Arijit Roy

1.1k total citations
44 papers, 695 citations indexed

About

Arijit Roy is a scholar working on Molecular Biology, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, Arijit Roy has authored 44 papers receiving a total of 695 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Molecular Biology, 17 papers in Computational Theory and Mathematics and 7 papers in Materials Chemistry. Recurrent topics in Arijit Roy's work include Computational Drug Discovery Methods (17 papers), Protein Structure and Dynamics (12 papers) and RNA and protein synthesis mechanisms (7 papers). Arijit Roy is often cited by papers focused on Computational Drug Discovery Methods (17 papers), Protein Structure and Dynamics (12 papers) and RNA and protein synthesis mechanisms (7 papers). Arijit Roy collaborates with scholars based in India, United States and Singapore. Arijit Roy's co-authors include Sowmya Ramaswamy Krishnan, Srabani Taraphder, Gopalakrishnan Bulusu, Navneet Bung, Martin J. Field, Dominique Bourgeois, Rajgopal Srinivasan, Philippe Carpentier, M. Michael Gromiha and Mitali Sengupta and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nucleic Acids Research.

In The Last Decade

Arijit Roy

43 papers receiving 684 citations

Peers

Arijit Roy

CTM

BIOPH

James E. Mills United Kingdom

Aaron T. Frank United States

Sara Núñez United States

Oranit Dror Israel

Fedor N. Novikov Russia

William W. Chen United States

Predrag Kukić United Kingdom

Vladimir Aladinskiy Russia

Jianyin Shao United States

Richard J. Taylor United Kingdom

James E. Mills United Kingdom

Arijit Roy

534 ×1.2

299 ×1.6

CTM

105 ×0.8

235 ×3.3

35 ×0.7

BIOPH

Citations per year, relative to Arijit Roy Arijit Roy (= 1×) peers James E. Mills

Countries citing papers authored by Arijit Roy

Since Specialization

Citations

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

Fields of papers citing papers by Arijit Roy

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arijit Roy

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

All Works

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20 of 20 papers shown

Krishnan, Sowmya Ramaswamy, et al.. (2025). A structure-oriented kinetics dataset of enzyme-substrate interactions. Scientific Data. 12(1). 1489–1489. 1 indexed citations

Krishnan, Sowmya Ramaswamy, et al.. (2024). Suitability of large language models for extraction of high-quality chemical reaction dataset from patent literature. Journal of Cheminformatics. 16(1). 131–131. 6 indexed citations

Srinivasan, Ashwin, Tirtharaj Dash, Sowmya Ramaswamy Krishnan, et al.. (2024). Generating Novel Leads for Drug Discovery Using LLMs with Logical Feedback. Proceedings of the AAAI Conference on Artificial Intelligence. 38(1). 21–29. 4 indexed citations

Krishnan, Sowmya Ramaswamy, Navneet Bung, Rajgopal Srinivasan, & Arijit Roy. (2024). Target-specific novel molecules with their recipe: Incorporating synthesizability in the design process. Journal of Molecular Graphics and Modelling. 129. 108734–108734. 4 indexed citations

Krishnan, Sowmya Ramaswamy, et al.. (2023). pBRICS: A Novel Fragmentation Method for Explainable Property Prediction of Drug-Like Small Molecules. Journal of Chemical Information and Modeling. 63(16). 5066–5076. 10 indexed citations

Bung, Navneet, et al.. (2022). An Interpretable Machine Learning Model for Selectivity of Small-Molecules Against Homologous Protein Family. Future Medicinal Chemistry. 14(20). 1441–1453. 3 indexed citations

Bung, Navneet, Sowmya Ramaswamy Krishnan, & Arijit Roy. (2022). An In Silico Explainable Multiparameter Optimization Approach for De Novo Drug Design against Proteins from the Central Nervous System. Journal of Chemical Information and Modeling. 62(11). 2685–2695. 17 indexed citations

Roy, Arijit, et al.. (2022). Amentoflavone and methyl hesperidin, novel lead molecules targeting epitranscriptomic modulator in acute myeloid leukemia: in silico drug screening and molecular dynamics simulation approach. Journal of Molecular Modeling. 29(1). 9–9. 13 indexed citations

Krishnan, Sowmya Ramaswamy, Navneet Bung, Siladitya Padhi, et al.. (2022). De novo design of anti-tuberculosis agents using a structure-based deep learning method. Journal of Molecular Graphics and Modelling. 118. 108361–108361. 5 indexed citations

10.

Sengupta, Mitali, et al.. (2022). Art of breaking bad news. Indian Journal of Psychiatry. 64(1). 25–37. 9 indexed citations

11.

Krishnan, Sowmya Ramaswamy, Arijit Roy, & M. Michael Gromiha. (2022). R-SIM: A Database of Binding Affinities for RNA-small Molecule Interactions. Journal of Molecular Biology. 435(14). 167914–167914. 13 indexed citations

12.

Kumar, J.S. Dileep, Navneet Bung, Arijit Roy, et al.. (2022). Sonochemical synthesis and biological evaluation of isoquinolin-1(2H)-one/isoindolin-1-one derivatives: Discovery of a positive ago-allosteric modulator (PAAM) of 5HT2CR. Bioorganic Chemistry. 129. 106202–106202. 2 indexed citations

13.

Krishnan, Sowmya Ramaswamy, Navneet Bung, Gopalakrishnan Bulusu, & Arijit Roy. (2021). Accelerating De Novo Drug Design against Novel Proteins Using Deep Learning. Journal of Chemical Information and Modeling. 61(2). 621–630. 61 indexed citations

14.

Bung, Navneet, Sowmya Ramaswamy Krishnan, Gopalakrishnan Bulusu, & Arijit Roy. (2021). De Novo Design of New Chemical Entities for SARS-CoV-2 Using Artificial Intelligence. Future Medicinal Chemistry. 13(6). 575–585. 64 indexed citations

15.

Krishnan, Sowmya Ramaswamy, et al.. (2021). De Novo Structure-Based Drug Design Using Deep Learning. Journal of Chemical Information and Modeling. 62(21). 5100–5109. 36 indexed citations

16.

Bailey, H., G.A. Bezerra, Jason R. Marcero, et al.. (2020). Human aminolevulinate synthase structure reveals a eukaryotic-specific autoinhibitory loop regulating substrate binding and product release. Nature Communications. 11(1). 2813–2813. 28 indexed citations

17.

Bung, Navneet, et al.. (2020). Network analysis of hydroxymethylbilane synthase dynamics. Journal of Molecular Graphics and Modelling. 99. 107641–107641. 3 indexed citations

18.

Krishnan, Sowmya Ramaswamy, et al.. (2019). A network-based approach reveals novel invasion and Maurer's clefts-related proteins in Plasmodium falciparum. Molecular Omics. 15(6). 431–441. 5 indexed citations

19.

Bung, Navneet, Arijit Roy, U. Deva Priyakumar, & Gopalakrishnan Bulusu. (2019). Computational modeling of the catalytic mechanism of hydroxymethylbilane synthase. Physical Chemistry Chemical Physics. 21(15). 7932–7940. 3 indexed citations

20.

Padhi, Siladitya, Meenakshi Pradhan, Navneet Bung, Arijit Roy, & Gopalakrishnan Bulusu. (2019). TPP riboswitch aptamer: Role of Mg2+ ions, ligand unbinding, and allostery. Journal of Molecular Graphics and Modelling. 88. 282–291. 11 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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