Dweipayan Goswami

3.1k total citations · 1 hit paper
78 papers, 2.1k citations indexed

About

Dweipayan Goswami is a scholar working on Molecular Biology, Plant Science and Computational Theory and Mathematics. According to data from OpenAlex, Dweipayan Goswami has authored 78 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 24 papers in Plant Science and 14 papers in Computational Theory and Mathematics. Recurrent topics in Dweipayan Goswami's work include Plant-Microbe Interactions and Immunity (16 papers), Computational Drug Discovery Methods (14 papers) and Bacterial biofilms and quorum sensing (9 papers). Dweipayan Goswami is often cited by papers focused on Plant-Microbe Interactions and Immunity (16 papers), Computational Drug Discovery Methods (14 papers) and Bacterial biofilms and quorum sensing (9 papers). Dweipayan Goswami collaborates with scholars based in India, Pakistan and Australia. Dweipayan Goswami's co-authors include Pinakin Dhandhukia, Janki N. Thakker, Meenu Saraf, Rakesh Rawal, Arpit Shukla, Paritosh Parmar, Priyashi Rao, Baldev Patel, Jignesh Prajapati and R. B. Patel and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Hazardous Materials.

In The Last Decade

Dweipayan Goswami

74 papers receiving 2.1k citations

Hit Papers

Portraying mechanics of plant growth promoting rhizobacte... 2016 2026 2019 2022 2016 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dweipayan Goswami India 23 1.1k 649 238 165 158 78 2.1k
Meenu Saraf India 27 1.5k 1.4× 651 1.0× 164 0.7× 121 0.7× 143 0.9× 116 2.5k
Kamal Dev India 25 483 0.4× 416 0.6× 116 0.5× 86 0.5× 463 2.9× 94 1.6k
Cha Young Kim South Korea 34 2.3k 2.1× 2.0k 3.0× 81 0.3× 73 0.4× 137 0.9× 118 3.5k
Mohammed Bourhia Saudi Arabia 27 1.2k 1.1× 563 0.9× 128 0.5× 192 1.2× 1.0k 6.4× 305 2.9k
Кришнан Каннабиран India 30 500 0.4× 529 0.8× 45 0.2× 496 3.0× 214 1.4× 116 2.3k
Mousa Alreshidi Saudi Arabia 23 308 0.3× 553 0.9× 96 0.4× 78 0.5× 420 2.7× 60 1.6k
Arun Kumar India 25 1.1k 1.0× 754 1.2× 42 0.2× 87 0.5× 134 0.8× 94 2.1k
M. Murali India 28 1.1k 1.0× 344 0.5× 66 0.3× 79 0.5× 94 0.6× 80 2.2k
M. Lakshmi Narasu India 27 1.0k 0.9× 1.8k 2.7× 54 0.2× 138 0.8× 184 1.2× 114 2.9k
P. Hariprasad India 26 1.4k 1.2× 388 0.6× 51 0.2× 65 0.4× 331 2.1× 105 2.1k

Countries citing papers authored by Dweipayan Goswami

Since Specialization
Citations

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

Fields of papers citing papers by Dweipayan Goswami

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dweipayan Goswami

This figure shows the co-authorship network connecting the top 25 collaborators of Dweipayan Goswami. A scholar is included among the top collaborators of Dweipayan Goswami 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 Dweipayan Goswami. Dweipayan Goswami 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.
Mathur, Shivangi, et al.. (2025). Sennoside A from Cassia angustifolia as a mixed-type inhibitor of DPP-IV: Integrative in vitro, in silico, and kinetic characterization. Biochemical and Biophysical Research Communications. 781. 152463–152463.
3.
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Goswami, Dweipayan, et al.. (2025). MurG as a potential target of quercetin in Staphylococcus aureus supported by evidence from subtractive proteomics and molecular dynamics. Scientific Reports. 15(1). 7309–7309. 3 indexed citations
5.
Patel, Krishna Kumar, et al.. (2024). Combatting antibiotic resistance by exploring the promise of Quorum Quenching in targeting bacterial virulence. SHILAP Revista de lepidopterología. 6. 100224–100224. 14 indexed citations
6.
Patel, R. B., et al.. (2024). Penicillin-binding proteins: the master builders and breakers of bacterial cell walls and its interaction with β-lactam antibiotics. Journal of Proteins and Proteomics. 15(2). 215–232. 17 indexed citations
7.
Patel, Arun, et al.. (2024). Understanding mastitis: Microbiome, control strategies, and prevalence – A comprehensive review. Microbial Pathogenesis. 187. 106533–106533. 15 indexed citations
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Prajapati, Jignesh, et al.. (2024). Antimicrobial Resistance Surveillance in Human Pathogens in Ahmedabad: A One-Year Prospective Study. Indian Journal of Microbiology. 64(4). 1769–1786. 4 indexed citations
10.
Patel, R. B., et al.. (2023). A clash of quorum sensing vs quorum sensing inhibitors: an overview and risk of resistance. Archives of Microbiology. 205(4). 107–107. 24 indexed citations
11.
Prajapati, Jignesh, R. B. Patel, Priyashi Rao, et al.. (2022). Perceiving SARS-CoV-2 Mpro and PLpro dual inhibitors from pool of recognized antiviral compounds of endophytic microbes: an in silico simulation study. Structural Chemistry. 33(5). 1619–1643. 17 indexed citations
12.
Patel, R. B., K D Mehta, Dweipayan Goswami, & Meenu Saraf. (2021). An Anecdote on Prospective Protein Targets for Developing Novel Plant Growth Regulators. Molecular Biotechnology. 64(2). 109–129. 2 indexed citations
13.
El-hoshoudy, A.N., et al.. (2021). Berries anthocyanins as potential SARS-CoV–2 inhibitors targeting the viral attachment and replication; molecular docking simulation. Egyptian Journal of Petroleum. 30(1). 33–43. 26 indexed citations
14.
Mehta, K D, et al.. (2021). Decoding the mojo of plant-growth-promoting microbiomes. Physiological and Molecular Plant Pathology. 115. 101687–101687. 26 indexed citations
15.
Patel, Chirag, et al.. (2021). Repurposing of anticancer phytochemicals for identifying potential fusion inhibitor for SARS-CoV-2 using molecular docking and molecular dynamics (MD) simulations. Journal of Biomolecular Structure and Dynamics. 40(17). 7744–7761. 16 indexed citations
17.
Patel, Dhavalkumar, et al.. (2020). Talaromyces pinophilus strain M13: a portrayal of novel groundbreaking fungal strain for phytointensification. Environmental Science and Pollution Research. 28(7). 8758–8769. 17 indexed citations
18.
Parmar, Paritosh, Arpit Shukla, Dweipayan Goswami, et al.. (2020). Comprehensive depiction of novel heavy metal tolerant and EPS producing bioluminescent Vibrio alginolyticus PBR1 and V. rotiferianus PBL1 confined from marine organisms. Microbiological Research. 238. 126526–126526. 23 indexed citations
19.
Parmar, Paritosh, Arpit Shukla, Priyashi Rao, et al.. (2020). The rise of gingerol as anti-QS molecule: Darkest episode in the LuxR-mediated bioluminescence saga. Bioorganic Chemistry. 99. 103823–103823. 28 indexed citations
20.
Goswami, Dweipayan & Sharda Sundaram Sanjay. (2014). Determination of Heavy Metals,viz.Cadmium,Copper,Lead and Zinc in the Different Matrices of the Ganges River from Rishikesh to Allahabad through Differential Pulse Anodic Striping Voltametry. International journal of advanced research in chemical sciences. 1(5). 7–11. 6 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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