Joanna Stanicka

675 total citations
10 papers, 412 citations indexed

About

Joanna Stanicka is a scholar working on Molecular Biology, Hematology and Immunology. According to data from OpenAlex, Joanna Stanicka has authored 10 papers receiving a total of 412 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Hematology and 4 papers in Immunology. Recurrent topics in Joanna Stanicka's work include Acute Myeloid Leukemia Research (4 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (3 papers) and Immune cells in cancer (3 papers). Joanna Stanicka is often cited by papers focused on Acute Myeloid Leukemia Research (4 papers), Neutrophil, Myeloperoxidase and Oxidative Mechanisms (3 papers) and Immune cells in cancer (3 papers). Joanna Stanicka collaborates with scholars based in Ireland, Germany and United States. Joanna Stanicka's co-authors include Thomas G. Cotter, John F. Woolley, Jennifer N. Moloney, Shane V. Hegarty, Rosemary O’Connor, Bryan C. Dickinson, Christopher J. Chang, Aideen M. Sullivan, Gerard W. O’Keeffe and Florence O. McCarthy and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Oncogene.

In The Last Decade

Joanna Stanicka

10 papers receiving 403 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Joanna Stanicka Ireland 9 232 69 64 48 46 10 412
Sora Mun South Korea 13 181 0.8× 39 0.6× 29 0.5× 62 1.3× 75 1.6× 30 459
Christian B. Billesbølle United States 9 232 1.0× 17 0.2× 130 2.0× 45 0.9× 19 0.4× 12 504
Vikas V. Dukhande United States 15 378 1.6× 30 0.4× 40 0.6× 61 1.3× 23 0.5× 41 615
Baiyan Wang China 12 323 1.4× 126 1.8× 82 1.3× 123 2.6× 38 0.8× 27 596
Luying Yang China 14 197 0.8× 45 0.7× 35 0.5× 112 2.3× 50 1.1× 37 588
Sandra Vorlová Germany 11 404 1.7× 65 0.9× 33 0.5× 100 2.1× 11 0.2× 15 698
Greg A. Timblin United States 8 166 0.7× 127 1.8× 11 0.2× 38 0.8× 43 0.9× 11 411
Gregory P. Holmes‐Hampton United States 15 321 1.4× 13 0.2× 110 1.7× 44 0.9× 44 1.0× 39 576
Robert Karisch Canada 8 360 1.6× 105 1.5× 27 0.4× 27 0.6× 17 0.4× 10 540

Countries citing papers authored by Joanna Stanicka

Since Specialization
Citations

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

Fields of papers citing papers by Joanna Stanicka

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Joanna Stanicka

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

All Works

10 of 10 papers shown
1.
Hegarty, Shane V. & Joanna Stanicka. (2022). K+/Cl co-transporter-2 upmodulation: a multi-modal therapy to treat spinal cord injury. Neural Regeneration Research. 17(9). 1984–1984. 3 indexed citations
3.
Stanicka, Joanna, Órla T. Cox, Michael F. Coleman, et al.. (2018). FES-related tyrosine kinase activates the insulin-like growth factor-1 receptor at sites of cell adhesion. Oncogene. 37(23). 3131–3150. 23 indexed citations
4.
Moloney, Jennifer N., Ashok Kumar Jayavelu, Joanna Stanicka, et al.. (2017). Nuclear membrane-localised NOX4D generates pro-survival ROS in FLT3-ITD-expressing AML. Oncotarget. 8(62). 105440–105457. 13 indexed citations
5.
Hegarty, Shane V., et al.. (2016). A Small Molecule Activator of p300/CBP Histone Acetyltransferase Promotes Survival and Neurite Growth in a Cellular Model of Parkinson’s Disease. Neurotoxicity Research. 30(3). 510–520. 30 indexed citations
6.
Moloney, Jennifer N., Joanna Stanicka, & Thomas G. Cotter. (2016). Subcellular localization of the FLT3-ITD oncogene plays a significant role in the production of NOX- and p22phox-derived reactive oxygen species in acute myeloid leukemia. Leukemia Research. 52. 34–42. 38 indexed citations
7.
Stanicka, Joanna, et al.. (2015). NADPH Oxidase-generated Hydrogen Peroxide Induces DNA Damage in Mutant FLT3-expressing Leukemia Cells. Journal of Biological Chemistry. 290(15). 9348–9361. 73 indexed citations
8.
O’Sullivan, E., et al.. (2014). Ellipticine derivative induces potent cytostatic effect in acute myeloid leukaemia cells. Investigational New Drugs. 32(6). 1113–1122. 17 indexed citations
9.
Woolley, John F., Joanna Stanicka, & Thomas G. Cotter. (2013). Recent advances in reactive oxygen species measurement in biological systems. Trends in Biochemical Sciences. 38(11). 556–565. 148 indexed citations
10.
Woolley, John F., et al.. (2012). H2O2 Production Downstream of FLT3 Is Mediated by p22phox in the Endoplasmic Reticulum and Is Required for STAT5 Signalling. PLoS ONE. 7(7). e34050–e34050. 47 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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