M.S. Lakshmi

1.2k total citations
71 papers, 994 citations indexed

About

M.S. Lakshmi is a scholar working on Molecular Biology, Genetics and Oncology. According to data from OpenAlex, M.S. Lakshmi has authored 71 papers receiving a total of 994 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 18 papers in Genetics and 11 papers in Oncology. Recurrent topics in M.S. Lakshmi's work include AI in cancer detection (8 papers), Gene expression and cancer classification (6 papers) and Animal Genetics and Reproduction (6 papers). M.S. Lakshmi is often cited by papers focused on AI in cancer detection (8 papers), Gene expression and cancer classification (6 papers) and Animal Genetics and Reproduction (6 papers). M.S. Lakshmi collaborates with scholars based in United Kingdom, India and United States. M.S. Lakshmi's co-authors include Gajanan V. Sherbet, G.V. Sherbet, Madasamy Parani, Ajay Parida, F. Cajone, C. S. Anuratha, R.N.G. Naguib, Hugh B. Coakham, K. Venkata Rao and Asish Kumar Parida and has published in prestigious journals such as Nature, Development and JNCI Journal of the National Cancer Institute.

In The Last Decade

M.S. Lakshmi

69 papers receiving 912 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M.S. Lakshmi United Kingdom 17 580 173 136 129 121 71 994
Louis S. Ramagli United States 14 728 1.3× 121 0.7× 203 1.5× 97 0.8× 46 0.4× 29 1.2k
G. Thomas Hayman United States 23 984 1.7× 293 1.7× 209 1.5× 87 0.7× 65 0.5× 53 1.4k
Kees W. Rodenburg Netherlands 24 641 1.1× 142 0.8× 215 1.6× 394 3.1× 83 0.7× 39 1.5k
Gerald Latter United States 18 1.2k 2.0× 188 1.1× 62 0.5× 55 0.4× 43 0.4× 29 1.5k
Heikki Lehväslaiho Finland 20 535 0.9× 150 0.9× 90 0.7× 73 0.6× 41 0.3× 34 1.5k
S. Pauliina Turunen Finland 18 338 0.6× 70 0.4× 69 0.5× 124 1.0× 71 0.6× 43 958
Peter Tolias United States 21 975 1.7× 155 0.9× 117 0.9× 65 0.5× 76 0.6× 46 1.4k
Mark B. Dworkin United States 23 1.4k 2.5× 265 1.5× 114 0.8× 158 1.2× 112 0.9× 38 1.8k
Paul Labhart United States 24 1.5k 2.5× 264 1.5× 193 1.4× 160 1.2× 45 0.4× 51 1.7k
Lidia Averboukh United States 10 883 1.5× 147 0.8× 98 0.7× 92 0.7× 36 0.3× 14 1.2k

Countries citing papers authored by M.S. Lakshmi

Since Specialization
Citations

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

Fields of papers citing papers by M.S. Lakshmi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.S. Lakshmi. 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 M.S. Lakshmi. The network helps show where M.S. Lakshmi may publish in the future.

Co-authorship network of co-authors of M.S. Lakshmi

This figure shows the co-authorship network connecting the top 25 collaborators of M.S. Lakshmi. A scholar is included among the top collaborators of M.S. Lakshmi 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 M.S. Lakshmi. M.S. Lakshmi 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.
Lakshmi, M.S., et al.. (2021). Molecular diversity assessment of rice genotypes for brown planthopper resistance using microsatellite markers. Electronic Journal of Plant Breeding. 12(2). 499–506. 5 indexed citations
2.
Şeker, Hüseyin, Michael Odetayo, Dobrila Petrov́ić, et al.. (2005). Prognostic comparison of statistical, neural and fuzzy methods of analysis of breast cancer image cytometric data. 4. 3811–3814. 1 indexed citations
3.
Şeker, Hüseyin, Michael Odetayo, Dobrila Petrov́ić, et al.. (2002). A fuzzy measurement-based assessment of breast cancer prognostic markers. 174–178. 14 indexed citations
4.
5.
Parani, Madasamy, et al.. (2000). Ribosomal DNA variation and phylogenetic relationships among Cajanus cajan (L.) Millsp. and its wild relatives.. Current Science. 78(10). 1235–1238. 13 indexed citations
6.
7.
Lakshmi, M.S., et al.. (1999). Molecular Cloning of a cDNA Sequence Encoding the H+/Ca2+ Antiporter 2 from the Japanese Morning Glory (Accession No. AB018526) (PGR99-024).. PLANT PHYSIOLOGY. 119(2). 806–806. 5 indexed citations
8.
Naguib, R.N.G., M.S. Lakshmi, V. Wadehra, et al.. (1999). DNA ploidy and cell cycle distribution of breast cancer aspirate cells measured by image cytometry and analyzed by artificial neural networks for their prognostic significance. IEEE Transactions on Information Technology in Biomedicine. 3(1). 61–69. 22 indexed citations
9.
Albertazzi, Elena, et al.. (1998). Expression of Metastasis-Associated Genes h-mts1 ( S100A4 ) and nm23 in Carcinoma of Breast Is Related to Disease Progression. DNA and Cell Biology. 17(4). 335–342. 43 indexed citations
10.
Albertazzi, Elena, F. Cajone, M.S. Lakshmi, & Gajanan V. Sherbet. (1998). Heat Shock Modulates the Expression of the Metastasis Associated Gene MTS1 and Proliferation of Murine and Human Cancer Cells. DNA and Cell Biology. 17(1). 1–7. 11 indexed citations
11.
Sherbet, Gajanan V., et al.. (1995). Epidermal Growth Factor Receptor Status Correlates with Cell Proliferation—related 18A2/mts1 Gene Expression in Human Carcinoma Cell Linesa. Annals of the New York Academy of Sciences. 768(1). 272–275. 8 indexed citations
12.
Cajone, F., S Debiasi, Christopher Parker, M.S. Lakshmi, & Gajanan V. Sherbet. (1994). Metastasis-associated mts1 gene expression is down-regulated by heat shock in variant cell lines of the B16 murine melanoma. Melanoma Research. 4(3). 143–150. 11 indexed citations
13.
Lakshmi, M.S., et al.. (1994). Metastasis-Associated mts1 Gene Expression Correlates with Increased p53 Detection in the B16 Murine Melanoma. DNA and Cell Biology. 13(4). 343–351. 37 indexed citations
14.
Usmani, B A, et al.. (1994). Induction of 18A2/mts1 Gene Expression and Its Effects on Metastasis and Cell Cycle Control. DNA and Cell Biology. 13(10). 1021–1028. 42 indexed citations
15.
Adams, A.E., et al.. (1992). Image Processing for Cell Cycle Analysis and Discrimination in Metastatic Variant Cell Lines of the B16 Murine Melanoma. Pathobiology. 60(2). 76–81. 8 indexed citations
16.
Lakshmi, M.S. & Gajanan V. Sherbet. (1990). Genetic recombination in human melanoma and astrocytoma cell lines involves oncogenes and growth factor genes. Clinical & Experimental Metastasis. 8(1). 75–87. 5 indexed citations
17.
Sherbet, G.V., M.S. Lakshmi, & F. Cajone. (1983). Isoelectric characteristics and the secondary structure of some nucleic acids. European Biophysics Journal. 10(3). 121–128. 26 indexed citations
18.
Lakshmi, M.S. & Gajanan V. Sherbet. (1964). A study of the effects of trypan blue injected into amphibian zygotes. Development Genes and Evolution. 155(4). 424–428. 1 indexed citations
19.
Sherbet, Gajanan V. & M.S. Lakshmi. (1964). Inhibition of development ofPlanorbis exustus by chloramphenicol. Development Genes and Evolution. 155(4). 429–436. 1 indexed citations
20.
Sherbet, Gajanan V. & M.S. Lakshmi. (1964). Inhibition of development ofPlanorbis exustus by cobaltous sulphate and chloramphenicol. Die Naturwissenschaften. 51(5). 119–119. 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.

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