Rohit Bavi

907 total citations
26 papers, 705 citations indexed

About

Rohit Bavi is a scholar working on Molecular Biology, Oncology and Computational Theory and Mathematics. According to data from OpenAlex, Rohit Bavi has authored 26 papers receiving a total of 705 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 5 papers in Oncology and 5 papers in Computational Theory and Mathematics. Recurrent topics in Rohit Bavi's work include RNA and protein synthesis mechanisms (7 papers), Computational Drug Discovery Methods (5 papers) and RNA modifications and cancer (5 papers). Rohit Bavi is often cited by papers focused on RNA and protein synthesis mechanisms (7 papers), Computational Drug Discovery Methods (5 papers) and RNA modifications and cancer (5 papers). Rohit Bavi collaborates with scholars based in India, South Korea and China. Rohit Bavi's co-authors include Md Aquib, Muhammad Asim Farooq, Keun Woo Lee, Raj Kumar, Samuel Kesse, Kailas D. Sonawane, Bo Wang, Faisal Raza, Kofi Oti Boakye‐Yiadom and Mensura Sied Filli and has published in prestigious journals such as PLoS ONE, Scientific Reports and Biochemical and Biophysical Research Communications.

In The Last Decade

Rohit Bavi

25 papers receiving 697 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rohit Bavi India 15 325 233 162 87 56 26 705
Fuzheng Ren China 15 181 0.6× 156 0.7× 141 0.9× 45 0.5× 162 2.9× 40 764
Fengling Zhang China 14 204 0.6× 180 0.8× 233 1.4× 28 0.3× 54 1.0× 30 723
Laleh Alisaraie Canada 13 188 0.6× 172 0.7× 153 0.9× 76 0.9× 58 1.0× 27 555
Ge Hong China 13 222 0.7× 108 0.5× 144 0.9× 38 0.4× 107 1.9× 35 659
Senbiao Fang China 15 429 1.3× 53 0.2× 132 0.8× 53 0.6× 60 1.1× 40 720
Ravinder Verma India 14 207 0.6× 131 0.6× 166 1.0× 40 0.5× 209 3.7× 61 835
Mian Zu China 11 258 0.8× 236 1.0× 329 2.0× 30 0.3× 96 1.7× 15 792
Hongmei Wen China 13 285 0.9× 142 0.6× 87 0.5× 22 0.3× 30 0.5× 47 575
Bharti Mangla India 18 331 1.0× 83 0.4× 125 0.8× 29 0.3× 213 3.8× 47 902
Marwa Sharaky Egypt 15 262 0.8× 132 0.6× 91 0.6× 33 0.4× 64 1.1× 78 892

Countries citing papers authored by Rohit Bavi

Since Specialization
Citations

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

Fields of papers citing papers by Rohit Bavi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rohit Bavi

This figure shows the co-authorship network connecting the top 25 collaborators of Rohit Bavi. A scholar is included among the top collaborators of Rohit Bavi 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 Rohit Bavi. Rohit Bavi 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.
2.
Kumbhar, Navanath, et al.. (2022). Identification of novel leads as potent inhibitors of HDAC3 using ligand-based pharmacophore modeling and MD simulation. Scientific Reports. 12(1). 1712–1712. 25 indexed citations
3.
Barage, Sagar, Rohit Bavi, Neetin Desai, et al.. (2020). Identification and characterization of novel RdRp and Nsp15 inhibitors for SARS-COV2 using computational approach. Journal of Biomolecular Structure and Dynamics. 40(6). 2557–2574. 17 indexed citations
4.
Bavi, Rohit, Parikshit Banerjee, Md Aquib, et al.. (2020). Doxorubicin-Conjugated Innovative 16-mer DNA Aptamer-Based Annexin A1 Targeted Anti-Cancer Drug Delivery. Molecular Therapy — Nucleic Acids. 21. 1074–1086. 21 indexed citations
5.
Aquib, Md, Muhammad Asim Farooq, George Frimpong Boafo, et al.. (2020). Theranostic applications of smart nanomedicines for tumor-targeted chemotherapy: a review. Environmental Chemistry Letters. 18(5). 1509–1527. 14 indexed citations
6.
Rampogu, Shailima, Chanin Park, Minky Son, et al.. (2019). Pharmacotherapeutics and Molecular Mechanism of Phytochemicals in Alleviating Hormone-Responsive Breast Cancer. Oxidative Medicine and Cellular Longevity. 2019. 1–14. 17 indexed citations
7.
Boakye‐Yiadom, Kofi Oti, Samuel Kesse, Yaw Opoku‐Damoah, et al.. (2019). Carbon dots: Applications in bioimaging and theranostics. International Journal of Pharmaceutics. 564. 308–317. 231 indexed citations
8.
Bavi, Rohit, et al.. (2019). In silico designed RNA aptamer against epithelial cell adhesion molecule for cancer cell imaging. Biochemical and Biophysical Research Communications. 509(4). 937–942. 31 indexed citations
9.
Kumar, Raj, Parameswaran Saravanan, Rohit Bavi, et al.. (2018). Investigation of novel chemical scaffolds targeting prolyl oligopeptidase for neurological therapeutics. Journal of Molecular Graphics and Modelling. 88. 92–103. 11 indexed citations
10.
Rampogu, Shailima, Ayoung Baek, Amir Zeb, et al.. (2018). Ginger (Zingiber officinale) phytochemicals—gingerenone-A and shogaol inhibit SaHPPK: molecular docking, molecular dynamics simulations and in vitro approaches. Annals of Clinical Microbiology and Antimicrobials. 17(1). 16–16. 54 indexed citations
11.
Kumar, Raj, Rohit Bavi, Min Gi Jo, et al.. (2017). New compounds identified through in silico approaches reduce the α-synuclein expression by inhibiting prolyl oligopeptidase in vitro. Scientific Reports. 7(1). 10827–10827. 29 indexed citations
12.
Bavi, Rohit, et al.. (2016). Exploration of Novel Inhibitors for Bruton’s Tyrosine Kinase by 3D QSAR Modeling and Molecular Dynamics Simulation. PLoS ONE. 11(1). e0147190–e0147190. 29 indexed citations
13.
Bavi, Rohit, Raj Kumar, Shailima Rampogu, et al.. (2016). Molecular interactions of UvrB protein and DNA from Helicobacter pylori: Insight into a molecular modeling approach. Computers in Biology and Medicine. 75. 181–189. 13 indexed citations
14.
Sonawane, Kailas D., et al.. (2016). Comparative Structural Dynamics of tRNAPhe with Respect to Hinge Region Methylated Guanosine: A Computational Approach. Cell Biochemistry and Biophysics. 74(2). 157–173. 11 indexed citations
15.
Bavi, Rohit, Raj Kumar, Shailima Rampogu, et al.. (2016). Novel virtual lead identification in the discovery of hematopoietic cell kinase (HCK) inhibitors: application of 3D QSAR and molecular dynamics simulation. Journal of Receptors and Signal Transduction. 37(3). 224–238. 10 indexed citations
16.
Kumar, Raj, Minky Son, Rohit Bavi, et al.. (2015). Novel chemical scaffolds of the tumor marker AKR1B10 inhibitors discovered by 3D QSAR pharmacophore modeling. Acta Pharmacologica Sinica. 36(8). 998–1012. 29 indexed citations
17.
Kumbhar, Bajarang Vasant, et al.. (2014). Conformational Preferences of Modified Nucleoside 5-Taurinomethyluridine, τm5U Occur at ‘wobble’ 34th Position in the Anticodon Loop of tRNA. Cell Biochemistry and Biophysics. 71(3). 1589–1603. 14 indexed citations
18.
Kumbhar, Bajarang Vasant, et al.. (2014). Structural significance of modified nucleosides k2C and t6A present in the anticodon loop of tRNAIle. RSC Advances. 4(27). 14176–14176. 11 indexed citations
19.
Bavi, Rohit, et al.. (2013). MD SIMULATION STUDIES TO INVESTIGATE ISO-ENERGETIC CONFORMATIONAL BEHAVIOUR OF MODIFIED NUCLEOSIDES M2G AND M22G PRESENT IN tRNA. Computational and Structural Biotechnology Journal. 5(6). e201302015–e201302015. 20 indexed citations
20.

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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