports and International Journal of Molecular Sciences.

In The Last Decade

Sang Gu Kang

59 papers receiving 2.5k citations

Hit Papers

Aflatoxins: A Global Concern for Food Safety, Human Healt... 2017 2026 2020 2023 2017 2019 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sang Gu Kang South Korea 23 1.1k 714 312 292 265 67 2.6k
Asad Ullah Pakistan 23 920 0.8× 996 1.4× 283 0.9× 99 0.3× 124 0.5× 74 2.8k
Amany Magdy Beshbishy Egypt 20 966 0.8× 694 1.0× 551 1.8× 216 0.7× 115 0.4× 29 2.9k
Luís Octávio Regasini Brazil 30 620 0.5× 706 1.0× 388 1.2× 209 0.7× 76 0.3× 110 2.5k
Pravindra Kumar India 30 400 0.4× 1.4k 1.9× 133 0.4× 455 1.6× 270 1.0× 145 2.7k
Arif Jamal Siddiqui Saudi Arabia 28 366 0.3× 776 1.1× 361 1.2× 168 0.6× 183 0.7× 120 2.5k
Debprasad Chattopadhyay India 32 568 0.5× 771 1.1× 340 1.1× 346 1.2× 84 0.3× 114 2.8k
Ahmed M. Sayed Egypt 26 363 0.3× 669 0.9× 306 1.0× 201 0.7× 270 1.0× 118 2.0k
Michaela Schmidtke Germany 34 366 0.3× 1.1k 1.6× 177 0.6× 379 1.3× 265 1.0× 114 3.2k
Fabrice Fekam Boyom Cameroon 29 1.3k 1.2× 720 1.0× 572 1.8× 124 0.4× 61 0.2× 199 2.8k
Pouya Hassandarvish Malaysia 29 430 0.4× 719 1.0× 307 1.0× 401 1.4× 214 0.8× 67 2.9k

Countries citing papers authored by Sang Gu Kang

Since Specialization
Citations

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

Fields of papers citing papers by Sang Gu Kang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sang Gu Kang

This figure shows the co-authorship network connecting the top 25 collaborators of Sang Gu Kang. A scholar is included among the top collaborators of Sang Gu 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 Sang Gu Kang. Sang Gu Kang 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
3.
Song, Xinjie, et al.. (2024). Caffeine: A Multifunctional Efficacious Molecule with Diverse Health Implications and Emerging Delivery Systems. International Journal of Molecular Sciences. 25(22). 12003–12003. 7 indexed citations
4.
Singh, Mahendra Pratap, et al.. (2024). Age-Related Macular Degeneration (AMD): Pathophysiology, Drug Targeting Approaches, and Recent Developments in Nanotherapeutics. Medicina. 60(10). 1647–1647. 11 indexed citations
6.
Narayanaswamy, Radhakrishnan, et al.. (2023). STITCH, Physicochemical, ADMET, and In Silico Analysis of Selected Mikania Constituents as Anti-Inflammatory Agents. Processes. 11(6). 1722–1722. 18 indexed citations
7.
Lee, Jihoon, et al.. (2023). Camera and IR Sensor-Based Sleep Apnea Diagnosis Device. IEEE Sensors Journal. 23(16). 18729–18737. 3 indexed citations
8.
Bharadwaj, Shiv, Sherif A. El‐Kafrawy, Thamir A. Alandijany, et al.. (2021). Structure-Based Identification of Natural Products as SARS-CoV-2 Mpro Antagonist from Echinacea angustifolia Using Computational Approaches. Viruses. 13(2). 305–305. 27 indexed citations
9.
Dwivedi, Vivek Dhar, Shiv Bharadwaj, Sumbul Afroz, et al.. (2020). Anti-dengue infectivity evaluation of bioflavonoid from Azadirachta indica by dengue virus serine protease inhibition. Journal of Biomolecular Structure and Dynamics. 39(4). 1417–1430. 49 indexed citations
10.
Lee, Kyung-Chang, Shiv Bharadwaj, Umesh Yadava, & Sang Gu Kang. (2020). Computational and In Vitro Investigation of (-)-Epicatechin and Proanthocyanidin B2 as Inhibitors of Human Matrix Metalloproteinase 1. Biomolecules. 10(10). 1379–1379. 22 indexed citations
11.
Bharadwaj, Shiv, Esam I. Azhar, Mohammad Amjad Kamal, et al.. (2020). SARS-CoV-2 M pro inhibitors: identification of anti-SARS-CoV-2 M pro compounds from FDA approved drugs. Journal of Biomolecular Structure and Dynamics. 40(6). 2769–2784. 41 indexed citations
12.
Kang, Sang Gu, et al.. (2020). Evaluation of Antioxidant, Tyrosinase and Collagenase Inhibitory of Grateloupia elliptica Extracts after Aureobasidium pullulans Fermentation. Journal of the Society of Cosmetic Scientists of Korea. 46(1). 1–9. 2 indexed citations
13.
Lee, Kyung Eun, Shiv Bharadwaj, Umesh Yadava, & Sang Gu Kang. (2019). Evaluation of caffeine as inhibitor against collagenase, elastase and tyrosinase using in silico and in vitro approach. Journal of Enzyme Inhibition and Medicinal Chemistry. 34(1). 927–936. 64 indexed citations
14.
Bharadwaj, Shiv, Kyung Eun Lee, Vivek Dhar Dwivedi, Umesh Yadava, & Sang Gu Kang. (2019). Computational aided mechanistic understanding of Camellia sinensis bioactive compounds against co‐chaperone p23 as potential anticancer agent. Journal of Cellular Biochemistry. 120(11). 19064–19075. 16 indexed citations
15.
Bharadwaj, Shiv, Kyung Eun Lee, Vivek Dhar Dwivedi, et al.. (2019). Discovery of Ganoderma lucidum triterpenoids as potential inhibitors against Dengue virus NS2B-NS3 protease. Scientific Reports. 9(1). 19059–19059. 89 indexed citations
16.
Rahman, Md. Mominur, Kyung Eun Lee, & Sang Gu Kang. (2015). Studies on the effects of pericarp pigmentation on grain development and yield of black rice. Indian Journal of Genetics and Plant Breeding (The). 75(4). 426–426. 15 indexed citations
17.
Kang, Sang Gu, et al.. (2010). Treatment of Heterotopic Calcification with Ulceration in Burn Scar.. 37(4). 415–420.
18.
Matin, Mohammad Nurul, et al.. (2006). Characterization of Phenotypes of Rice Lesion Resembling Disease Mutants. Genes & Genomics. 28(3). 221–228. 3 indexed citations
19.
Kang, Sang Gu, et al.. (2006). Morphological Characters of Panicle and Seed Mutants of Rice. The Korean Journal of Crop Science. 51(4). 348–355. 2 indexed citations
20.
Kang, Sang Gu, et al.. (2005). A Case of Ethylene Glycol Poisoning with Metabolic Acidosis Treated with Hemodialysis. Kidney Research and Clinical Practice. 24(6). 1039–1043. 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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