Swastika Maity

435 total citations
11 papers, 223 citations indexed

About

Swastika Maity is a scholar working on Molecular Biology, Computational Theory and Mathematics and Infectious Diseases. According to data from OpenAlex, Swastika Maity has authored 11 papers receiving a total of 223 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Computational Theory and Mathematics and 3 papers in Infectious Diseases. Recurrent topics in Swastika Maity's work include Computational Drug Discovery Methods (4 papers), SARS-CoV-2 and COVID-19 Research (3 papers) and Diverse Scientific Research Studies (2 papers). Swastika Maity is often cited by papers focused on Computational Drug Discovery Methods (4 papers), SARS-CoV-2 and COVID-19 Research (3 papers) and Diverse Scientific Research Studies (2 papers). Swastika Maity collaborates with scholars based in India, United States and Australia. Swastika Maity's co-authors include Yogendra Nayak, K. Sreedhara Ranganath Pai, Chetan Hasmukh Mehta, Usha Y. Nayak, Akhil Suresh, Jayesh Mudgal, Madhavan Nampoothiri, Manas Kinra, Devinder Arora and Sairaj Satarker and has published in prestigious journals such as Scientific Reports, European Journal of Pharmacology and Archives of Medical Research.

In The Last Decade

Swastika Maity

11 papers receiving 220 citations

Peers

Swastika Maity

MB

CTM

PRM

ID

OC

Abdul Rashid Issahaku South Africa

Tamina Park South Korea

Marcin Delijewski Poland

Sahar Qazi India

F A Dain Md Opo Saudi Arabia

Kunal Bhattacharya India

Pritee Chunarkar Patil India

Sumit Birangal India

Ghanshyam Parmar India

Qin Qiu China

Abdul Rashid Issahaku South Africa

Swastika Maity

150 ×1.7

MB

112 ×1.6

CTM

19 ×0.5

PRM

19 ×0.5

ID

61 ×1.6

OC

Citations per year, relative to Swastika Maity Swastika Maity (= 1×) peers Abdul Rashid Issahaku

Countries citing papers authored by Swastika Maity

Since Specialization

Citations

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

Fields of papers citing papers by Swastika Maity

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Swastika Maity

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

All Works

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11 of 11 papers shown

1.

Maity, Swastika, et al.. (2025). Focal adhesion kinase (FAK): emerging target for drug-resistant malignant tumors. Molecular Biology Reports. 52(1). 248–248. 4 indexed citations

2.

Maity, Swastika, Chetan Hasmukh Mehta, Usha Y. Nayak, et al.. (2023). Computational drug repurposing of Akt-1 allosteric inhibitors for non-small cell lung cancer. Scientific Reports. 13(1). 7947–7947. 15 indexed citations

3.

Cheruku, Sri Pragnya, Swastika Maity, Krishnadas Nandakumar, et al.. (2023). Enhancing temozolomide antiglioma response by inhibiting O6-methylguanine-DNA methyltransferase with selected phytochemicals: in silico and in vitro approach. 3 Biotech. 13(12). 385–385. 1 indexed citations

4.

Maity, Swastika, et al.. (2023). Thalidomide interaction with inflammation in idiopathic pulmonary fibrosis. Inflammopharmacology. 31(3). 1167–1182. 7 indexed citations

5.

Maity, Swastika, et al.. (2022). Development of nanostructured lipid carriers loaded caffeic acid topical cream for prevention of inflammation in Wistar rat model. Journal of Applied Pharmaceutical Science. 5 indexed citations

6.

Maity, Swastika, et al.. (2021). SARS-CoV-2 entry inhibitors by dual targeting TMPRSS2 and ACE2: An in silico drug repurposing study. European Journal of Pharmacology. 896. 173922–173922. 33 indexed citations

7.

Satarker, Sairaj, Swastika Maity, Jayesh Mudgal, & Madhavan Nampoothiri. (2021). In silico screening of neurokinin receptor antagonists as a therapeutic strategy for neuroinflammation in Alzheimer’s disease. Molecular Diversity. 26(1). 443–466. 19 indexed citations

8.

Maity, Swastika, Manas Kinra, Madhavan Nampoothiri, et al.. (2021). Caffeic acid, a dietary polyphenol, as a promising candidate for combination therapy. Chemical Papers. 76(3). 1271–1283. 39 indexed citations

9.

Maity, Swastika, et al.. (2020). Targeting SARS-CoV-2 Main Protease: A Computational Drug Repurposing Study. Archives of Medical Research. 52(1). 38–47. 47 indexed citations

10.

Maity, Swastika, K. Sreedhara Ranganath Pai, & Yogendra Nayak. (2020). Advances in targeting EGFR allosteric site as anti-NSCLC therapy to overcome the drug resistance. Pharmacological Reports. 72(4). 799–813. 49 indexed citations

11.

Maity, Swastika, et al.. (2020). In Silico Drug Repurposing of Penicillins to Target Main Protease M^proof SARS-CoV-2. Pharmaceutical Sciences. 26(Covid-19). S52–S62. 4 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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