This map shows the geographic impact of V. G. Malathi'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 V. G. Malathi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites V. G. Malathi more than expected).
This network shows the impact of papers produced by V. G. Malathi. 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 V. G. Malathi. The network helps show where V. G. Malathi may publish in the future.
Co-authorship network of co-authors of V. G. Malathi
This figure shows the co-authorship network connecting the top 25 collaborators of V. G. Malathi.
A scholar is included among the top collaborators of V. G. Malathi 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 V. G. Malathi. V. G. Malathi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Sangeetha, B., et al.. (2020). Antiviral potential of Mirabilis jalapa root extracts against groundnut bud necrosis virus. Journal of Entomology and Zoology Studies. 8(1). 955–961.
Renukadevi, P., et al.. (2016). Occurrence, biological and serological assay of Tobacco streak virus infecting cotton in Tamil Nadu.. JOURNAL OF MYCOLOGY AND PLANT PATHOLOGY. 46(2). 159–168.4 indexed citations
Suresh, L. M., V. G. Malathi, & M. B. Shivanna. (2013). Molecular detection of begomoviruses associated with a new yellow leaf crumple disease of cucumber in Maharashtra, India. Indian Phytopathology. 66(3). 294–301.1 indexed citations
7.
Biswas, Kajal Kumar, et al.. (2012). Evaluation of urdbean cultivars for identification of resistance to leaf crinkle disease by mechanical sap inoculation. Indian Phytopathology. 65(4). 416–417.8 indexed citations
Aggarwal, Rashmi, Renu Renu, P. Srinivas, & V. G. Malathi. (2010). Assessment of genetic diversity in Chaetomium globosum, a potential biocontrol agent by Amplified Fragment Length Polymorphism.. Indian Phytopathology. 63(1). 2–5.2 indexed citations
11.
Amudha, J., et al.. (2010). Cotton transgenics with Antisense AC1 gene for resistance against cotton leaf curl virus. Electronic Journal of Plant Breeding. 1(4). 360–369.8 indexed citations
Malathi, V. G., et al.. (2008). Molecular markers for differentiating the populations of Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae), vector of begomoviruses. Indian Phytopathology. 61(2). 252–258.1 indexed citations
14.
Sivalingam, Palaiyur Nanjappan, et al.. (2007). Detection of begomoviruses by PCR in weeds and crop plants in and around cotton field infected with cotton leaf curl disease.. Indian Phytopathology. 60(3). 356–361.2 indexed citations
Gogoi, Robin, et al.. (2005). Differentiation of Karnal bunt resistant and susceptible cultivars of wheat using RAPD. Indian Phytopathology. 58(2). 157–162.3 indexed citations
Radhakrishnan, Girish, V. G. Malathi, & Ashok K. Varma. (2004). Biological characterization of an isolate of Cotton leaf curl Rajasthan virus from northern India and identification of sources of resistance. Indian Phytopathology. 57(2). 174–180.6 indexed citations
19.
Baranwal, V. K., et al.. (2004). Banana streak virus from India and its detection by polymerase chain reaction.. Indian Journal of Biotechnology. 3(3). 409–413.7 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.