Prahlad T. Ram

13.8k total citations · 4 hit papers
67 papers, 8.5k citations indexed

About

Prahlad T. Ram is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Prahlad T. Ram has authored 67 papers receiving a total of 8.5k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Molecular Biology, 20 papers in Cancer Research and 15 papers in Oncology. Recurrent topics in Prahlad T. Ram's work include MicroRNA in disease regulation (12 papers), Gene Regulatory Network Analysis (12 papers) and Bioinformatics and Genomic Networks (12 papers). Prahlad T. Ram is often cited by papers focused on MicroRNA in disease regulation (12 papers), Gene Regulatory Network Analysis (12 papers) and Bioinformatics and Genomic Networks (12 papers). Prahlad T. Ram collaborates with scholars based in United States, United Kingdom and Puerto Rico. Prahlad T. Ram's co-authors include Ravi Iyengar, Gordon B. Mills, Yiling Lu, Bryan T. Hennessy, Debra L. Smith, Susana R. Neves, Richard M. Schultz, Upinder S. Bhalla, Kakajan Komurov and Steven M. Hill and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Prahlad T. Ram

67 papers receiving 8.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Exploiting the PI3K/AKT Pathway for Cancer Drug Discovery

2005 1.8k citations Prahlad T. Ram, Yiling Lu et al. profile →
G Protein Pathways

2002 969 citations Prahlad T. Ram, Ravi Iyengar et al. profile →
Core epithelial-to-mesenchymal transition interactome gene-expression signature is associated with claudin-low and metaplastic breast cancer subtypes

2010 803 citations Kakajan Komurov, Prahlad T. Ram et al. profile →
Tumor microenvironment derived exosomes pleiotropically modulate cancer cell metabolism

2016 729 citations Tyler J. Moss, Elena G. Seviour et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Prahlad T. Ram United States	39	6.0k	2.0k	1.9k	688	626	67	8.5k
Nicholas C. Popescu United States	49	5.6k 0.9×	1.9k 1.0×	1.4k 0.7×	948 1.4×	628 1.0×	104	8.6k
Stephan Wullschleger Switzerland	21	6.3k 1.0×	1.3k 0.7×	871 0.5×	437 0.6×	967 1.5×	26	8.8k
Stefan Wiemann Germany	51	5.8k 1.0×	1.2k 0.6×	2.1k 1.1×	753 1.1×	778 1.2×	186	8.8k
Wilhelm Haas United States	53	11.0k 1.8×	2.0k 1.0×	1.5k 0.8×	907 1.3×	847 1.4×	101	15.3k
David H. Hawke United States	48	7.4k 1.2×	1.7k 0.9×	2.7k 1.4×	395 0.6×	878 1.4×	134	9.9k
Vuk Stambolic Canada	44	8.6k 1.4×	2.5k 1.3×	1.6k 0.8×	769 1.1×	1.0k 1.6×	85	10.8k
Ashani T. Weeraratna United States	40	3.9k 0.7×	1.8k 0.9×	1.1k 0.5×	405 0.6×	1.1k 1.7×	114	6.6k
Roberto D. Polakiewicz United States	41	6.7k 1.1×	1.4k 0.7×	1.3k 0.7×	456 0.7×	948 1.5×	69	9.1k
Tullio Florio Italy	57	5.0k 0.8×	2.9k 1.5×	1.4k 0.7×	336 0.5×	1.5k 2.3×	272	10.3k
Richard B. Pearson Australia	61	9.6k 1.6×	2.1k 1.0×	1.3k 0.7×	640 0.9×	889 1.4×	136	12.4k

Countries citing papers authored by Prahlad T. Ram

Since Specialization

Citations

This map shows the geographic impact of Prahlad T. Ram'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 Prahlad T. Ram with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Prahlad T. Ram more than expected).

Fields of papers citing papers by Prahlad T. Ram

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Prahlad T. Ram. 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 Prahlad T. Ram. The network helps show where Prahlad T. Ram may publish in the future.

Co-authorship network of co-authors of Prahlad T. Ram

This figure shows the co-authorship network connecting the top 25 collaborators of Prahlad T. Ram. A scholar is included among the top collaborators of Prahlad T. Ram 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 Prahlad T. Ram. Prahlad T. Ram is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Parashar, Deepak, Anjali Geethadevi, Jasmine George, et al.. (2020). Peritoneal Spread of Ovarian Cancer Harbors Therapeutic Vulnerabilities Regulated by FOXM1 and EGFR/ERBB2 Signaling. Cancer Research. 80(24). 5554–5568. 29 indexed citations

Ma, Shaolin, Sunila Pradeep, Alejandro Villar‐Prados, et al.. (2019). GnRH-R–Targeted Lytic Peptide Sensitizes BRCA Wild-type Ovarian Cancer to PARP Inhibition. Molecular Cancer Therapeutics. 18(5). 969–979. 13 indexed citations

Villar‐Prados, Alejandro, Sherry Y. Wu, Karem A. Court, et al.. (2018). Predicting Novel Therapies and Targets: Regulation of Notch3 by the Bromodomain Protein BRD4. Molecular Cancer Therapeutics. 18(2). 421–436. 10 indexed citations

Seviour, Elena G., Vishal Sehgal, Dhruva K. Mishra, et al.. (2016). Targeting KRas-dependent tumour growth, circulating tumour cells and metastasis in vivo by clinically significant miR-193a-3p. Oncogene. 36(10). 1339–1350. 38 indexed citations

Kang, Yu, Archana S. Nagaraja, Guillermo N. Armaiz-Peña, et al.. (2015). Adrenergic Stimulation of DUSP1 Impairs Chemotherapy Response in Ovarian Cancer. Clinical Cancer Research. 22(7). 1713–1724. 77 indexed citations

Moss, Tyler J., Elena G. Seviour, Vasudha Sehgal, et al.. (2015). Genome-wide perturbations by miRNAs map onto functional cellular pathways, identifying regulators of chromatin modifiers. npj Systems Biology and Applications. 1(1). 15001–15001. 5 indexed citations

Seviour, Elena G., Vishal Sehgal, Yue Lu, et al.. (2015). Functional proteomics identifies miRNAs to target a p27/Myc/phospho-Rb signature in breast and ovarian cancer. Oncogene. 35(6). 691–701. 48 indexed citations

Gopal, Y.N. Vashisht, Helen Rizos, Guo Chen, et al.. (2014). Inhibition of mTORC1/2 Overcomes Resistance to MAPK Pathway Inhibitors Mediated by PGC1α and Oxidative Phosphorylation in Melanoma. Cancer Research. 74(23). 7037–7047. 148 indexed citations

Wen, Yunfei, Whitney A. Spannuth Graybill, Rebecca A. Previs, et al.. (2014). Immunotherapy Targeting Folate Receptor Induces Cell Death Associated with Autophagy in Ovarian Cancer. Clinical Cancer Research. 21(2). 448–459. 53 indexed citations

10.

Roh, Ju‐Won, Jie Huang, Wei Hu, et al.. (2014). Biologic Effects of Platelet-Derived Growth Factor Receptor α Blockade in Uterine Cancer. Clinical Cancer Research. 20(10). 2740–2750. 15 indexed citations

11.

Slingluff, Craig L., Gina R. Petroni, David L. Brautigan, et al.. (2013). Clinical Activity and Safety of Combination Therapy with Temsirolimus and Bevacizumab for Advanced Melanoma: A Phase II Trial (CTEP 7190/Mel47). Clinical Cancer Research. 19(13). 3611–3620. 28 indexed citations

12.

Ram, Prahlad T., John Mendelsohn, & Gordon B. Mills. (2012). Bioinformatics and systems biology. Molecular Oncology. 6(2). 147–154. 16 indexed citations

13.

Nick, Alpa M., Rebecca L. Stone, Guillermo N. Armaiz-Peña, et al.. (2011). Silencing of p130Cas in Ovarian Carcinoma: A Novel Mechanism for Tumor Cell Death. JNCI Journal of the National Cancer Institute. 103(21). 1596–1612. 40 indexed citations

14.

Iadevaia, Sergio, Yiling Lu, Fabiana C. Morales, Gordon B. Mills, & Prahlad T. Ram. (2010). Identification of Optimal Drug Combinations Targeting Cellular Networks: Integrating Phospho-Proteomics and Computational Network Analysis. Cancer Research. 70(17). 6704–6714. 164 indexed citations

15.

Gopal, Y.N. Vashisht, Wanleng Deng, Scott E. Woodman, et al.. (2010). Basal and Treatment-Induced Activation of AKT Mediates Resistance to Cell Death by AZD6244 (ARRY-142886) in Braf- Mutant Human Cutaneous Melanoma Cells. Cancer Research. 70(21). 8736–8747. 177 indexed citations

16.

Ruths, Derek, Luay Nakhleh, & Prahlad T. Ram. (2008). Rapidly exploring structural and dynamic properties of signaling networks using PathwayOracle. BMC Systems Biology. 2(1). 76–76. 12 indexed citations

17.

Öbrink, Björn, Hiroki Sawa, Inka Scheffrahn, et al.. (2002). Computational Analysis of Isoform‐Specific Signal Regulation by CEACAM1—A Cell Adhesion Molecule Expressed in PC12 Cells. Annals of the New York Academy of Sciences. 971(1). 597–607. 24 indexed citations

18.

Dai, Jun, Prahlad T. Ram, Lin Yuan, Louaine L. Spriggs, & Steven M. Hill. (2001). Transcriptional repression of RORα activity in human breast cancer cells by melatonin. Molecular and Cellular Endocrinology. 176(1-2). 111–120. 53 indexed citations

19.

Worrad, Diane M., Prahlad T. Ram, & Richard M. Schultz. (1994). Regulation of gene expression in the mouse oocyte and early preimplantation embryo: developmental changes in Sp1 and TATA box-binding protein, TBP. Development. 120(8). 2347–2357. 158 indexed citations

20.

Ram, Prahlad T. & Richard M. Schultz. (1993). Reporter Gene Expression in G2 of the 1-Cell Mouse Embryo. Developmental Biology. 156(2). 552–556. 165 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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