Roman Camarda

2.6k total citations · 1 hit paper
17 papers, 1.8k citations indexed

About

Roman Camarda is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Roman Camarda has authored 17 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 9 papers in Cancer Research and 6 papers in Oncology. Recurrent topics in Roman Camarda's work include Cancer, Hypoxia, and Metabolism (5 papers), Epigenetics and DNA Methylation (3 papers) and Cancer-related Molecular Pathways (3 papers). Roman Camarda is often cited by papers focused on Cancer, Hypoxia, and Metabolism (5 papers), Epigenetics and DNA Methylation (3 papers) and Cancer-related Molecular Pathways (3 papers). Roman Camarda collaborates with scholars based in United States, Germany and South Korea. Roman Camarda's co-authors include Michael Lagunoff, Andrei Goga, Krystal A. Fontaine, Erica L. Sanchez, Gregor Krings, Daniel K. Nomura, Sanjeev Balakrishnan, Alicia Y. Zhou, Brittany Anderton and Atul J. Butte and has published in prestigious journals such as Nature Medicine, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Roman Camarda

17 papers receiving 1.8k citations

Hit Papers

Comprehensive analysis of normal adjacent to tumor transc... 2017 2026 2020 2023 2017 100 200 300
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.

  1. Comprehensive analysis of normal adjacent to tumor transcriptomes
    2017 375 citations Dvir Aran, Roman Camarda et al. Nature Communications profile →

Peers

Roman Camarda
Gangqiao Zhou China
Manuela Vecchi Italy
Zhiao Chen China
Yaoyu E. Wang United States
Peter R. Strack United States
Zheng Fu China
Monika Mehta United States
Yide Mei China
Evangelia Komisopoulou United States
Victoria H. Cowling United Kingdom
Gangqiao Zhou China
Roman Camarda
Citations per year, relative to Roman Camarda Roman Camarda (= 1×) peers Gangqiao Zhou

Countries citing papers authored by Roman Camarda

Since Specialization
Citations

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

Fields of papers citing papers by Roman Camarda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Roman Camarda

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

All Works

17 of 17 papers shown
1.
Ζαννίκου, Μαρκέλλα, Deepak Kanojia, Sara F. Dunne, et al.. (2024). S100A8/A9 predicts response to PIM kinase and PD-1/PD-L1 inhibition in triple-negative breast cancer mouse models. SHILAP Revista de lepidopterología. 4(1). 22–22. 2 indexed citations
2.
Camarda, Roman, Suprit Gupta, Olga Momčilović, et al.. (2021). Oncogene-regulated release of extracellular vesicles. Developmental Cell. 56(13). 1989–2006.e6. 47 indexed citations
3.
Rohrberg, Julia, Joyce V. Lee, Alexandra Corella, et al.. (2020). MYC Dysregulates Mitosis, Revealing Cancer Vulnerabilities. Cell Reports. 30(10). 3368–3382.e7. 38 indexed citations
4.
Yau, Christina, Christopher K. Wong, Yulia Newton, et al.. (2020). A risk-associated Active transcriptome phenotype expressed by histologically normal human breast tissue and linked to a pro-tumorigenic adipocyte population. Breast Cancer Research. 22(1). 81–81. 12 indexed citations
5.
Donnella, Hayley, James T. Webber, Rebecca S. Levin, et al.. (2018). Kinome rewiring reveals AURKA limits PI3K-pathway inhibitor efficacy in breast cancer. Nature Chemical Biology. 14(8). 768–777. 67 indexed citations
6.
Shin, Peter, Zihan Zhu, Roman Camarda, et al.. (2017). Cancer recurrence monitoring using hyperpolarized [1-13C]pyruvate metabolic imaging in murine breast cancer model. Magnetic Resonance Imaging. 43. 105–109. 10 indexed citations
7.
Camarda, Roman, Jeremy Williams, & Andrei Goga. (2017). In vivo Reprogramming of Cancer Metabolism by MYC. Frontiers in Cell and Developmental Biology. 5. 35–35. 47 indexed citations
8.
Anderton, Brittany, Roman Camarda, Sanjeev Balakrishnan, et al.. (2017). MYC ‐driven inhibition of the glutamate‐cysteine ligase promotes glutathione depletion in liver cancer. EMBO Reports. 18(4). 569–585. 64 indexed citations
9.
Aran, Dvir, Roman Camarda, Justin I. Odegaard, et al.. (2017). Comprehensive analysis of normal adjacent to tumor transcriptomes. Nature Communications. 8(1). 1077–1077. 375 indexed citations breakdown →
10.
Camarda, Roman, Alicia Y. Zhou, Rebecca A. Kohnz, et al.. (2016). Inhibition of fatty acid oxidation as a therapy for MYC-overexpressing triple-negative breast cancer. Nature Medicine. 22(4). 427–432. 396 indexed citations
11.
Horiuchi, Dai, Roman Camarda, Alicia Y. Zhou, et al.. (2016). PIM1 kinase inhibition as a targeted therapy against triple-negative breast tumors with elevated MYC expression. Nature Medicine. 22(11). 1321–1329. 122 indexed citations
12.
Louie, Sharon M., Lisa A. Crawford, Roman Camarda, et al.. (2016). GSTP1 Is a Driver of Triple-Negative Breast Cancer Cell Metabolism and Pathogenicity. Cell chemical biology. 23(5). 567–578. 115 indexed citations
13.
Li, Meng, et al.. (2016). Functional annotation of cancer driver genes in breast cancer patient-derived xenografts to identify a novel target for PARP inhibitors.. Journal of Clinical Oncology. 34(15_suppl). e23192–e23192. 1 indexed citations
14.
Caswell‐Jin, Jennifer L., Roman Camarda, Alicia Y. Zhou, et al.. (2015). Multiple breast cancer risk variants are associated with differential transcript isoform expression in tumors. Human Molecular Genetics. 24(25). 7421–7431. 16 indexed citations
15.
Fontaine, Krystal A., Roman Camarda, & Michael Lagunoff. (2014). Vaccinia Virus Requires Glutamine but Not Glucose for Efficient Replication. Journal of Virology. 88(8). 4366–4374. 131 indexed citations
16.
Fontaine, Krystal A., Erica L. Sanchez, Roman Camarda, & Michael Lagunoff. (2014). Dengue Virus Induces and Requires Glycolysis for Optimal Replication. Journal of Virology. 89(4). 2358–2366. 253 indexed citations
17.
Delgado, Tracie, Erica L. Sanchez, Roman Camarda, & Michael Lagunoff. (2012). Global Metabolic Profiling of Infection by an Oncogenic Virus: KSHV Induces and Requires Lipogenesis for Survival of Latent Infection. PLoS Pathogens. 8(8). e1002866–e1002866. 144 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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