Daniel P. Camarco

547 total citations
21 papers, 415 citations indexed

About

Daniel P. Camarco is a scholar working on Oncology, Molecular Biology and Organic Chemistry. According to data from OpenAlex, Daniel P. Camarco has authored 21 papers receiving a total of 415 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Oncology, 8 papers in Molecular Biology and 5 papers in Organic Chemistry. Recurrent topics in Daniel P. Camarco's work include interferon and immune responses (5 papers), Cytokine Signaling Pathways and Interactions (5 papers) and Protein Degradation and Inhibitors (4 papers). Daniel P. Camarco is often cited by papers focused on interferon and immune responses (5 papers), Cytokine Signaling Pathways and Interactions (5 papers) and Protein Degradation and Inhibitors (4 papers). Daniel P. Camarco collaborates with scholars based in United States, China and India. Daniel P. Camarco's co-authors include Paul A. Johnston, David A. Close, Yun Hua, John S. Lazo, Billy W. Day, Raghavan Balachandran, Andreas Vogt, Malabika Sen, Feng Shan and Peter Wipf and has published in prestigious journals such as Journal of the American Chemical Society, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Daniel P. Camarco

21 papers receiving 413 citations

Peers

Daniel P. Camarco
Yajing Liu China
Marie‐Line Puiffe France
Somsundaram Chettiar United States
Rósula García‐Navas Spain
Dehua Lu China
Qinhuai Lai China
Scott J. Sauer United States
Elin Lindhagen Sweden
Christy W.S. Tong Hong Kong
Young‐Choon Moon United States
Yajing Liu China
Daniel P. Camarco
Citations per year, relative to Daniel P. Camarco Daniel P. Camarco (= 1×) peers Yajing Liu

Countries citing papers authored by Daniel P. Camarco

Since Specialization
Citations

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

Fields of papers citing papers by Daniel P. Camarco

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel P. Camarco. 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 Daniel P. Camarco. The network helps show where Daniel P. Camarco may publish in the future.

Co-authorship network of co-authors of Daniel P. Camarco

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel P. Camarco. A scholar is included among the top collaborators of Daniel P. Camarco 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 Daniel P. Camarco. Daniel P. Camarco 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.
Lear, Travis, E.H.Y. Chu, Daniel P. Camarco, et al.. (2023). E3 ubiquitin ligase ZBTB25 suppresses beta coronavirus infection through ubiquitination of the main viral protease MPro. Journal of Biological Chemistry. 299(12). 105388–105388. 6 indexed citations
2.
Liu, Yuan, Mads Larsen, Bo Lin, et al.. (2023). Abstract 1805: Identification of a small molecule that induces targeted protein degradation of ADAR1. Cancer Research. 83(7_Supplement). 1805–1805. 1 indexed citations
3.
Chen, Yanwen, Travis Lear, John Evankovich, et al.. (2021). A high-throughput screen for TMPRSS2 expression identifies FDA-approved compounds that can limit SARS-CoV-2 entry. Nature Communications. 12(1). 3907–3907. 58 indexed citations
4.
Lear, Travis, Yanwen Chen, John Evankovich, et al.. (2021). A high throughput screen for TMPRSS2 expression identifies FDA‐approved and clinically advanced compounds that can limit SARS‐CoV‐2 entry. The FASEB Journal. 35(S1). 1 indexed citations
5.
6.
Chen, Yanwen, John Evankovich, Travis Lear, et al.. (2020). A small molecule NRF2 activator BC-1901S ameliorates inflammation through DCAF1/NRF2 axis. Redox Biology. 32. 101485–101485. 20 indexed citations
7.
8.
Shan, Feng, David A. Close, Daniel P. Camarco, & Paul A. Johnston. (2017). High-Content Screening Comparison of Cancer Drug Accumulation and Distribution in Two-Dimensional and Three-Dimensional Culture Models of Head and Neck Cancer. Assay and Drug Development Technologies. 16(1). 27–50. 28 indexed citations
9.
Sen, Malabika, Paul A. Johnston, Netanya Pollock, et al.. (2017). Mechanism of action of selective inhibitors of IL-6 induced STAT3 pathway in head and neck cancer cell lines. PubMed. 10(3). 129–141. 9 indexed citations
10.
Hua, Yun, Daniel P. Camarco, Christopher J. Strock, & Paul A. Johnston. (2017). High Content Positional Biosensor Assay to Screen for Compounds that Prevent or Disrupt Androgen Receptor and Transcription Intermediary Factor 2 Protein-Protein Interactions. Methods in molecular biology. 1683. 211–227. 7 indexed citations
11.
Johnston, Paul A., Malabika Sen, Yun Hua, et al.. (2017). High Content Imaging Assays for IL-6-Induced STAT3 Pathway Activation in Head and Neck Cancer Cell Lines. Methods in molecular biology. 1683. 229–244. 10 indexed citations
12.
Close, David A., et al.. (2017). The Generation of Three-Dimensional Head and Neck Cancer Models for Drug Discovery in 384-Well Ultra-Low Attachment Microplates. Methods in molecular biology. 1683. 355–369. 19 indexed citations
13.
Hua, Yun, et al.. (2016). Reconfiguring the AR-TIF2 Protein–Protein Interaction HCS Assay in Prostate Cancer Cells and Characterizing the Hits from a LOPAC Screen. Assay and Drug Development Technologies. 14(8). 453–477. 10 indexed citations
14.
Johnston, Paul A., Minh M. Nguyen, Javid A. Dar, et al.. (2016). Development and Implementation of a High-Throughput High-Content Screening Assay to Identify Inhibitors of Androgen Receptor Nuclear Localization in Castration-Resistant Prostate Cancer Cells. Assay and Drug Development Technologies. 14(4). 226–239. 24 indexed citations
15.
LaPorte, Matthew G., Raffaele Colombo, Atefeh Garzan, et al.. (2016). Optimization of pyrazole-containing 1,2,4-triazolo-[3,4-b]thiadiazines, a new class of STAT3 pathway inhibitors. Bioorganic & Medicinal Chemistry Letters. 26(15). 3581–3585. 28 indexed citations
16.
Colombo, Raffaele, Zhiyong Wang, Junyan Han, et al.. (2016). Total Synthesis and Biological Evaluation of Tubulysin Analogues. The Journal of Organic Chemistry. 81(21). 10302–10320. 28 indexed citations
17.
Johnston, Paul A., Malabika Sen, Yun Hua, et al.. (2015). HCS Campaign to Identify Selective Inhibitors of IL-6-Induced STAT3 Pathway Activation in Head and Neck Cancer Cell Lines. Assay and Drug Development Technologies. 13(7). 356–376. 24 indexed citations
18.
LaPorte, Matthew G., Feng Zhang, Malabika Sen, et al.. (2014). 2-Guanidinoquinazolines as new inhibitors of the STAT3 pathway. Bioorganic & Medicinal Chemistry Letters. 24(21). 5081–5085. 16 indexed citations
19.
Johnston, Paul A., Malabika Sen, Yun Hua, et al.. (2013). High-Content pSTAT3/1 Imaging Assays to Screen for Selective Inhibitors of STAT3 Pathway Activation in Head and Neck Cancer Cell Lines. Assay and Drug Development Technologies. 12(1). 55–79. 28 indexed citations
20.
Vollmer, Laura L., M. J. Jiménez, Daniel P. Camarco, et al.. (2011). A Simplified Synthesis of Novel Dictyostatin Analogues with In Vitro Activity against Epothilone B–Resistant Cells and Antiangiogenic Activity in Zebrafish Embryos. Molecular Cancer Therapeutics. 10(6). 994–1006. 21 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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