Zbigniew Madeja

3.8k total citations
136 papers, 2.7k citations indexed

About

Zbigniew Madeja is a scholar working on Molecular Biology, Biomedical Engineering and Cell Biology. According to data from OpenAlex, Zbigniew Madeja has authored 136 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Molecular Biology, 20 papers in Biomedical Engineering and 16 papers in Cell Biology. Recurrent topics in Zbigniew Madeja's work include Planarian Biology and Electrostimulation (16 papers), Cellular Mechanics and Interactions (13 papers) and Connexins and lens biology (12 papers). Zbigniew Madeja is often cited by papers focused on Planarian Biology and Electrostimulation (16 papers), Cellular Mechanics and Interactions (13 papers) and Connexins and lens biology (12 papers). Zbigniew Madeja collaborates with scholars based in Poland, United States and United Kingdom. Zbigniew Madeja's co-authors include W Korohoda, Jarosław Czyż, Jolanta Sroka, Marta Michalik, Maria E. Mycielska, Milena Paw, Dawid Wnuk, Ewa Zuba‐Surma, Katarzyna Miękus and Justyna Drukała and has published in prestigious journals such as Circulation, PLoS ONE and Scientific Reports.

In The Last Decade

Zbigniew Madeja

130 papers receiving 2.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Zbigniew Madeja Poland 28 1.4k 436 344 312 297 136 2.7k
Hyung-Seok Kim South Korea 31 1.3k 0.9× 535 1.2× 309 0.9× 175 0.6× 281 0.9× 156 3.2k
Haiyan Chen China 31 1.9k 1.4× 357 0.8× 344 1.0× 205 0.7× 178 0.6× 112 3.2k
Yiping Li China 30 2.6k 1.9× 395 0.9× 550 1.6× 221 0.7× 262 0.9× 107 4.3k
Xiaojing Liu China 33 2.1k 1.5× 330 0.8× 688 2.0× 226 0.7× 310 1.0× 190 3.9k
Zheng Cui China 24 1.7k 1.2× 234 0.5× 352 1.0× 262 0.8× 401 1.4× 67 2.8k
Henrique Girão Portugal 36 2.7k 2.0× 311 0.7× 584 1.7× 416 1.3× 227 0.8× 116 3.8k
Guei‐Sheung Liu Australia 31 1.4k 1.0× 220 0.5× 219 0.6× 183 0.6× 143 0.5× 101 2.9k
Sigrid A. Langhans United States 17 1.0k 0.7× 855 2.0× 229 0.7× 207 0.7× 130 0.4× 39 2.3k
Min Xiong China 31 1.4k 1.0× 224 0.5× 394 1.1× 153 0.5× 187 0.6× 172 3.5k
Yung‐Jen Chuang Taiwan 28 1.1k 0.8× 173 0.4× 374 1.1× 323 1.0× 196 0.7× 91 2.4k

Countries citing papers authored by Zbigniew Madeja

Since Specialization
Citations

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

Fields of papers citing papers by Zbigniew Madeja

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zbigniew Madeja

This figure shows the co-authorship network connecting the top 25 collaborators of Zbigniew Madeja. A scholar is included among the top collaborators of Zbigniew Madeja 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 Zbigniew Madeja. Zbigniew Madeja 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.
Lasota, Sławomir, Paweł Dąbczyński, Zbigniew Madeja, et al.. (2025). Exploring ammonia plasma functionalization of graphenic surfaces: experiments, theoretical insights, and biological implications. Applied Surface Science. 701. 163256–163256.
2.
Jakubowska, Monika A., et al.. (2025). Repurposing BCL2 inhibitors: Venetoclax protects against acinar cell necrosis in acute pancreatitis by promoting apoptosis. Cell Death and Disease. 16(1). 566–566.
3.
4.
Lin, Hui‐Yi, Melody Baddoo, Chindo Hicks, et al.. (2025). Human endogenous retroviruses (HERVs) associated with glioblastoma risk and prognosis. Cancer Gene Therapy. 32(6). 622–632.
5.
Ryszawy, Damian, et al.. (2024). Metabolic reprogramming of poly(morpho)nuclear giant cells determines glioblastoma recovery from doxorubicin-induced stress. Journal of Translational Medicine. 22(1). 757–757. 1 indexed citations
6.
Bobis‐Wozowicz, Sylwia, Elżbieta Karnas, Olga Woźnicka, et al.. (2024). Induced pluripotent stem cell‐derived extracellular vesicles enriched with miR ‐126 induce proangiogenic properties and promote repair of ischemic tissue. The FASEB Journal. 38(2). e23415–e23415. 10 indexed citations
7.
Lasota, Sławomir, et al.. (2023). Functionalization of graphenic surfaces by oxygen plasma toward enhanced wettability and cell adhesion: experiments corroborated by molecular modelling. Journal of Materials Chemistry B. 11(22). 4946–4957. 14 indexed citations
8.
Paw, Milena, Dawid Wnuk, Zbigniew Madeja, & Marta Michalik. (2023). PPARδ Agonist GW501516 Suppresses the TGF-β-Induced Profibrotic Response of Human Bronchial Fibroblasts from Asthmatic Patients. International Journal of Molecular Sciences. 24(9). 7721–7721. 5 indexed citations
9.
Koczurkiewicz, Paulina, Agnieszka Gunia‐Krzyżak, Kamil Piska, et al.. (2021). Cinnamic Acid Derivatives as Cardioprotective Agents against Oxidative and Structural Damage Induced by Doxorubicin. International Journal of Molecular Sciences. 22(12). 6217–6217. 18 indexed citations
10.
Kaczmarzyk, Tomasz, et al.. (2020). Multilineage Differentiation Potential of Human Dental Pulp Stem Cells—Impact of 3D and Hypoxic Environment on Osteogenesis In Vitro. International Journal of Molecular Sciences. 21(17). 6172–6172. 34 indexed citations
11.
12.
Paw, Milena, Dawid Wnuk, Sławomir Lasota, et al.. (2018). Fenofibrate Reduces the Asthma-Related Fibroblast-To-Myofibroblast Transition by TGF-Β/Smad2/3 Signaling Attenuation and Connexin 43-Dependent Phenotype Destabilization. International Journal of Molecular Sciences. 19(9). 2571–2571. 25 indexed citations
13.
Paw, Milena, Izabela Borek, Dawid Wnuk, et al.. (2017). Connexin43 Controls the Myofibroblastic Differentiation of Bronchial Fibroblasts from Patients with Asthma. American Journal of Respiratory Cell and Molecular Biology. 57(1). 100–110. 33 indexed citations
14.
15.
Zuba‐Surma, Ewa, Wojciech Wojakowski, Zbigniew Madeja, & Mariusz Z. Ratajczak. (2012). Stem Cells as a Novel Tool for Drug Screening and Treatment of Degenerative Diseases. Current Pharmaceutical Design. 18(18). 2644–2656. 18 indexed citations
16.
Czyż, Jarosław, et al.. (2012). The role of connexins in prostate cancer promotion and progression. Nature Reviews Urology. 9(5). 274–282. 60 indexed citations
17.
Sroka, Jolanta & Zbigniew Madeja. (2009). Udział reaktywnych form tlenu i reduktazy tioredoksyny w regulacji migracji komórek. Postępy Biochemii. 55(2). 1 indexed citations
18.
Michalik, Marta, I. D. Kosińska, Jolanta Sroka, et al.. (2001). Effects of Trimethyltin on Pinocytosis of Dictyostelium discoideum. Acta Protozoologica. 40(3). 4 indexed citations
19.
Madeja, Zbigniew, Adam Master, Marta Michalik, & Jolanta Sroka. (2001). Contact-mediated acceleration of migration of melanoma B16 cells depends on extracellular calcium ions.. Homo Politicus (Academy of Humanities and Economics in Lodz). 49(3-4). 113–24. 3 indexed citations
20.
Wolnicka-Głubisz, Agnieszka, et al.. (1998). Morphometric analysis of pancreatic carcinoma by computer-assisted image analysis.. PubMed. 46(1-2). 7–15. 2 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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