Beata Greb‐Markiewicz

448 total citations
20 papers, 274 citations indexed

About

Beata Greb‐Markiewicz is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Genetics. According to data from OpenAlex, Beata Greb‐Markiewicz has authored 20 papers receiving a total of 274 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 6 papers in Cellular and Molecular Neuroscience and 3 papers in Genetics. Recurrent topics in Beata Greb‐Markiewicz's work include Neurobiology and Insect Physiology Research (5 papers), RNA Research and Splicing (5 papers) and RNA modifications and cancer (4 papers). Beata Greb‐Markiewicz is often cited by papers focused on Neurobiology and Insect Physiology Research (5 papers), RNA Research and Splicing (5 papers) and RNA modifications and cancer (4 papers). Beata Greb‐Markiewicz collaborates with scholars based in Poland, United States and Germany. Beata Greb‐Markiewicz's co-authors include W Peczyńska-Czoch, Jolanta Bryjak, Andrzej Ożyhar, Mirosław Zarębski, Vincent Parissi, Jurek Dobrucki, Christina Ernst, Wai‐Lung Ng, Vladimir N. Uversky and Jakub Godlewski and has published in prestigious journals such as Journal of Biological Chemistry, PLoS ONE and Scientific Reports.

In The Last Decade

Beata Greb‐Markiewicz

18 papers receiving 268 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Beata Greb‐Markiewicz Poland 9 161 72 40 35 30 20 274
Sougata Sinha Ray India 10 205 1.3× 39 0.5× 16 0.4× 14 0.4× 15 0.5× 13 336
Luis Briseño-Roa France 10 279 1.7× 85 1.2× 20 0.5× 24 0.7× 47 1.6× 14 516
Xiaoyang Li China 13 323 2.0× 98 1.4× 15 0.4× 7 0.2× 24 0.8× 26 461
Takako Iida Japan 11 217 1.3× 192 2.7× 24 0.6× 170 4.9× 35 1.2× 14 626
Taylor H. Nguyen United States 8 353 2.2× 26 0.4× 22 0.6× 10 0.3× 51 1.7× 15 436
Ryo Murakami Japan 13 353 2.2× 73 1.0× 12 0.3× 6 0.2× 64 2.1× 46 550
Brian P. Landry United States 9 492 3.1× 124 1.7× 124 3.1× 16 0.5× 108 3.6× 9 621
Vadim Schmatchenko Russia 9 240 1.5× 173 2.4× 7 0.2× 20 0.6× 40 1.3× 9 382
Rosa Morra United Kingdom 10 260 1.6× 26 0.4× 12 0.3× 8 0.2× 73 2.4× 15 363
Yvonne Nyathi United Kingdom 10 398 2.5× 112 1.6× 9 0.2× 6 0.2× 47 1.6× 13 506

Countries citing papers authored by Beata Greb‐Markiewicz

Since Specialization
Citations

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

Fields of papers citing papers by Beata Greb‐Markiewicz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Beata Greb‐Markiewicz. 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 Beata Greb‐Markiewicz. The network helps show where Beata Greb‐Markiewicz may publish in the future.

Co-authorship network of co-authors of Beata Greb‐Markiewicz

This figure shows the co-authorship network connecting the top 25 collaborators of Beata Greb‐Markiewicz. A scholar is included among the top collaborators of Beata Greb‐Markiewicz 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 Beata Greb‐Markiewicz. Beata Greb‐Markiewicz 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.
Greb‐Markiewicz, Beata, et al.. (2025). An attempt to explain what intrinsically disordered TCF4 does in its spare time when PTHS-related mutations prevent it from doing its job. Cell Communication and Signaling. 23(1). 258–258.
2.
Niedźwiecka, Anna, et al.. (2025). The molecular properties of the bHLH TCF4 protein as an intrinsically disordered hub transcription factor. Cell Communication and Signaling. 23(1). 154–154. 1 indexed citations
3.
Greb‐Markiewicz, Beata, et al.. (2025). Neutrophil extracellular traps and cannabinoids: potential in cancer metastasis. Frontiers in Oncology. 15. 1595913–1595913. 1 indexed citations
4.
Greb‐Markiewicz, Beata, et al.. (2023). Beauveria bassiana Water Extracts’ Effect on the Growth of Wheat. Plants. 12(2). 326–326. 3 indexed citations
5.
Ernst, Christina, et al.. (2022). Phase separation in viral infections. Trends in Microbiology. 30(12). 1217–1231. 49 indexed citations
6.
Uversky, Vladimir N., et al.. (2021). The Participation of the Intrinsically Disordered Regions of the bHLH-PAS Transcription Factors in Disease Development. International Journal of Molecular Sciences. 22(6). 2868–2868. 5 indexed citations
7.
Zarębski, Mirosław, et al.. (2021). The method utilized to purify the SARS-CoV-2 N protein can affect its molecular properties. International Journal of Biological Macromolecules. 188. 391–403. 11 indexed citations
8.
Taube, Michał, Maciej Kozak, Mark J. Bostock, et al.. (2020). The intrinsically disordered region of GCE protein adopts a more fixed structure by interacting with the LBD of the nuclear receptor FTZ-F1. Cell Communication and Signaling. 18(1). 180–180. 6 indexed citations
9.
Greb‐Markiewicz, Beata, et al.. (2019). The Significance of the Intrinsically Disordered Regions for the Functions of the bHLH Transcription Factors. International Journal of Molecular Sciences. 20(21). 5306–5306. 30 indexed citations
10.
Greb‐Markiewicz, Beata, et al.. (2019). The subcellular localization of bHLH transcription factor TCF4 is mediated by multiple nuclear localization and nuclear export signals. Scientific Reports. 9(1). 15629–15629. 9 indexed citations
11.
Greb‐Markiewicz, Beata, et al.. (2019). bHLH–PAS Proteins: Their Structure and Intrinsic Disorder. International Journal of Molecular Sciences. 20(15). 3653–3653. 27 indexed citations
12.
Greb‐Markiewicz, Beata, et al.. (2019). Subcellular Localization Signals of bHLH-PAS Proteins: Their Significance, Current State of Knowledge and Future Perspectives. International Journal of Molecular Sciences. 20(19). 4746–4746. 8 indexed citations
13.
Greb‐Markiewicz, Beata, Mirosław Zarębski, & Andrzej Ożyhar. (2018). Multiple sequences orchestrate subcellular trafficking of neuronal PAS domain–containing protein 4 (NPAS4). Journal of Biological Chemistry. 293(29). 11255–11270. 7 indexed citations
14.
Taube, Michał, et al.. (2016). Intrinsic Disorder of the C-Terminal Domain of Drosophila Methoprene-Tolerant Protein. PLoS ONE. 11(9). e0162950–e0162950. 6 indexed citations
15.
Greb‐Markiewicz, Beata, et al.. (2015). Mapping of the Sequences Directing Localization of the Drosophila Germ Cell-Expressed Protein (GCE). PLoS ONE. 10(7). e0133307–e0133307. 10 indexed citations
16.
Greb‐Markiewicz, Beata, et al.. (2011). Sequences that direct subcellular traffic of the Drosophila methoprene-tolerant protein (MET) are located predominantly in the PAS domains. Molecular and Cellular Endocrinology. 345(1-2). 16–26. 17 indexed citations
17.
Greb‐Markiewicz, Beata, et al.. (2008). The variety of complexes formed by EcR and Usp nuclear receptors in the nuclei of living cells. Molecular and Cellular Endocrinology. 294(1-2). 45–51. 9 indexed citations
18.
Greb‐Markiewicz, Beata, Torsten Fauth, & Margarethe Spindler‐Barth. (2005). Ligand binding is without effect on complex formation of the ligand binding domain of the ecdysone receptor (EcR). Archives of Insect Biochemistry and Physiology. 59(1). 1–11. 2 indexed citations
19.
Bryjak, Jolanta, et al.. (2002). Immobilization of wood-rotting fungi laccases on modified cellulose and acrylic carriers. Process Biochemistry. 37(12). 1387–1394. 73 indexed citations
20.

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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