Saumya Patel

624 total citations
71 papers, 400 citations indexed

About

Saumya Patel is a scholar working on Molecular Biology, Computational Theory and Mathematics and Plant Science. According to data from OpenAlex, Saumya Patel has authored 71 papers receiving a total of 400 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Molecular Biology, 14 papers in Computational Theory and Mathematics and 12 papers in Plant Science. Recurrent topics in Saumya Patel's work include Computational Drug Discovery Methods (14 papers), MicroRNA in disease regulation (9 papers) and Synthesis and biological activity (5 papers). Saumya Patel is often cited by papers focused on Computational Drug Discovery Methods (14 papers), MicroRNA in disease regulation (9 papers) and Synthesis and biological activity (5 papers). Saumya Patel collaborates with scholars based in India, Iran and United States. Saumya Patel's co-authors include Rakesh Rawal, Yogesh T. Jasrai, Himanshu Pandya, Maulikkumar Patel, Archana Mankad, Sivakumar Prasanth Kumar, Kanisha Shah, Biswaranjan Paital, Shivangi Mathur and Shanaya Patel and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Archives of Biochemistry and Biophysics.

In The Last Decade

Saumya Patel

55 papers receiving 392 citations

Peers

Saumya Patel

POLLU

Wanyan Wang China

Meng Sun China

Vinay Randhawa India

Manish Dwivedi India

Vikas Yadav India

Ahmed Hassan Ibrahim Faraag Egypt

Geetha B. Kumar India

Gulshan Wadhwa India

Kênya Silva Cunha Brazil

Jingnan Xu China

Wanyan Wang China

Saumya Patel

262 ×1.7

98 ×1.2

58 ×0.7

26 ×0.5

18 ×0.5

POLLU

Citations per year, relative to Saumya Patel Saumya Patel (= 1×) peers Wanyan Wang

Countries citing papers authored by Saumya Patel

Since Specialization

Citations

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

Fields of papers citing papers by Saumya Patel

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saumya Patel

This figure shows the co-authorship network connecting the top 25 collaborators of Saumya Patel. A scholar is included among the top collaborators of Saumya Patel 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 Saumya Patel. Saumya Patel 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

Agrawal, Prachi, et al.. (2025). Introduction to microbiomes in health and diseases. International review of cell and molecular biology. 394. 1–42.

Patel, Bhumika, et al.. (2025). Structure-guided computational design of novel polycyclic aromatic compounds as telomerase inhibitors for the treatment of cancer. Network Modeling Analysis in Health Informatics and Bioinformatics. 14(1).

Patel, Saumya, et al.. (2025). Designing a potential universal multi-epitope vaccine candidate against Hepatitis E Virus. Next research.. 2(2). 100365–100365.

Patel, Maulikkumar, et al.. (2024). Deciphering the latent biomarkers in HBV and HDV- associated HepatoCellular carcinoma – An integrated bioinformatics analysis. Human Gene. 40. 201287–201287.

Mehta, Devashish, et al.. (2024). Furan-Triazine clubbed Schiff base derivatives: Computational insight and empirical precision against A-549 and MDA-MB-468 Carcinoma cells. Journal of Molecular Structure. 1321. 140141–140141.

Hamid, Roslida Abd, et al.. (2024). Exploring the therapeutic mechanisms of millet in obesity through molecular docking, pharmacokinetics, and dynamic simulation. Frontiers in Nutrition. 11. 1453819–1453819. 4 indexed citations

Rawal, Rakesh, et al.. (2024). Integrative bioinformatics analysis for the identification of hub genes and Virtual screening of phytochemicals to inhibit AURKA in HepatoCellular carcinoma. Human Gene. 41. 201321–201321.

Bhatt, Hardik, et al.. (2024). Designing of target‐specific N ‐substituted tetrahydroquinoline derivatives as potent mTOR inhibitors via integrated structure‐guided computational approaches. ChemistrySelect. 9(7). 6 indexed citations

Rawal, Rakesh, et al.. (2023). Deciphering the role of Andrographis paniculata micro-RNAs in regulation of cancer. Human Gene. 36. 201162–201162. 4 indexed citations

10.

Patel, Saumya, et al.. (2023). New molecular insights for 4 H -1,2,4-triazole derivatives as inhibitors of tankyrase and Wnt-signaling antagonist: a molecular dynamics simulation study. Journal of Biomolecular Structure and Dynamics. 41(22). 13496–13508. 3 indexed citations

11.

Patel, Saumya, et al.. (2023). Design of 2-amino-6-methyl-pyrimidine benzoic acids as ATP competitive casein kinase-2 (CK2) inhibitors using structure- and fragment-based design, docking and molecular dynamic simulation studies. SAR and QSAR in environmental research. 34(3). 211–230. 3 indexed citations

12.

Patel, Saumya, et al.. (2023). Deciphering the lysine acetylation pattern of leptospiral strains by in silico approach. Network Modeling Analysis in Health Informatics and Bioinformatics. 12(1). 1 indexed citations

13.

Patel, Chirag, et al.. (2023). COMPUTATIONAL ANALYSIS OF TRANSCRIPTION FACTORS AS CANCER DRUG TARGETS WITH POTENTIAL INHIBITORS FROM THE NPACT DATABASE. 2(2). 14–26.

14.

Kumar, Sivakumar Prasanth, et al.. (2022). MHC2AffyPred : A machine‐learning approach to estimate affinity of MHC class II peptides based on structural interaction fingerprints. Proteins Structure Function and Bioinformatics. 91(2). 277–289. 1 indexed citations

15.

Jha, Neha, et al.. (2022). Small RNA sequencing and identification of papaya (Carica papaya L.) miRNAs with potential cross-kingdom human gene targets. Molecular Genetics and Genomics. 297(4). 981–997. 11 indexed citations

16.

Patel, Maulikkumar, Shanaya Patel, Saumya Patel, et al.. (2018). Ocimum basilicum miRNOME revisited: A cross kingdom approach. Genomics. 111(4). 772–785. 16 indexed citations

17.

Patel, Saumya, et al.. (2015). 200 Structural insights into the theoretical model of Plasmodium falciparum multi drug resistance 1 protein (PfMDR1) and its interaction with phytochemicals as efficacious antimalarial drugs: an in silico and in vitro approach. Journal of Biomolecular Structure and Dynamics. 33(sup1). 132–134. 1 indexed citations

18.

Patel, Saumya, et al.. (2013). A Computational Approach towards the Understanding of Plasmodium falciparum Multidrug Resistance Protein 1. PubMed. 2013. 1–15. 7 indexed citations

19.

Patel, Saumya, et al.. (2012). Virtual Screening of Xanthones in Combating Malaria Targeting Plasmodium Falciparum Erythrocyte Membrane Protein 1(PfEMP1). Asian journal of biomedical and pharmaceutical sciences. 2(6). 0. 1 indexed citations

20.

Vora, Rita, et al.. (2012). Prevalence Of Various Dermatoses in School Children of Anand District. SHILAP Revista de lepidopterología. 14 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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