Naveen Babbar

2.4k total citations
31 papers, 1.1k citations indexed

About

Naveen Babbar is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Oncology. According to data from OpenAlex, Naveen Babbar has authored 31 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 17 papers in Pulmonary and Respiratory Medicine and 13 papers in Oncology. Recurrent topics in Naveen Babbar's work include Advanced Breast Cancer Therapies (17 papers), Polyamine Metabolism and Applications (9 papers) and Cancer Genomics and Diagnostics (7 papers). Naveen Babbar is often cited by papers focused on Advanced Breast Cancer Therapies (17 papers), Polyamine Metabolism and Applications (9 papers) and Cancer Genomics and Diagnostics (7 papers). Naveen Babbar collaborates with scholars based in United States, Spain and Italy. Naveen Babbar's co-authors include Robert A. Casero, Eugene W. Gerner, Natalia A. Ignatenko, Tracy Murray Stewart, Nadia Solovieff, Marı́a Elena Martı́nez, Fei Su, David W. Boorman, Yongjun Guo and Amy Hacker and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Oncology.

In The Last Decade

Naveen Babbar

30 papers receiving 1.1k citations

Peers

Naveen Babbar
Xiaoning Wu China
Ming‐Derg Lai Taiwan
Russell D. Klein United States
Carrie Cartwright United States
Gerhard Sperl United States
Yong Zou China
Jason R. Mann United States
Rit Vatsyayan United States
Yayun Liang United States
Gong-Kan Feng China
Xiaoning Wu China
Naveen Babbar
Citations per year, relative to Naveen Babbar Naveen Babbar (= 1×) peers Xiaoning Wu

Countries citing papers authored by Naveen Babbar

Since Specialization
Citations

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

Fields of papers citing papers by Naveen Babbar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Naveen Babbar

This figure shows the co-authorship network connecting the top 25 collaborators of Naveen Babbar. A scholar is included among the top collaborators of Naveen Babbar 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 Naveen Babbar. Naveen Babbar 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.
Chiu, Joanne, Fei Su, Norikazu Masuda, et al.. (2023). Potential value of ctDNA monitoring in metastatic HR + /HER2 − breast cancer: longitudinal ctDNA analysis in the phase Ib MONALEESASIA trial. BMC Medicine. 21(1). 306–306. 13 indexed citations
2.
André, Fabrice, Faye Su, Nadia Solovieff, et al.. (2023). Pooled ctDNA analysis of MONALEESA phase III advanced breast cancer trials. Annals of Oncology. 34(11). 1003–1014. 43 indexed citations
3.
Ferrarotto, Renata, Paul Swiecicki, Dan P. Zandberg, et al.. (2023). PRT543, a protein arginine methyltransferase 5 inhibitor, in patients with advanced adenoid cystic carcinoma: An open-label, phase I dose-expansion study. Oral Oncology. 149. 106634–106634. 19 indexed citations
4.
Wang, Min, et al.. (2023). Abstract C013: Clinical biomarkers based on PK/PD modeling to guide the development for a first-in-class, highly selective SMARCA2 (BRM) degrader, PRT3789. Molecular Cancer Therapeutics. 22(12_Supplement). C013–C013. 1 indexed citations
5.
Monga, Varun, Tanner M. Johanns, Roger Stupp, et al.. (2023). A phase 1 study of the protein arginine methyltransferase 5 (PRMT5) brain-penetrant inhibitor PRT811 in patients (pts) with recurrent high-grade glioma or uveal melanoma (UM).. Journal of Clinical Oncology. 41(16_suppl). 3008–3008. 7 indexed citations
6.
Prat, Aleix, Anwesha Chaudhury, Nadia Solovieff, et al.. (2021). Correlative Biomarker Analysis of Intrinsic Subtypes and Efficacy Across the MONALEESA Phase III Studies. Journal of Clinical Oncology. 39(13). 1458–1467. 90 indexed citations
7.
8.
O’Brien, Neil A., Martina S.J. McDermott, Dylan Conklin, et al.. (2020). Targeting activated PI3K/mTOR signaling overcomes acquired resistance to CDK4/6-based therapies in preclinical models of hormone receptor-positive breast cancer. Breast Cancer Research. 22(1). 89–89. 87 indexed citations
9.
André, Fabrice, Fei Su, Nadia Solovieff, et al.. (2020). Pooled ctDNA analysis of the MONALEESA (ML) phase III advanced breast cancer (ABC) trials.. Journal of Clinical Oncology. 38(15_suppl). 1009–1009. 35 indexed citations
10.
Lu, Yen‐Shen, Sara A. Hurvitz, Fei Su, et al.. (2019). In-depth gene expression analysis of premenopausal patients with HR+/HER2− advanced breast cancer (ABC) treated with ribociclib-containing therapy in the Phase III MONALEESA-7 trial.. Journal of Clinical Oncology. 37(15_suppl). 1018–1018. 5 indexed citations
11.
O’Brien, Neil A., Dylan Conklin, Alex Gaither, et al.. (2019). Abstract 3825: Targeting activated PI3K/mTOR signaling overcomes resistance to CDK4/6-based therapies in preclinical ER+ breast cancer models. 3825–3825. 1 indexed citations
12.
O’Brien, Neil A., Martina S.J. McDermott, Dylan Conklin, et al.. (2019). Abstract 3825: Targeting activated PI3K/mTOR signaling overcomes resistance to CDK4/6-based therapies in preclinical ER+ breast cancer models. Cancer Research. 79(13_Supplement). 3825–3825. 1 indexed citations
13.
Jones, Jeffrey J., Bruce E. Wilcox, Ryan W. Benz, et al.. (2016). A Plasma-Based Protein Marker Panel for Colorectal Cancer Detection Identified by Multiplex Targeted Mass Spectrometry. Clinical Colorectal Cancer. 15(2). 186–194.e13. 27 indexed citations
14.
Babbar, Naveen & Eugene W. Gerner. (2010). Targeting Polyamines and Inflammation for Cancer Prevention. Recent results in cancer research. 188. 49–64. 63 indexed citations
15.
Babbar, Naveen, Tracy Murray Stewart, & Robert A. Casero. (2007). Inflammation and polyamine catabolism: the good, the bad and the ugly. Biochemical Society Transactions. 35(2). 300–304. 68 indexed citations
16.
Babbar, Naveen & Robert A. Casero. (2006). Tumor necrosis factor alpha increases reactive oxygen species production and induces DNA damage by inducing spermine oxidase in human lung bronchial epithelial cells in vitro: Potential mechanism for inflammation induced lung carcinogenesis.. Cancer Epidemiology and Prevention Biomarkers. 15. 1 indexed citations
17.
Babbar, Naveen, Amy Hacker, Yi Huang, & Robert A. Casero. (2006). Tumor Necrosis Factor α Induces Spermidine/Spermine N1-Acetyltransferase through Nuclear Factor κBin Non-small Cell Lung Cancer Cells. Journal of Biological Chemistry. 281(34). 24182–24192. 50 indexed citations
18.
19.
Ignatenko, Natalia A., et al.. (2004). Suppression of polyamine catabolism by activated Ki‐ras in human colon cancer cells. Molecular Carcinogenesis. 39(2). 91–102. 58 indexed citations
20.
Babbar, Naveen, Natalia A. Ignatenko, Robert A. Casero, & Eugene W. Gerner. (2003). Cyclooxygenase-independent Induction of Apoptosis by Sulindac Sulfone Is Mediated by Polyamines in Colon Cancer. Journal of Biological Chemistry. 278(48). 47762–47775. 114 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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