Kavitha Bharatham

509 total citations
20 papers, 405 citations indexed

About

Kavitha Bharatham is a scholar working on Molecular Biology, Organic Chemistry and Oncology. According to data from OpenAlex, Kavitha Bharatham has authored 20 papers receiving a total of 405 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 2 papers in Organic Chemistry and 2 papers in Oncology. Recurrent topics in Kavitha Bharatham's work include Protein Structure and Dynamics (5 papers), RNA and protein synthesis mechanisms (5 papers) and Galectins and Cancer Biology (2 papers). Kavitha Bharatham is often cited by papers focused on Protein Structure and Dynamics (5 papers), RNA and protein synthesis mechanisms (5 papers) and Galectins and Cancer Biology (2 papers). Kavitha Bharatham collaborates with scholars based in South Korea, India and Singapore. Kavitha Bharatham's co-authors include Nagakumar Bharatham, Keun Woo Lee, Ki Hun Park, Anang A. Shelat, Keun Woo Lee, Ivana Mihalek, David Ban, Jian Zuo, Luigi I. Iconaru and Arvind Ramanathan and has published in prestigious journals such as Nucleic Acids Research, Molecular Cell and PLoS ONE.

In The Last Decade

Kavitha Bharatham

19 papers receiving 398 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kavitha Bharatham South Korea 11 297 74 64 53 30 20 405
Jingxuan Zhu China 12 309 1.0× 69 0.9× 42 0.7× 55 1.0× 29 1.0× 27 513
Mohd Rehan Ajmal India 8 350 1.2× 68 0.9× 58 0.9× 52 1.0× 115 3.8× 11 603
David Machalz Germany 10 214 0.7× 139 1.9× 49 0.8× 35 0.7× 43 1.4× 15 381
Songmi Kim South Korea 12 223 0.8× 80 1.1× 49 0.8× 29 0.5× 18 0.6× 20 367
Jessica E. Friedman United States 6 331 1.1× 78 1.1× 101 1.6× 38 0.7× 87 2.9× 7 625
Abdul Rashid Issahaku South Africa 9 150 0.5× 112 1.5× 61 1.0× 20 0.4× 28 0.9× 36 304
Selvaraman Nagamani India 13 195 0.7× 177 2.4× 63 1.0× 29 0.5× 35 1.2× 44 380
Monimoy Banerjee United States 13 279 0.9× 49 0.7× 20 0.3× 56 1.1× 60 2.0× 23 420
Sarah Tomas‐Hernández Spain 7 234 0.8× 143 1.9× 56 0.9× 39 0.7× 46 1.5× 10 418
Md. Junaid Bangladesh 14 219 0.7× 96 1.3× 81 1.3× 29 0.5× 44 1.5× 30 484

Countries citing papers authored by Kavitha Bharatham

Since Specialization
Citations

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

Fields of papers citing papers by Kavitha Bharatham

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kavitha Bharatham

This figure shows the co-authorship network connecting the top 25 collaborators of Kavitha Bharatham. A scholar is included among the top collaborators of Kavitha Bharatham 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 Kavitha Bharatham. Kavitha Bharatham 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.
Singh, Manvi, et al.. (2022). Identification of Mtb GlmU Uridyltransferase Domain Inhibitors by Ligand-Based and Structure-Based Drug Design Approaches. Molecules. 27(9). 2805–2805. 2 indexed citations
2.
3.
Watt, Paul M., Vikrant Kumar, Kavitha Bharatham, et al.. (2021). Target identification for small-molecule discovery in the FOXO3a tumor-suppressor pathway using a biodiverse peptide library. Cell chemical biology. 28(11). 1602–1615.e9. 8 indexed citations
4.
5.
Chintha, Chetan, Kavyashree Manjunath, Kavitha Bharatham, et al.. (2018). Targeting Phosphopeptide Recognition by the Human BRCA1 Tandem BRCT Domain to Interrupt BRCA1-Dependent Signaling. Cell chemical biology. 25(6). 677–690.e12. 15 indexed citations
6.
Iconaru, Luigi I., David Ban, Kavitha Bharatham, et al.. (2015). Discovery of Small Molecules that Inhibit the Disordered Protein, p27Kip1. Scientific Reports. 5(1). 15686–15686. 67 indexed citations
7.
Krishnamurthy, Srinath, Balakrishnan S. Moorthy, Kavitha Bharatham, et al.. (2014). Active Site Coupling in PDE:PKA Complexes Promotes Resetting of Mammalian cAMP Signaling. Biophysical Journal. 107(6). 1426–1440. 24 indexed citations
8.
McCoy, Francis, Rashid Darbandi, Hoi Chang Lee, et al.. (2013). Metabolic Activation of CaMKII by Coenzyme A. Molecular Cell. 52(3). 468–468. 1 indexed citations
9.
Bharatham, Nagakumar, Kavitha Bharatham, Anang A. Shelat, & Donald Bashford. (2013). Ligand Binding Mode Prediction by Docking: Mdm2/Mdmx Inhibitors as a Case Study. Journal of Chemical Information and Modeling. 54(2). 648–659. 29 indexed citations
10.
McCoy, Francis, Rashid Darbandi, Hoi Chang Lee, et al.. (2013). Metabolic Activation of CaMKII by Coenzyme A. Molecular Cell. 52(3). 325–339. 29 indexed citations
11.
Zhang, Zong Hong, et al.. (2011). Cube-DB: detection of functional divergence in human protein families. Nucleic Acids Research. 40(D1). D490–D494. 3 indexed citations
12.
Bharatham, Kavitha, Zong Hong Zhang, & Ivana Mihalek. (2011). Determinants, Discriminants, Conserved Residues - A Heuristic Approach to Detection of Functional Divergence in Protein Families. PLoS ONE. 6(9). e24382–e24382. 12 indexed citations
13.
Zhang, Zong Hong, et al.. (2010). deconSTRUCT: general purpose protein database search on the substructure level. Nucleic Acids Research. 38(suppl_2). W590–W594. 12 indexed citations
14.
Bharatham, Nagakumar, Kavitha Bharatham, Yuno Lee, et al.. (2010). Molecular Docking Study of Aminoacyl-tRNA Synthetases with Ligand Molecules from Four Different Scaffolds. Bulletin of the Korean Chemical Society. 31(3). 606–610. 1 indexed citations
15.
Bharatham, Nagakumar, Kavitha Bharatham, Yuno Lee, & Keun Woo Lee. (2009). Molecular dynamics simulation study of valyl-tRNA synthetase with its pre- and post-transfer editing substrates. Biophysical Chemistry. 143(1-2). 34–43. 7 indexed citations
16.
Bharatham, Kavitha, Nagakumar Bharatham, Yong Jung Kwon, & Keun Woo Lee. (2008). Molecular dynamics simulation study of PTP1B with allosteric inhibitor and its application in receptor based pharmacophore modeling. Journal of Computer-Aided Molecular Design. 22(12). 925–933. 29 indexed citations
17.
Bharatham, Kavitha, Nagakumar Bharatham, Ki Hun Park, & Keun Woo Lee. (2007). Binding mode analyses and pharmacophore model development for sulfonamide chalcone derivatives, a new class of α-glucosidase inhibitors. Journal of Molecular Graphics and Modelling. 26(8). 1202–1212. 97 indexed citations
18.
Bharatham, Kavitha, Nagakumar Bharatham, & Keun Woo Lee. (2007). Pharmacophore modeling for protein tyrosine phosphatase 1B inhibitors. Archives of Pharmacal Research. 30(5). 533–542. 11 indexed citations
19.
Bharatham, Nagakumar, Kavitha Bharatham, & Keun Woo Lee. (2006). Pharmacophore identification and virtual screening for methionyl-tRNA synthetase inhibitors. Journal of Molecular Graphics and Modelling. 25(6). 813–823. 44 indexed citations
20.
Bharatham, Nagakumar, et al.. (2006). Urokinase Inhibitor Design Based on Pharmacophore Model Derived from Diverse Classes of Inhibitors. 1(2). 115–122. 1 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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