D. Majumdar

1.3k total citations · 1 hit paper
9 papers, 1.0k citations indexed

About

D. Majumdar is a scholar working on Parasitology, Epidemiology and Virology. According to data from OpenAlex, D. Majumdar has authored 9 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Parasitology, 5 papers in Epidemiology and 4 papers in Virology. Recurrent topics in D. Majumdar's work include Toxoplasma gondii Research Studies (8 papers), Parasitic Infections and Diagnostics (6 papers) and Herpesvirus Infections and Treatments (5 papers). D. Majumdar is often cited by papers focused on Toxoplasma gondii Research Studies (8 papers), Parasitic Infections and Diagnostics (6 papers) and Herpesvirus Infections and Treatments (5 papers). D. Majumdar collaborates with scholars based in United States, United Kingdom and France. D. Majumdar's co-authors include Chunlei Su, J. P. Dubey, Xing‐Quan Zhu, Hilda Fátima Jesus Pena, E. Keats Shwab, Solange María Gennari, N. Sundar, O. C. H. Kwok, Gopal V. Velmurugan and Marie‐Laure Dardé and has published in prestigious journals such as Proceedings of the National Academy of Sciences, International Journal for Parasitology and Veterinary Parasitology.

In The Last Decade

D. Majumdar

9 papers receiving 1000 citations

Hit Papers

Geographical patterns of Toxoplasma gondii genetic divers... 2013 2026 2017 2021 2013 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. Majumdar United States 9 953 666 271 80 61 9 1.0k
Shiv K. Verma United States 22 1.2k 1.2× 574 0.9× 367 1.4× 94 1.2× 47 0.8× 66 1.2k
Laís Pardini Argentina 17 548 0.6× 310 0.5× 148 0.5× 46 0.6× 18 0.3× 35 594
D. Bacigalupe Argentina 17 667 0.7× 290 0.4× 179 0.7× 36 0.5× 11 0.2× 20 726
Juliana Martins Aguiar Brazil 10 521 0.5× 268 0.4× 119 0.4× 36 0.5× 20 0.3× 14 559
R. H. WILLIAMS United Kingdom 8 424 0.4× 233 0.3× 94 0.3× 40 0.5× 13 0.2× 10 465
Anderson Barbosa de Moura Brazil 14 530 0.6× 223 0.3× 86 0.3× 76 0.9× 16 0.3× 77 612
David Arranz-Solís United States 16 450 0.5× 215 0.3× 47 0.2× 30 0.4× 51 0.8× 29 529
K.M. Thomson United Kingdom 12 670 0.7× 343 0.5× 110 0.4× 24 0.3× 34 0.6× 12 814
M.-F. Cesbron-Delauw France 13 683 0.7× 480 0.7× 153 0.6× 39 0.5× 103 1.7× 20 716
Xuenan Xuan Japan 13 366 0.4× 181 0.3× 55 0.2× 47 0.6× 66 1.1× 39 532

Countries citing papers authored by D. Majumdar

Since Specialization
Citations

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

Fields of papers citing papers by D. Majumdar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. Majumdar

This figure shows the co-authorship network connecting the top 25 collaborators of D. Majumdar. A scholar is included among the top collaborators of D. Majumdar 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 D. Majumdar. D. Majumdar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
1.
Shwab, E. Keats, Xing‐Quan Zhu, D. Majumdar, et al.. (2013). Geographical patterns of Toxoplasma gondii genetic diversity revealed by multilocus PCR-RFLP genotyping. Parasitology. 141(4). 453–461. 331 indexed citations breakdown →
2.
Su, Chunlei, Asis Khan, Peng Zhou, et al.. (2012). Globally diverse Toxoplasma gondii isolates comprise six major clades originating from a small number of distinct ancestral lineages. Proceedings of the National Academy of Sciences. 109(15). 5844–5849. 275 indexed citations
3.
Dubey, J. P., C. Rajendran, L. R. Ferreira, et al.. (2010). A New Atypical Highly Mouse Virulent Toxoplasma gondii Genotype Isolated from a Wild Black Bear in Alaska. Journal of Parasitology. 96(4). 713–716. 34 indexed citations
4.
5.
Dubey, J. P., Patricia A. Fair, N. Sundar, et al.. (2008). Isolation of Toxoplasma gondii From Bottlenose Dolphins (Tursiops truncatus). Journal of Parasitology. 94(4). 821–823. 40 indexed citations
6.
Dubey, J. P., Gopal V. Velmurugan, Victoria Ulrich, et al.. (2007). Transplacental toxoplasmosis in naturally-infected white-tailed deer: Isolation and genetic characterisation of Toxoplasma gondii from foetuses of different gestational ages. International Journal for Parasitology. 38(8-9). 1057–1063. 55 indexed citations
7.
Sundar, N., Rebecca A. Cole, Nancy J. Thomas, et al.. (2007). Genetic diversity among sea otter isolates of Toxoplasma gondii. Veterinary Parasitology. 151(2-4). 125–132. 47 indexed citations
8.
Dubey, J. P., N. Sundar, Dolores E. Hill, et al.. (2007). High prevalence and abundant atypical genotypes of Toxoplasma gondii isolated from lambs destined for human consumption in the USA. International Journal for Parasitology. 38(8-9). 999–1006. 161 indexed citations
9.
Das, Paramananda, et al.. (2005). Isolation and characterization of polymorphic microsatellites in Labeo rohita and their cross‐species amplification in related species. Molecular Ecology Notes. 5(2). 231–233. 40 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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