K. Gunasekaran

1.3k total citations
95 papers, 976 citations indexed

About

K. Gunasekaran is a scholar working on Molecular Biology, Organic Chemistry and Computational Theory and Mathematics. According to data from OpenAlex, K. Gunasekaran has authored 95 papers receiving a total of 976 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Molecular Biology, 20 papers in Organic Chemistry and 13 papers in Computational Theory and Mathematics. Recurrent topics in K. Gunasekaran's work include Computational Drug Discovery Methods (13 papers), Metal complexes synthesis and properties (11 papers) and Crystal structures of chemical compounds (10 papers). K. Gunasekaran is often cited by papers focused on Computational Drug Discovery Methods (13 papers), Metal complexes synthesis and properties (11 papers) and Crystal structures of chemical compounds (10 papers). K. Gunasekaran collaborates with scholars based in India, United States and Russia. K. Gunasekaran's co-authors include Anantha Krishnan Dhanabalan, N Sivagnaname, Saleem Iqbal, N. Nandhagopal, S. Aishwarya, Devadasan Velmurugan, Aziz Kalilur Rahiman, Peter Setlow, Mark J. Jedrzejas and D. Velmurugan and has published in prestigious journals such as Nature, Journal of Biological Chemistry and SHILAP Revista de lepidopterología.

In The Last Decade

K. Gunasekaran

91 papers receiving 948 citations

Peers

K. Gunasekaran
Maryam Iman Iran
Nidhi Singh India
Tulika Bhardwaj India
Madhu Chopra India
Chin Fei Chee Malaysia
R. Krishna India
Ajamaluddin Malik Saudi Arabia
Bernhard Ellinger Germany
Ghulam Mustafa Germany
Isabella Romeo Italy
Maryam Iman Iran
K. Gunasekaran
Citations per year, relative to K. Gunasekaran K. Gunasekaran (= 1×) peers Maryam Iman

Countries citing papers authored by K. Gunasekaran

Since Specialization
Citations

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

Fields of papers citing papers by K. Gunasekaran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of K. Gunasekaran

This figure shows the co-authorship network connecting the top 25 collaborators of K. Gunasekaran. A scholar is included among the top collaborators of K. Gunasekaran 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 K. Gunasekaran. K. Gunasekaran 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.
Velayutham, Manikandan, et al.. (2024). DbGTi: Thermostable trypsin inhibitor from Dioscorea bulbifera L. ground tubers: assessment of antioxidant and antibacterial properties and cytotoxicity evaluation using zebrafish model. International Journal of Biological Macromolecules. 263(Pt 2). 130244–130244. 7 indexed citations
2.
Mannan, Mohammad Abdul, et al.. (2024). An analysis of the environmental effects of three types of concrete: Ready-mixed, reactive powder, and geopolymer. Ain Shams Engineering Journal. 15(9). 102926–102926. 7 indexed citations
3.
Gunasekaran, K., et al.. (2023). Power Quality Optimization in Microgrids Using Genetic Algorithm and Reinforcement Learning. 6(1). 1–5. 1 indexed citations
4.
Altemimi, Ammar B., et al.. (2022). Leucine-Rich, Potent Anti-Bacterial Protein against Vibrio cholerae, Staphylococcus aureus from Solanum trilobatum Leaves. Molecules. 27(4). 1167–1167. 3 indexed citations
5.
Dhanabalan, Anantha Krishnan, et al.. (2022). Structure‐based pharmacophore modeling, virtual screening approaches to identifying the potent hepatitis C viral protease and polymerase novel inhibitors. Journal of Cellular Biochemistry. 123(8). 1366–1380. 2 indexed citations
6.
Dhanabalan, Anantha Krishnan, et al.. (2022). Evaluation of action of steroid molecules on SARS-CoV-2 by inhibiting NSP-15, an endoribonuclease. Molecular Diversity. 27(6). 2715–2728. 2 indexed citations
7.
Dhanabalan, Anantha Krishnan, et al.. (2021). Piperazine-substituted derivatives of favipiravir for Nipah virus inhibition: What do in silico studies unravel?. SN Applied Sciences. 3(1). 110–110. 23 indexed citations
8.
9.
Dhanabalan, Anantha Krishnan, et al.. (2020). Screening of potential drug for Alzheimer’s disease: a computational study with GSK-3 β inhibition through virtual screening, docking, and molecular dynamics simulation. Journal of Biomolecular Structure and Dynamics. 39(18). 7065–7079. 17 indexed citations
10.
Nandhagopal, N., et al.. (2020). Isolation and characterization of an iridoid, Arbortristoside-C from Nyctanthes arbor-tristis Linn., a potential drug candidate for diabetes targeting α-glucosidase. Journal of Biomolecular Structure and Dynamics. 40(1). 337–347. 11 indexed citations
11.
Gunasekaran, K., et al.. (2020). Structure of intact chitinase with hevein domain from the plant Simarouba glauca, known for its traditional anti-inflammatory efficacy. International Journal of Biological Macromolecules. 161. 1381–1392. 13 indexed citations
12.
Selvakumar, R., Anantha Krishnan Dhanabalan, C. V. Ramakrishnan, Devadasan Velmurugan, & K. Gunasekaran. (2019). Identification of novel NAD(P)H dehydrogenase [quinone] 1 antagonist using computational approaches. Journal of Biomolecular Structure and Dynamics. 38(3). 682–696. 3 indexed citations
13.
Iqbal, Saleem, Anantha Krishnan Dhanabalan, & K. Gunasekaran. (2017). Identification of potential PKC inhibitors through pharmacophore designing, 3D-QSAR and molecular dynamics simulations targeting Alzheimer’s disease. Journal of Biomolecular Structure and Dynamics. 36(15). 4029–4044. 20 indexed citations
14.
Sankar, T. S., et al.. (2015). Crystal structure of 2,3-Bis (5-bromo-4-fluoro-2-nitrophenyl) oxirane. MyPrints@UOM (Mysore University Library). 1(1). 2 indexed citations
15.
Sankar, T. S., S. Naveen, N.K. Lokanath, & K. Gunasekaran. (2015). Crystal structure of ethyl 4-(2,4-dichlorophenyl)-2-methyl-4H-benzo[4,5]thiazolo[3,2-a]pyrimidine-3-carboxylate. SHILAP Revista de lepidopterología. 71(5). o306–o307. 1 indexed citations
16.
Teyssier, Catherine, V. Delfosse, Valérie Vivat, et al.. (2015). An Unexpected Mode Of Binding Defines BMS948 as A Full Retinoic Acid Receptor β (RARβ, NR1B2) Selective Agonist. PLoS ONE. 10(5). e0123195–e0123195. 14 indexed citations
17.
Kuttalam, S., et al.. (2014). Dissipation Pattern of Lufenuron 5.4 EC Residues in Soil and Cabbage in Temperate Region. Madras Agricultural Journal. 101(June). 138–141. 2 indexed citations
18.
Gunasekaran, K., et al.. (2013). 6-Ferrocenoyl-7-phenylspiro[hexahydropyrrolo[1,2-c][1,3]thiazole-5,11′-indeno[1,2-b]quinoxaline]. Acta Crystallographica Section E Structure Reports Online. 69(9). m500–m500. 1 indexed citations
19.
Govindan, K., et al.. (2009). Evaluation of Bt cotton hybrids in comparison with non Bt cotton against first instar larvae of Spodoptera litura.. Indian journal of plant protection. 37. 68–73. 1 indexed citations
20.
Gunasekaran, K., et al.. (1995). In vitro differentiation of shoots from leaf callus cultures of Withania somnifera (L.) Dunal. The Journal of Indian Botanical Society. 74. 323–324. 12 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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