Kumaran Narayanan

754 total citations
76 papers, 571 citations indexed

About

Kumaran Narayanan is a scholar working on Molecular Biology, Plant Science and Ecology. According to data from OpenAlex, Kumaran Narayanan has authored 76 papers receiving a total of 571 indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Molecular Biology, 29 papers in Plant Science and 17 papers in Ecology. Recurrent topics in Kumaran Narayanan's work include Insect Resistance and Genetics (14 papers), CRISPR and Genetic Engineering (12 papers) and Bacteriophages and microbial interactions (12 papers). Kumaran Narayanan is often cited by papers focused on Insect Resistance and Genetics (14 papers), CRISPR and Genetic Engineering (12 papers) and Bacteriophages and microbial interactions (12 papers). Kumaran Narayanan collaborates with scholars based in Malaysia, United States and India. Kumaran Narayanan's co-authors include Choon Weng Lee, Edmund Ui‐Hang Sim, R. Williamson, S. Jayaraj, Nikolai V. Ravin, Chui Wei Bong, Ching Ching Ng, Peter E. Warburton, Yaw Shin Ooi and R. Govindarajan and has published in prestigious journals such as Nucleic Acids Research, Water Research and Analytical Biochemistry.

In The Last Decade

Kumaran Narayanan

66 papers receiving 548 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kumaran Narayanan Malaysia 12 335 147 110 98 86 76 571
Nicola E. Wittekindt Germany 10 415 1.2× 144 1.0× 157 1.4× 76 0.8× 90 1.0× 13 761
Nicole Kloft Germany 12 496 1.5× 57 0.4× 42 0.4× 93 0.9× 82 1.0× 12 811
Keith N. Rand Australia 16 680 2.0× 136 0.9× 97 0.9× 103 1.1× 111 1.3× 23 960
Yun Xiang Liang China 18 1.4k 4.1× 386 2.6× 110 1.0× 104 1.1× 199 2.3× 28 1.5k
Laura Baxter United Kingdom 18 277 0.8× 92 0.6× 150 1.4× 533 5.4× 68 0.8× 30 989
Mario Drungowski Germany 11 467 1.4× 81 0.6× 39 0.4× 132 1.3× 112 1.3× 16 709
Michelle Davison United States 11 791 2.4× 209 1.4× 70 0.6× 184 1.9× 308 3.6× 18 1.0k
Jèssica Gómez‐Garrido Spain 12 329 1.0× 155 1.1× 36 0.3× 196 2.0× 68 0.8× 36 686
Alexander Wagner Germany 11 711 2.1× 255 1.7× 29 0.3× 70 0.7× 141 1.6× 17 823
Isidoro Feliciello Italy 15 625 1.9× 180 1.2× 41 0.4× 417 4.3× 65 0.8× 34 853

Countries citing papers authored by Kumaran Narayanan

Since Specialization
Citations

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

Fields of papers citing papers by Kumaran Narayanan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kumaran Narayanan

This figure shows the co-authorship network connecting the top 25 collaborators of Kumaran Narayanan. A scholar is included among the top collaborators of Kumaran Narayanan 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 Kumaran Narayanan. Kumaran Narayanan 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.
Nag, Sagnik, Yong Sze Ong, Kumaran Narayanan, Vetriselvan Subramaniyan, & Rakesh Naidu. (2025). Mechanistic Insights into Nanomaterials and Advanced Drug Delivery Platforms for the Theranostic Management of Hepatic Cancer: A Comprehensive Update. BioNanoScience. 15(4). 1 indexed citations
2.
Ravi, R., et al.. (2025). Exosome-Based Sensor: A Landmark of the Precision Cancer Diagnostic Era. ACS Applied Bio Materials. 8(6). 4489–4513. 1 indexed citations
3.
Dhar, Rajib, et al.. (2025). Dendritic Cell-Derived Exosomes: Next Generation of Cancer Immunotherapy. Biomedicines. 13(10). 2497–2497.
4.
5.
Lee, Choon Weng, Chui Wei Bong, Ching Ching Ng, et al.. (2024). Environmental factors that regulate Vibrio spp. abundance and community structure in tropical waters. 7(1). 1 indexed citations
6.
Sim, Edmund Ui‐Hang, et al.. (2023). Multigenic prognosis assessment model for nasopharyngeal carcinoma via a modified meta-analysis approach. ONCOLOGIE. 0(0). 1 indexed citations
7.
Narayanan, Kumaran, et al.. (2020). Improved DNA Delivery Efficiency of Bacterial Vectors by Co-Delivery with Exogenous Lipid and Antimicrobial Reagents. Methods in molecular biology. 2211. 15–27.
8.
Lee, Choon Weng, et al.. (2020). Influence of elevated river flow on hypoxia occurrence, nutrient concentration and microbial dynamics in a tropical estuary. Environmental Monitoring and Assessment. 192(10). 660–660. 4 indexed citations
9.
Lee, Choon Weng, et al.. (2017). Rapid preparation of adherent mammalian cells for basic scanning electron microscopy (SEM) analysis. Analytical Biochemistry. 534. 46–48. 16 indexed citations
10.
Narayanan, Kumaran, et al.. (2015). Preliminary Report on the Isolation of Magnetotactic Bacteria from River Tamiraparani in South India. 12–14. 3 indexed citations
11.
Narayanan, Kumaran, et al.. (2014). Recombineering Linear BACs. Methods in molecular biology. 1227. 27–54. 3 indexed citations
12.
Verma, Meenakshi, et al.. (2013). INVESTIGATION OF ANTI BACTERIAL AND ANTI FUGAL POTENTIALS OF MACARANGA PELTATA. International Journal of Current Research and Review. 5(7). 26–32. 3 indexed citations
13.
Narayanan, Kumaran. (2008). Intact recombineering of highly repetitive DNA requires reduced induction of recombination enzymes and improved host viability. Analytical Biochemistry. 375(2). 394–396. 11 indexed citations
14.
Narayanan, Kumaran. (2005). Occurrence and cross infectivity of cytoplasmic polyhedrosis virus of tobacco caterpillar, Spodoptera litura Fab.. Journal of Entomological Research. 29(4). 319–321. 1 indexed citations
15.
Narayanan, Kumaran. (2004). Insect defence: its impact on microbial control of insect pests. Current Science. 86(6). 800–814. 57 indexed citations
16.
Narayanan, Kumaran, et al.. (2003). Nuclear Polyhedrosis Viruses from Coconut Blackheaded Caterpillar, Opisina arenosella Walker and Sorghum Spotted Stern Borer, Chilo partellus (Swinhoe). Journal of Biological Control. 17(1). 97–98. 2 indexed citations
17.
Narayanan, Kumaran & C. Gopalakrishnan. (2003). Integration of entomopathogenic nematode, Steinernema feltiae with Helicoverpa armigera nuclear polyhedrosis virus for the control of insect pests on vegetable pigeonpea. Indian Journal Of Nematology. 33(1). 33–36. 1 indexed citations
18.
Gopalakrishnan, C. & Kumaran Narayanan. (1990). Studies on the dose-mortality relationship between the entomofungal pathogen Beauveria bassiana (Bals.) Vuillemin and Heliothis armigera Hubner (Lepidoptera: Noctuidae).. Journal of Biological Control. 4(2). 112–115.
19.
Narayanan, Kumaran, et al.. (1987). Occurrence of cytoplasmic polyhedrosis virus in citrus leaf caterpillar, Papilio demoleus L. (Papilionidae: Lepidoptera).. Journal of Biological Control. 1(1). 73–74. 1 indexed citations
20.
Narayanan, Kumaran, et al.. (1987). Effect of entomogenous nemamode, Steinernema feltiae (Rhabditida: Steinernematldae) to the pre-pupa, pupa and adult of Spodoptera litura (Noctuidae: Lepidoptera). Indian Journal Of Nematology. 17(2). 273–276. 9 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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