Sujata Das

2.7k total citations
109 papers, 1.7k citations indexed

About

Sujata Das is a scholar working on Ophthalmology, Radiology, Nuclear Medicine and Imaging and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Sujata Das has authored 109 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Ophthalmology, 50 papers in Radiology, Nuclear Medicine and Imaging and 30 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Sujata Das's work include Corneal surgery and disorders (43 papers), Corneal Surgery and Treatments (39 papers) and Ocular Infections and Treatments (36 papers). Sujata Das is often cited by papers focused on Corneal surgery and disorders (43 papers), Corneal Surgery and Treatments (39 papers) and Ocular Infections and Treatments (36 papers). Sujata Das collaborates with scholars based in India, United States and Germany. Sujata Das's co-authors include Berthold Seitz, Savitri Sharma, Srikant Kumar Sahu, Geeta K. Vemuganti, Achim Langenbucher, Barbara Link, Prashant Garg, Vibha Anand, Hugh R. Taylor and S P Percival and has published in prestigious journals such as PLoS ONE, Journal of Clinical Microbiology and Journal of Nutrition.

In The Last Decade

Sujata Das

99 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sujata Das India 26 846 839 576 178 164 109 1.7k
Usha Gopinathan India 27 2.2k 2.6× 694 0.8× 1.2k 2.0× 55 0.3× 179 1.1× 50 2.7k
Ana Luísa Höfling-Lima Brazil 31 1.6k 1.9× 978 1.2× 870 1.5× 17 0.1× 453 2.8× 166 2.6k
Alfonso Iovieno Canada 25 1.4k 1.6× 877 1.0× 925 1.6× 18 0.1× 162 1.0× 89 2.2k
Loretta Szczotka‐Flynn United States 29 1.4k 1.6× 1.5k 1.8× 1.5k 2.7× 1 0.0× 307 1.9× 74 2.5k
John D. Wright United States 16 75 0.1× 64 0.1× 112 0.2× 17 0.1× 165 1.0× 39 880
Pentti Ukkonen Finland 18 26 0.0× 149 0.2× 121 0.2× 57 0.3× 599 3.7× 36 1.1k
Lucy Rasmussen United States 29 65 0.1× 70 0.1× 47 0.1× 548 3.1× 2.1k 13.0× 49 2.5k
Padma Malyala United States 15 25 0.0× 134 0.2× 48 0.1× 14 0.1× 156 1.0× 19 1.2k
Toyokazu Ishikawa Japan 19 16 0.0× 56 0.1× 228 0.4× 97 0.5× 397 2.4× 37 851
Holly Hamilton United States 15 47 0.1× 28 0.0× 63 0.1× 26 0.1× 231 1.4× 32 1.2k

Countries citing papers authored by Sujata Das

Since Specialization
Citations

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

Fields of papers citing papers by Sujata Das

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sujata Das

This figure shows the co-authorship network connecting the top 25 collaborators of Sujata Das. A scholar is included among the top collaborators of Sujata Das 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 Sujata Das. Sujata Das 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.
Sharma, S. K., Samar Basak, Sujata Das, & Debasmita Pankaj Alone. (2025). Characterisation of the role played by ELMO 1, GPR 141 and the intergenic polymorphism rs918980 in Fuchs' dystrophy in the Indian population. FEBS Open Bio. 15(5). 822–835. 1 indexed citations
2.
Sahu, Srikant Kumar, et al.. (2025). Culture positivity of anterior chamber exudate in cases of fungal keratitis. International Ophthalmology. 45(1). 399–399.
3.
Roy, Aravind, et al.. (2024). Filamentary keratitis: A review. The Ocular Surface. 34. 22–29. 4 indexed citations
4.
Basak, Samar, et al.. (2023). Intergenic variants, rs1200114 and rs1200108 are genetically associated along with a decreased ATP1B1 expression in Fuchs Endothelial Corneal Dystrophy. Experimental Eye Research. 228. 109403–109403. 4 indexed citations
5.
Barik, Manas Ranjan, et al.. (2023). Case Series: Mixed Infectious Keratitis by Pythium insidiosum and Fungal Species. Optometry and Vision Science. 100(12). 887–894. 1 indexed citations
6.
Das, Rajesh Kumar, et al.. (2022). Fuchs Endothelial Corneal Dystrophy associated risk variant, rs3768617 in LAMC1 shows allele specific binding of GFI1B. Gene. 817. 146179–146179. 4 indexed citations
7.
Barik, Manas Ranjan, et al.. (2021). Microsporidia-induced stromal keratitis: a new cause of presumed immune stromal (interstitial) keratitis. British Journal of Ophthalmology. 107(5). 607–613. 4 indexed citations
8.
Sahu, Srikant Kumar, et al.. (2021). Past, present, and prospects in microsporidial keratoconjunctivitis- A review. The Ocular Surface. 28. 364–377. 3 indexed citations
9.
Chaurasia, Sunita, et al.. (2021). Early postoperative infection following lamellar keratoplasty: a review. British Journal of Ophthalmology. 106(6). 741–754. 4 indexed citations
10.
Das, Anthony Vipin, Sunita Chaurasia, Joveeta Joseph, et al.. (2021). Clinical profile and microbiological trends of therapeutic keratoplasty at a network of tertiary care ophthalmology centers in India. International Ophthalmology. 42(5). 1391–1399. 5 indexed citations
11.
Barik, Manas Ranjan, et al.. (2021). Simple polymerase chain reaction assay to differentiate between fungal and Pythium insidiosum keratitis. Clinical and Experimental Ophthalmology. 49(6). 630–632. 9 indexed citations
12.
Sharma, Savitri, et al.. (2020). Linezolid shows high safety and efficacy in the treatment of Pythium insidiosum keratitis in a rabbit model. Experimental Eye Research. 202. 108345–108345. 21 indexed citations
13.
Bagga, Bhupesh, et al.. (2020). Successful Strategic Management of Pythium insidiosum Keratitis with Antibiotics. Ophthalmology. 128(1). 169–172. 14 indexed citations
14.
Das, Sujata, et al.. (2018). rs4246215 is targeted by hsa-miR1236 to regulate FEN1 expression but is not associated with Fuchs’ endothelial corneal dystrophy. PLoS ONE. 13(9). e0204278–e0204278. 5 indexed citations
15.
Das, Sujata, et al.. (2018). Types of organisms and in-vitro susceptibility of bacterial isolates from patients with microbial keratitis: A trend analysis of 8 years. Indian Journal of Ophthalmology. 67(1). 49–49. 31 indexed citations
16.
Sharma, Savitri, et al.. (2017). In vitro synergy of natamycin and voriconazole against clinical isolates of Fusarium, Candida, Aspergillus and Curvularia spp. British Journal of Ophthalmology. 102(1). 142–145. 12 indexed citations
17.
Sharma, Savitri, et al.. (2010). Is inclusion of Sabouraud dextrose agar essential for the laboratory diagnosis of fungal keratitis?. Indian Journal of Ophthalmology. 58(4). 281–281. 25 indexed citations
18.
Roy, Aravind, et al.. (2010). Penetrating Sclerokeratoplasty in Massive Recurrent Invasive Squamous Cell Carcinoma. Ophthalmic Plastic and Reconstructive Surgery. 27(2). e39–e40. 3 indexed citations
19.
Das, Sujata, et al.. (2008). Role of Confocal Microscopy in Deep Fungal Keratitis. Cornea. 28(1). 11–13. 33 indexed citations
20.
Das, Sujata, Barbara Link, & Berthold Seitz. (2005). Salzmann's Nodular Degeneration of the Cornea. Cornea. 24(7). 772–777. 57 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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