Daniel J. Garama

955 total citations
21 papers, 707 citations indexed

About

Daniel J. Garama is a scholar working on Molecular Biology, Oncology and Immunology. According to data from OpenAlex, Daniel J. Garama has authored 21 papers receiving a total of 707 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 8 papers in Oncology and 4 papers in Immunology. Recurrent topics in Daniel J. Garama's work include Cytokine Signaling Pathways and Interactions (5 papers), interferon and immune responses (4 papers) and Epigenetics and DNA Methylation (3 papers). Daniel J. Garama is often cited by papers focused on Cytokine Signaling Pathways and Interactions (5 papers), interferon and immune responses (4 papers) and Epigenetics and DNA Methylation (3 papers). Daniel J. Garama collaborates with scholars based in Australia, New Zealand and Canada. Daniel J. Garama's co-authors include Daniel J. Gough, Chamira Dilanka Fernando, Jesse J. Balic, Christine L. White, Alan Carne, W. Samantha N. Jayasekara, Fernando J. Rossello, Katherine A. Fitzgerald, Dominic De Nardo and Maher Abdul‐Hay and has published in prestigious journals such as Science, Nature Communications and Molecular Cell.

In The Last Decade

Daniel J. Garama

20 papers receiving 704 citations

Peers

Daniel J. Garama

ONCOL

IMMUN

PFM

Kati Talvinen Finland

Chengrong Lu China

Jeonghun Yeom South Korea

Tammy Flagg United States

Marjo de Graauw Netherlands

Xin Cai China

Christian Rohlff United States

Jennifer Yeung United States

Andrey Kropotov Russia

Kati Talvinen Finland

Daniel J. Garama

462 ×1.2

197 ×0.9

ONCOL

76 ×0.6

IMMUN

160 ×1.4

38 ×0.6

PFM

Citations per year, relative to Daniel J. Garama Daniel J. Garama (= 1×) peers Kati Talvinen

Countries citing papers authored by Daniel J. Garama

Since Specialization

Citations

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

Fields of papers citing papers by Daniel J. Garama

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel J. Garama

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

All Works

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20 of 20 papers shown

Costacurta, Matteo, Jarrod J. Sandow, Belinda Maher, et al.. (2024). Mapping the IM i D ‐dependent cereblon interactome using B io ID ‐proximity labelling. FEBS Journal. 291(22). 4892–4912. 4 indexed citations

Jayasekara, W. Samantha N., Eveline D. de Geus, Nicole A. de Weerd, et al.. (2024). A STAT3–STING–IFN axis controls the metastatic spread of small cell lung cancer. Nature Immunology. 25(12). 2259–2269. 12 indexed citations

Jayasekara, W. Samantha N., Maija R.J. Kohonen‐Corish, Wendy A. Cooper, et al.. (2023). A STAT3 protein complex required for mitochondrial mRNA stability and cancer. Cell Reports. 42(9). 113033–113033. 14 indexed citations

Garama, Daniel J., Muhammad Alamgeer, Michael DeVeer, et al.. (2023). MYC drives platinum resistant SCLC that is overcome by the dual PI3K-HDAC inhibitor fimepinostat. Journal of Experimental & Clinical Cancer Research. 42(1). 100–100. 21 indexed citations

Josephs, Tracy M., Matthew J. Belousoff, Yi-Lynn Liang, et al.. (2021). Structure and dynamics of the CGRP receptor in apo and peptide-bound forms. Science. 372(6538). 63 indexed citations

Doan, Anh, Daniel J. Garama, Marius Dannappel, et al.. (2021). MED12 and BRD4 cooperate to sustain cancer growth upon loss of mediator kinase. Molecular Cell. 82(1). 123–139.e7. 21 indexed citations

Jayasekara, W. Samantha N., Dhilshan Jayasinghe, Anette Szczepny, et al.. (2021). Lineage-restricted neoplasia driven by Myc defaults to small cell lung cancer when combined with loss of p53 and Rb in the airway epithelium. Oncogene. 41(1). 138–145. 19 indexed citations

Balic, Jesse J., Kevin Luu, W. Samantha N. Jayasekara, et al.. (2020). STAT3 serine phosphorylation is required for TLR4 metabolic reprogramming and IL-1β expression. Nature Communications. 11(1). 3816–3816. 101 indexed citations

Balic, Jesse J., Daniel J. Garama, Mohamed I. Saad, et al.. (2019). Serine-Phosphorylated STAT3 Promotes Tumorigenesis via Modulation of RNA Polymerase Transcriptional Activity. Cancer Research. 79(20). 5272–5287. 28 indexed citations

10.

Szczepny, Anette, Lisa D. McKenzie, W. Samantha N. Jayasekara, et al.. (2018). The tumor suppressor Hic1 maintains chromosomal stability independent of Tp53. Oncogene. 37(14). 1939–1948. 16 indexed citations

11.

Garama, Daniel J., et al.. (2018). Carotenoid composition of a New Zealand (Evechinus chloroticus) and an Australian (Heliocidaris erythrogramma) sea urchin in relation to gonad colour. Aquaculture Research. 49(8). 2751–2762.

12.

Sandow, Jarrod J., Adam Rainczuk, Giuseppe Infusini, et al.. (2018). Discovery and Validation of Novel Protein Biomarkers in Ovarian Cancer Patient Urine. PROTEOMICS - CLINICAL APPLICATIONS. 12(3). e1700135–e1700135. 41 indexed citations

13.

Lee, William, Xin Sun, Te‐Sha Tsai, et al.. (2017). Mitochondrial DNA haplotypes induce differential patterns of DNA methylation that result in differential chromosomal gene expression patterns. Cell Death Discovery. 3(1). 17062–17062. 38 indexed citations

14.

Garama, Daniel J., Christine L. White, Jesse J. Balic, & Daniel J. Gough. (2016). Mitochondrial STAT3: Powering up a potent factor. Cytokine. 87. 20–25. 57 indexed citations

15.

Garama, Daniel J., Tiffany J. Harris, Christine L. White, et al.. (2015). A Synthetic Lethal Interaction between Glutathione Synthesis and Mitochondrial Reactive Oxygen Species Provides a Tumor-Specific Vulnerability Dependent on STAT3. Molecular and Cellular Biology. 35(21). 3646–3656. 48 indexed citations

16.

Garama, Daniel J., et al.. (2014). The transcriptome of the NZ endemic sea urchin Kina (Evechinus chloroticus). BMC Genomics. 15(1). 45–45. 19 indexed citations

17.

Garama, Daniel J., et al.. (2014). A Novel Fatty Acid-Binding Protein-Like Carotenoid-Binding Protein from the Gonad of the New Zealand Sea Urchin Evechinus chloroticus. PLoS ONE. 9(9). e106465–e106465. 9 indexed citations

18.

Garama, Daniel J., et al.. (2012). Carotenoid-binding proteins; accessories to carotenoid function.. Acta Biochimica Polonica. 59(1). 163–5. 14 indexed citations

19.

Garama, Daniel J., Phil Bremer, & Alan Carne. (2012). Extraction and analysis of carotenoids from the New Zealand sea urchin Evechinus chloroticus gonads.. Acta Biochimica Polonica. 59(1). 83–5. 12 indexed citations

20.

Turner, Paul R., et al.. (2007). Production, purification and functional validation of human secreted amyloid precursor proteins for use as neuropharmacological reagents. Journal of Neuroscience Methods. 164(1). 68–74. 20 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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