Debayan Dey

553 total citations
24 papers, 308 citations indexed

About

Debayan Dey is a scholar working on Molecular Biology, Molecular Medicine and Genetics. According to data from OpenAlex, Debayan Dey has authored 24 papers receiving a total of 308 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 7 papers in Molecular Medicine and 4 papers in Genetics. Recurrent topics in Debayan Dey's work include RNA and protein synthesis mechanisms (9 papers), RNA modifications and cancer (8 papers) and Antibiotic Resistance in Bacteria (7 papers). Debayan Dey is often cited by papers focused on RNA and protein synthesis mechanisms (9 papers), RNA modifications and cancer (8 papers) and Antibiotic Resistance in Bacteria (7 papers). Debayan Dey collaborates with scholars based in United States and India. Debayan Dey's co-authors include Graeme L. Conn, Suryanarayanarao Ramakumar, Valakunja Nagaraja, U.A. Ramagopal, Karuna Dixit, Siddhartha P. Sarma, Soumitra Ghosh, Tuhin Bhowmick, William M. Wuest and C.M. Dunham and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Debayan Dey

20 papers receiving 303 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Debayan Dey United States 9 181 72 69 52 50 24 308
Tiep Khac Nguyen Vietnam 6 196 1.1× 144 2.0× 104 1.5× 61 1.2× 26 0.5× 15 375
Jules Philippe France 7 129 0.7× 54 0.8× 80 1.2× 139 2.7× 88 1.8× 8 295
Mimi R. Precit United States 8 156 0.9× 86 1.2× 31 0.4× 61 1.2× 50 1.0× 13 321
Markus Furter Switzerland 8 286 1.6× 105 1.5× 88 1.3× 71 1.4× 22 0.4× 8 510
Coloma Costas Spain 11 165 0.9× 52 0.7× 154 2.2× 81 1.6× 70 1.4× 12 367
Christopher Connor United Kingdom 8 107 0.6× 47 0.7× 191 2.8× 54 1.0× 40 0.8× 15 384
Karleigh A. Hamblin United Kingdom 11 181 1.0× 58 0.8× 33 0.5× 24 0.5× 59 1.2× 15 376
Alaina R. Martinez United States 7 261 1.4× 113 1.6× 49 0.7× 99 1.9× 135 2.7× 8 528
Katarzyna Mickiewicz United Kingdom 7 170 0.9× 34 0.5× 67 1.0× 107 2.1× 35 0.7× 12 353
Allison R. Eberly United States 9 191 1.1× 30 0.4× 79 1.1× 72 1.4× 113 2.3× 24 373

Countries citing papers authored by Debayan Dey

Since Specialization
Citations

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

Fields of papers citing papers by Debayan Dey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Debayan Dey

This figure shows the co-authorship network connecting the top 25 collaborators of Debayan Dey. A scholar is included among the top collaborators of Debayan Dey 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 Debayan Dey. Debayan Dey 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
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Dey, Debayan, et al.. (2025). Basis for selective drug evasion of an aminoglycoside-resistance ribosomal RNA modification. Nature Communications. 16(1). 7992–7992.
4.
Dey, Debayan, et al.. (2024). Cumulative phylogenetic, sequence and structural analysis of Insulin superfamily proteins provide unique structure‐function insights. Molecular Informatics. 43(9). e202300160–e202300160. 1 indexed citations
5.
Dey, Debayan, et al.. (2024). Structural and functional diversity of Resistance-Nodulation-Division (RND) efflux pump transporters with implications for antimicrobial resistance. Microbiology and Molecular Biology Reviews. 88(3). e0008923–e0008923. 13 indexed citations
6.
Dey, Debayan, et al.. (2023). Ribosome-targeting antibiotics and resistance via ribosomal RNA methylation. RSC Medicinal Chemistry. 14(4). 624–643. 21 indexed citations
7.
Mahoney, Andrew R., et al.. (2023). Di-berberine conjugates as chemical probes of Pseudomonas aeruginosa MexXY-OprM efflux function and inhibition. PubMed. 1(1). 12–12. 8 indexed citations
8.
Srinivas, Pooja, Meisam Nosrati, Natalia Zelinskaya, et al.. (2023). 30S subunit recognition and G1405 modification by the aminoglycoside-resistance 16S ribosomal RNA methyltransferase RmtC. Proceedings of the National Academy of Sciences. 120(25). e2304128120–e2304128120. 8 indexed citations
9.
Dey, Debayan, Natalia Zelinskaya, Pooja Srinivas, et al.. (2022). 50S subunit recognition and modification by the Mycobacterium tuberculosis ribosomal RNA methyltransferase TlyA. Proceedings of the National Academy of Sciences. 119(14). e2120352119–e2120352119. 17 indexed citations
10.
Schwartz, Samantha L., et al.. (2022). Role of helical structure and dynamics in oligoadenylate synthetase 1 (OAS1) mismatch tolerance and activation by short dsRNAs. Proceedings of the National Academy of Sciences. 119(3). 4 indexed citations
11.
Dey, Debayan, et al.. (2022). Tied up in knots: Untangling substrate recognition by the SPOUT methyltransferases. Journal of Biological Chemistry. 298(10). 102393–102393. 12 indexed citations
12.
Dey, Debayan, Suryanarayanarao Ramakumar, & Graeme L. Conn. (2021). Targeted Redesign of Suramin Analogs for Novel Antimicrobial Lead Development. Journal of Chemical Information and Modeling. 61(9). 4442–4454. 11 indexed citations
13.
Dey, Debayan, et al.. (2020). Overproduction of the AlgT Sigma Factor Is Lethal to Mucoid Pseudomonas aeruginosa. Journal of Bacteriology. 202(20). 7 indexed citations
14.
Dey, Debayan, et al.. (2020). Antibiotic Substrate Selectivity of Pseudomonas aeruginosa MexY and MexB Efflux Systems Is Determined by a Goldilocks Affinity. Antimicrobial Agents and Chemotherapy. 64(8). 20 indexed citations
15.
Nosrati, Meisam, Debayan Dey, Natalia Zelinskaya, et al.. (2019). Functionally critical residues in the aminoglycoside resistance-associated methyltransferase RmtC play distinct roles in 30S substrate recognition. Journal of Biological Chemistry. 294(46). 17642–17653. 33 indexed citations
16.
Kuiper, Emily G., et al.. (2019). Substrate recognition by the Pseudomonas aeruginosa EF-Tu–modifying methyltransferase EftM. Journal of Biological Chemistry. 294(52). 20109–20121. 4 indexed citations
17.
Dey, Debayan, et al.. (2017). Conformational heterogeneity in tails of DNA-binding proteins is augmented by proline containing repeats. Molecular BioSystems. 13(12). 2531–2544. 2 indexed citations
18.
Dey, Debayan, Valakunja Nagaraja, & Suryanarayanarao Ramakumar. (2016). Structural and evolutionary analyses reveal determinants of DNA binding specificities of nucleoid-associated proteins HU and IHF. Molecular Phylogenetics and Evolution. 107. 356–366. 36 indexed citations
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Bhowmick, Tuhin, Soumitra Ghosh, Karuna Dixit, et al.. (2014). Targeting Mycobacterium tuberculosis nucleoid-associated protein HU with structure-based inhibitors. Nature Communications. 5(1). 4124–4124. 93 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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