Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Bacterial exopolysaccharides – a perception
2007453 citationsKalpana Mody, Bhavanath Jha et al.profile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
hero ref
This map shows the geographic impact of Kalpana Mody'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 Kalpana Mody with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kalpana Mody more than expected).
This network shows the impact of papers produced by Kalpana Mody. 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 Kalpana Mody. The network helps show where Kalpana Mody may publish in the future.
Co-authorship network of co-authors of Kalpana Mody
This figure shows the co-authorship network connecting the top 25 collaborators of Kalpana Mody.
A scholar is included among the top collaborators of Kalpana Mody 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 Kalpana Mody. Kalpana Mody is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Mody, Kalpana, et al.. (2008). Preparation of semi-refined K-carrageenan: Recycling of alkali solution and recovery of alkali from spent liquor. Indian Journal of Chemical Technology. 15(1). 45–52.11 indexed citations
Mody, Kalpana, et al.. (2005). Characterization of an exopolysaccharide produced by a marine Enterobacter cloacae.. PubMed. 43(5). 467–71.49 indexed citations
Mody, Haresh M., et al.. (2002). Catalytic activity of an immobilized a-amylase on mesoporous silicas. INDIAN JOURNAL OF CHEMISTRY- SECTION A. 41(9). 1795–1803.
13.
Shanmugam, M., et al.. (2002). Screening of codiacean algae (Chlorophyta) of the Indian coasts for blood anticoagulant activity. Indian Journal of Marine Sciences. 31(1). 33–38.13 indexed citations
14.
Siddhanta, A. K., et al.. (2002). Sulphated galactans of marine red alga Laurencia spp. (Rhodomelaceae, Rhodophyta) from the west coast of India. Indian Journal of Marine Sciences. 31(4). 305–309.10 indexed citations
15.
Siddhanta, A. K., AJIT GOSWAMI, M. Shanmugam, Kalpana Mody, & B. K. Ramavat. (2002). Sterols from marine green algae of Indian waters. Zenodo (CERN European Organization for Nuclear Research).4 indexed citations
16.
Shanmugam, M., et al.. (2001). Blood anticoagulant activity of a green marine alga Codium dwarkense (Codiaceae, Chlorophyta) in relation to its growth stages. Indian Journal of Marine Sciences. 30(1). 49–52.10 indexed citations
17.
Shanmugam, M., et al.. (2001). Distribution of heparinoid-active sulphated polysaccharides in some Indian marine green algae. Indian Journal of Marine Sciences. 30(4). 222–227.25 indexed citations
18.
Siddhanta, A. K., et al.. (2001). Water soluble polysaccharides of marine algal species of Ulva (Ulvales, Chlorophyta) of Indian waters. Indian Journal of Marine Sciences. 30(3). 166–172.47 indexed citations
19.
Shanmugam, M. & Kalpana Mody. (2000). Heparinoid-active sulphated polysaccharides from marine algae as potential blood anticoagulant agents.. Current Science. 79(12). 1672–1683.183 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.