Anisha Gupta

1.9k total citations · 2 hit papers
36 papers, 1.3k citations indexed

About

Anisha Gupta is a scholar working on Molecular Biology, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Anisha Gupta has authored 36 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 3 papers in Computer Vision and Pattern Recognition and 3 papers in Artificial Intelligence. Recurrent topics in Anisha Gupta's work include Advanced biosensing and bioanalysis techniques (14 papers), RNA Interference and Gene Delivery (13 papers) and DNA and Nucleic Acid Chemistry (7 papers). Anisha Gupta is often cited by papers focused on Advanced biosensing and bioanalysis techniques (14 papers), RNA Interference and Gene Delivery (13 papers) and DNA and Nucleic Acid Chemistry (7 papers). Anisha Gupta collaborates with scholars based in United States, India and United Kingdom. Anisha Gupta's co-authors include Raman Bahal, Karishma Dhuri, Elias Quijano, Ajit Vikram, Hà Phạm, Aniket Wahane, Peter M. Glazer, W. Mark Saltzman, Ravinder Reddy Gaddam and Meera Gupta and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Biochemistry.

In The Last Decade

Anisha Gupta

30 papers receiving 1.3k citations

Hit Papers

Antisense Oligonucleotides: An Emerging Area in Drug Disc... 2020 2026 2022 2024 2020 2021 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anisha Gupta United States 15 815 190 180 110 107 36 1.3k
Xiangping Liu China 19 662 0.8× 253 1.3× 114 0.6× 144 1.3× 88 0.8× 95 1.3k
Haotian Chen China 19 630 0.8× 187 1.0× 170 0.9× 177 1.6× 54 0.5× 69 1.2k
Zhi Sheng United States 23 779 1.0× 156 0.8× 80 0.4× 193 1.8× 70 0.7× 58 1.4k
Yuda Chen United States 14 540 0.7× 159 0.8× 123 0.7× 177 1.6× 51 0.5× 25 874
Yudong Li China 16 341 0.4× 120 0.6× 115 0.6× 92 0.8× 62 0.6× 34 907
Junjie Feng China 19 780 1.0× 256 1.3× 72 0.4× 156 1.4× 65 0.6× 33 995
Ping‐Hsing Tsai Taiwan 23 808 1.0× 300 1.6× 56 0.3× 146 1.3× 49 0.5× 51 1.4k

Countries citing papers authored by Anisha Gupta

Since Specialization
Citations

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

Fields of papers citing papers by Anisha Gupta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anisha Gupta

This figure shows the co-authorship network connecting the top 25 collaborators of Anisha Gupta. A scholar is included among the top collaborators of Anisha Gupta 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 Anisha Gupta. Anisha Gupta 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.
Slack, Frank J., et al.. (2026). Advances in peptide nucleic acid for targeting RNA and genomic DNA. Cell Reports Physical Science. 7(1). 103061–103061.
2.
Ricciardi, Adele S., Elias Quijano, Anisha Gupta, et al.. (2025). Systemic in utero gene editing as a treatment for cystic fibrosis. Proceedings of the National Academy of Sciences. 122(24). e2418731122–e2418731122. 2 indexed citations
3.
Gupta, Anisha, et al.. (2025). A novel sarcasm detection approach for text-image data: Leveraging multimodal fusion and weighted latent factors. Information Fusion. 123. 103266–103266.
4.
Parkinson, Charles R., Maria Davies, Anisha Gupta, et al.. (2024). Why is dentine hypersensitivity underdiagnosed: DHCP and patient perspective. International Dental Journal. 74. S33–S34.
5.
Asimakopoulou, Koula, Nicola West, Maria Davies, et al.. (2024). Why don't patients with dentine hypersensitivity discuss the condition with their dentist?. Journal of Dentistry. 150. 105362–105362.
6.
Gupta, Anisha, Elias Quijano, Alexandra S. Piotrowski-Daspit, et al.. (2024). Next generation triplex-forming PNAs for site-specific genome editing of the F508del CFTR mutation. Journal of Cystic Fibrosis. 24(1). 142–148.
7.
Wahane, Aniket, et al.. (2024). Development of bioconjugate-based delivery systems for nucleic acids. RNA. 31(1). 1–13.
8.
Gupta, Anisha, et al.. (2024). A Hybrid U-Net and Vision Transformer approach for Video Anomaly detection. 1–6. 1 indexed citations
9.
Kumar, Vikas, et al.. (2024). Enhancing RNA inhibitory activity using clamp-G-modified nucleobases. Cell Reports Physical Science. 5(8). 102120–102120. 2 indexed citations
10.
Asimakopoulou, Koula, Nicola West, Maria Davies, et al.. (2023). Why don't dental teams routinely discuss dentine hypersensitivity during consultations? A qualitative study informed by the Theoretical Domains Framework. Journal Of Clinical Periodontology. 51(2). 118–126. 2 indexed citations
11.
Kumar, Vikas, Aniket Wahane, Anisha Gupta, José E. Manautou, & Raman Bahal. (2023). Multivalent Lactobionic Acid and N‐Acetylgalactosamine‐Conjugated Peptide Nucleic Acids for Efficient In Vivo Targeting of Hepatocytes. Advanced Healthcare Materials. 12(12). e2202859–e2202859. 12 indexed citations
12.
Gupta, Anisha, et al.. (2023). Therapeutic and diagnostic applications of antisense peptide nucleic acids. Molecular Therapy — Nucleic Acids. 35(1). 102086–102086. 21 indexed citations
13.
Piotrowski-Daspit, Alexandra S., Yanxiang Deng, Adele S. Ricciardi, et al.. (2022). In vivo correction of cystic fibrosis mediated by PNA nanoparticles. Science Advances. 8(40). eabo0522–eabo0522. 29 indexed citations
14.
Dhuri, Karishma, Jason Shi, Eleni Anastasiadou, et al.. (2022). Simultaneous Targeting of Multiple oncomiRs with Phosphorothioate or PNA-Based Anti-miRs in Lymphoma Cell Lines. Pharmaceutical Research. 39(11). 2709–2720. 8 indexed citations
15.
Gupta, Anisha, et al.. (2021). Formulation and fluoride content of dentifrices: a review of current patterns. BDJ. 6 indexed citations
16.
Gupta, Anisha, et al.. (2019). Assessment of Critical Factors Affecting E-Learning Education. 21(15). 53–66. 1 indexed citations
17.
Gupta, Anisha, Raman Bahal, Meera Gupta, Peter M. Glazer, & W. Mark Saltzman. (2016). Nanotechnology for delivery of peptide nucleic acids (PNAs). Journal of Controlled Release. 240. 302–311. 60 indexed citations
18.
McNeer, Nicole, Rachel J. Fields, Christina Caputo, et al.. (2015). Nanoparticles that deliver triplex-forming peptide nucleic acid molecules correct F508del CFTR in airway epithelium. Nature Communications. 6(1). 6952–6952. 113 indexed citations
19.
Jarvela, Alys M. Cheatle, Anastasia Vedenko, Anisha Gupta, et al.. (2014). Modular Evolution of DNA-Binding Preference of a Tbrain Transcription Factor Provides a Mechanism for Modifying Gene Regulatory Networks. Molecular Biology and Evolution. 31(10). 2672–2688. 24 indexed citations
20.
Gupta, Anisha, L. Slade Lee, Subhadeep Roy, et al.. (2013). Strand Invasion of DNA Quadruplexes by PNA: Comparison of Homologous and Complementary Hybridization. ChemBioChem. 14(12). 1476–1484. 22 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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