Beata Kieć‐Wilk

3.2k total citations
123 papers, 2.3k citations indexed

About

Beata Kieć‐Wilk is a scholar working on Endocrinology, Diabetes and Metabolism, Physiology and Molecular Biology. According to data from OpenAlex, Beata Kieć‐Wilk has authored 123 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Endocrinology, Diabetes and Metabolism, 43 papers in Physiology and 42 papers in Molecular Biology. Recurrent topics in Beata Kieć‐Wilk's work include Diabetes Management and Research (22 papers), Adipose Tissue and Metabolism (18 papers) and Diabetes and associated disorders (15 papers). Beata Kieć‐Wilk is often cited by papers focused on Diabetes Management and Research (22 papers), Adipose Tissue and Metabolism (18 papers) and Diabetes and associated disorders (15 papers). Beata Kieć‐Wilk collaborates with scholars based in Poland, United Kingdom and Spain. Beata Kieć‐Wilk's co-authors include A. Dembińska-Kieć, Maciej T. Małecki, Hannu Mykkänen, Otto Mykkänen, Barbara Zapała, Anna Polus, Urszula Raźny, José López‐Miranda, Helen M. Roche and Catherine Defoort and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and American Journal of Clinical Nutrition.

In The Last Decade

Beata Kieć‐Wilk

119 papers receiving 2.3k 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 Kieć‐Wilk Poland 27 766 748 557 338 324 123 2.3k
Chi Wai Lau Hong Kong 34 828 1.1× 1.3k 1.7× 554 1.0× 224 0.7× 373 1.2× 82 3.6k
Antonio García‐Ríos Spain 29 875 1.1× 492 0.7× 405 0.7× 407 1.2× 347 1.1× 81 2.3k
Chang Ling Sia United States 20 621 0.8× 670 0.9× 420 0.8× 192 0.6× 478 1.5× 28 2.2k
Celia Bañuls Spain 31 788 1.0× 1.3k 1.7× 581 1.0× 205 0.6× 482 1.5× 102 3.4k
Kazushige Dobashi Japan 29 667 0.9× 663 0.9× 451 0.8× 299 0.9× 459 1.4× 93 2.6k
Rennan Feng China 32 735 1.0× 883 1.2× 494 0.9× 184 0.5× 733 2.3× 66 2.7k
Nalini Santanam United States 36 527 0.7× 725 1.0× 321 0.6× 385 1.1× 333 1.0× 102 3.6k
Christian Darimont Switzerland 28 1.3k 1.7× 1.2k 1.6× 480 0.9× 256 0.8× 556 1.7× 56 2.8k
Elena M. Yubero‐Serrano Spain 36 1.1k 1.4× 1.0k 1.4× 468 0.8× 520 1.5× 379 1.2× 111 3.3k
Sanaa Abuaysheh United States 21 759 1.0× 639 0.9× 857 1.5× 200 0.6× 584 1.8× 37 2.5k

Countries citing papers authored by Beata Kieć‐Wilk

Since Specialization
Citations

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

Fields of papers citing papers by Beata Kieć‐Wilk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Beata Kieć‐Wilk

This figure shows the co-authorship network connecting the top 25 collaborators of Beata Kieć‐Wilk. A scholar is included among the top collaborators of Beata Kieć‐Wilk 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 Kieć‐Wilk. Beata Kieć‐Wilk 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.
Żuber, Zbigniew, et al.. (2023). Diagnosis and Management of Mucopolysaccharidosis Type II (Hunter Syndrome) in Poland. Biomedicines. 11(6). 1668–1668. 4 indexed citations
2.
Matejko, Bartłomiej, Beata Kieć‐Wilk, Katarzyna Cyranka, et al.. (2023). One-Year Follow-Up of Advanced Hybrid Closed-Loop System in Adults with Type 1 Diabetes Previously Naive to Diabetes Technology: The Effect of Switching to a Calibration-Free Sensor. Diabetes Technology & Therapeutics. 25(8). 554–558. 13 indexed citations
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Mrozińska, Sandra, Przemysław Kapusta, Tomasz Gosiewski, et al.. (2021). The Gut Microbiota Profile According to Glycemic Control in Type 1 Diabetes Patients Treated with Personal Insulin Pumps. Microorganisms. 9(1). 155–155. 19 indexed citations
7.
Polus, Anna, et al.. (2021). Gene expression with corresponding pathways analysis in Gaucher disease. Experimental and Molecular Pathology. 123. 104679–104679. 3 indexed citations
8.
Trybus, Marek, Monika Kolanowska, Mateusz Koziej, et al.. (2021). BMPR1B gene in brachydactyly type 2–A family with de novo R486W mutation and a disease phenotype. Molecular Genetics & Genomic Medicine. 9(3). e1594–e1594. 3 indexed citations
9.
Matejko, Bartłomiej, Łukasz Tota, Sandra Mrozińska, et al.. (2020). Predictors of the maximal oxygen consumption in adult patients with type 1 diabetes treated with personal insulin pumps. Journal of Diabetes Investigation. 12(8). 1377–1385. 5 indexed citations
10.
Matejko, Bartłomiej, et al.. (2019). Assessment of selected food intake frequency in patients with type 1 diabetes treated with personal insulin pumps. Roczniki Państwowego Zakładu Higieny. 70(3). 259–265. 3 indexed citations
11.
Matejko, Bartłomiej, et al.. (2018). Basal Insulin Dose in Adults with Type 1 Diabetes Mellitus on Insulin Pumps in Real-Life Clinical Practice: A Single-Center Experience. SHILAP Revista de lepidopterología. 2018. 1–5. 5 indexed citations
12.
Szopa, Magdalena, Agnieszka H. Ludwig‐Słomczyńska, Jan Skupień, et al.. (2015). Genetic testing for monogenic diabetes using targeted next-generation sequencing in patients with maturity-onset diabetes of the young. Polskie Archiwum Medycyny Wewnętrznej. 125(11). 845–851. 33 indexed citations
13.
Paniagua, Juan Antonio Pacheco, Pablo Pérez‐Martínez, Ingrid M.F. Gjelstad, et al.. (2011). A low-fat high-carbohydrate diet supplemented with long-chain n-3 PUFA reduces the risk of the metabolic syndrome. Atherosclerosis. 218(2). 443–450. 49 indexed citations
14.
Pérez‐Martínez, Pablo, Javier Delgado‐Lista, Antonio García‐Ríos, et al.. (2011). Calpain-10 interacts with plasma saturated fatty acid concentrations to influence insulin resistance in individuals with the metabolic syndrome. American Journal of Clinical Nutrition. 93(5). 1136–1141. 26 indexed citations
15.
Dimitrow, Paweł Petkow, et al.. (2011). Phospholamban gene mutations are not associated with hypertrophic cardiomyopathy in patients from southern Poland.. PubMed. 69(2). 134–7. 1 indexed citations
16.
Phillips, Catherine M., Louisa Goumidi, Sandrine Bertrais, et al.. (2010). Gene-nutrient interactions with dietary fat modulate the association between genetic variation of the ACSL1 gene and metabolic syndrome. Journal of Lipid Research. 51(7). 1793–1800. 50 indexed citations
17.
Kieć‐Wilk, Beata, et al.. (2009). [Role of impaired calcium homeostasis in the development of cardiac hypertrophy].. PubMed. 67(12). 1396–402. 1 indexed citations
18.
Kieć‐Wilk, Beata, Wojciech Dudek, & A. Dembińska-Kieć. (2006). Nutrigenomics, angiogenesis and obesity. 12(4). 141–148. 2 indexed citations
19.
Kieć‐Wilk, Beata, et al.. (2005). β-Carotene stimulates chemotaxis of human endothelial progenitor cells. Clinical Chemistry and Laboratory Medicine (CCLM). 43(5). 488–98. 15 indexed citations
20.
Kieć‐Wilk, Beata, et al.. (2002). Correlation of the -3826A >G polymorphism in the promoter of the uncoupling protein 1 gene with obesity and metabolic disorders in obese families from southern Poland.. PubMed. 53(3). 477–90. 41 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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