Kacper Żukowski

1.1k total citations
54 papers, 660 citations indexed

About

Kacper Żukowski is a scholar working on Genetics, Animal Science and Zoology and Cancer Research. According to data from OpenAlex, Kacper Żukowski has authored 54 papers receiving a total of 660 indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Genetics, 15 papers in Animal Science and Zoology and 14 papers in Cancer Research. Recurrent topics in Kacper Żukowski's work include Genetic and phenotypic traits in livestock (32 papers), Genetic Mapping and Diversity in Plants and Animals (25 papers) and Cancer-related molecular mechanisms research (12 papers). Kacper Żukowski is often cited by papers focused on Genetic and phenotypic traits in livestock (32 papers), Genetic Mapping and Diversity in Plants and Animals (25 papers) and Cancer-related molecular mechanisms research (12 papers). Kacper Żukowski collaborates with scholars based in Poland, United Kingdom and Netherlands. Kacper Żukowski's co-authors include Katarzyna Ropka‐Molik, Katarzyna Piórkowska, Artur Gurgul, M. Tyra, Maria Oczkowicz, Monika Bugno‐Poniewierska, Tomasz Szmatoła, R. Eckert, Igor Jasielczuk and Katarzyna Połtowicz and has published in prestigious journals such as International Journal of Molecular Sciences, Infection and Immunity and Gene.

In The Last Decade

Kacper Żukowski

52 papers receiving 647 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kacper Żukowski Poland 14 408 240 164 157 56 54 660
Youji Ma China 13 326 0.8× 248 1.0× 214 1.3× 59 0.4× 45 0.8× 47 589
Zongjun Yin China 14 289 0.7× 279 1.2× 277 1.7× 92 0.6× 34 0.6× 81 683
Shouzhi Wang China 14 324 0.8× 226 0.9× 117 0.7× 194 1.2× 58 1.0× 39 625
Catherine Collette Sweden 3 625 1.5× 302 1.3× 156 1.0× 138 0.9× 63 1.1× 3 851
Zengkui Lu China 18 448 1.1× 253 1.1× 263 1.6× 142 0.9× 52 0.9× 65 754
Xiujin Li China 15 223 0.5× 236 1.0× 135 0.8× 125 0.8× 16 0.3× 49 627
Martin Braunschweig Switzerland 12 815 2.0× 486 2.0× 207 1.3× 245 1.6× 80 1.4× 23 1.2k
Tatsuo Fujita Japan 12 359 0.9× 233 1.0× 125 0.8× 65 0.4× 35 0.6× 25 594
Takatoshi Kojima Japan 13 360 0.9× 171 0.7× 83 0.5× 116 0.7× 43 0.8× 42 739
Yuyun Xing China 10 317 0.8× 113 0.5× 105 0.6× 82 0.5× 21 0.4× 29 428

Countries citing papers authored by Kacper Żukowski

Since Specialization
Citations

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

Fields of papers citing papers by Kacper Żukowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kacper Żukowski

This figure shows the co-authorship network connecting the top 25 collaborators of Kacper Żukowski. A scholar is included among the top collaborators of Kacper Żukowski 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 Kacper Żukowski. Kacper Żukowski 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
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Piórkowska, Katarzyna, et al.. (2025). Identification of Genes Related to Fat Deposition as Candidates for ER Stress Based on Combined RNA-ATAC Sequencing Analysis. Annals of Animal Science. 25(2). 585–595. 1 indexed citations
3.
Bagnicka, Emilia, et al.. (2023). The association of gene polymorphisms with milk production and mastitis resistance phenotypic traits in dairy cattle. Annals of Animal Science. 23(2). 419–430. 3 indexed citations
4.
Czarnik, Urszula, et al.. (2021). Association of bovine CXCL8 polymorphism with clinical mastitis and fertility trait in Polish HF cattle. 3(2). 9–9. 1 indexed citations
5.
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Piórkowska, Katarzyna, Katarzyna Ropka‐Molik, Magdalena Szyndler‐Nędza, et al.. (2020). Evaluation of SCD, ACACA and FASN Mutations: Effects on Pork Quality and Other Production Traits in Pigs Selected Based on RNA-Seq Results. Animals. 10(1). 123–123. 30 indexed citations
7.
Piórkowska, Katarzyna, Kacper Żukowski, Katarzyna Połtowicz, et al.. (2020). Identification of candidate genes and regulatory factors related to growth rate through hypothalamus transcriptome analyses in broiler chickens. BMC Genomics. 21(1). 509–509. 12 indexed citations
8.
Piórkowska, Katarzyna, Kacper Żukowski, M. Tyra, et al.. (2019). The Pituitary Transcriptional Response Related to Feed Conversion in Pigs. Genes. 10(9). 712–712. 10 indexed citations
9.
Żukowski, Kacper, et al.. (2019). Polymorphism of the Myostatin (MSTN) Gene in Landes and Kielecka Geese Breeds. Animals. 10(1). 10–10. 6 indexed citations
10.
Piórkowska, Katarzyna, et al.. (2018). The effect of QTL-rich region polymorphisms identified by targeted DNA-seq on pig production traits. Molecular Biology Reports. 45(3). 361–371. 5 indexed citations
11.
Piórkowska, Katarzyna, Kacper Żukowski, Katarzyna Ropka‐Molik, M. Tyra, & Artur Gurgul. (2018). A comprehensive transcriptome analysis of skeletal muscles in two Polish pig breeds differing in fat and meat quality traits. Genetics and Molecular Biology. 41(1). 125–136. 41 indexed citations
12.
Ropka‐Molik, Katarzyna, Monika Stefaniuk‐Szmukier, Kacper Żukowski, et al.. (2017). Transcriptome profiling of Arabian horse blood during training regimens. BMC Genetics. 18(1). 31–31. 24 indexed citations
13.
Pokorska, Joanna, et al.. (2016). Single nucleotide polymorphisms in the CXCR1 gene and its association with clinical mastitis incidence in Polish Holstein-Friesian cows. Genetics and Molecular Research. 15(2). 11 indexed citations
14.
Gurgul, Artur, Igor Jasielczuk, Tomasz Szmatoła, et al.. (2015). Genome-wide characteristics of copy number variation in Polish Holstein and Polish Red cattle using SNP genotyping assay. Genetica. 143(2). 145–155. 11 indexed citations
15.
Żukowski, Kacper, et al.. (2013). SCD1 SNP in relation to breeding value of milk production traits in Polish Holstein-Friesian cows. 12(1). 3 indexed citations
16.
Piórkowska, Katarzyna, Katarzyna Ropka‐Molik, Maria Oczkowicz, M. Różycki, & Kacper Żukowski. (2013). Association study of PIT1 and GHRH SNPs with economically important traits in pigs of three breeds reared in Poland.. Animal Science Papers and Reports. 31(4). 303–314. 8 indexed citations
17.
Żukowski, Kacper, et al.. (2013). SLC27A1 SNPs in relation to breeding value of milk production traits in Polish Holstein-Friesian cows. Animal Science Papers and Reports. 31(4). 273–279. 1 indexed citations
18.
Gurgul, Artur, Kacper Żukowski, Klaudia Pawlina‐Tyszko, et al.. (2013). The Evaluation of Bovine SNP50 BeadChip Assay Performance in Polish Red Cattle Breed. Folia Biologica. 61(3). 173–176. 2 indexed citations
19.
Oczkowicz, Maria, et al.. (2012). Effect of IGF2 intron3-g.3072G>A on intramuscular fat (IMF) content in pigs raised in Poland. Livestock Science. 149(3). 301–304. 14 indexed citations
20.
Szyda, Joanna, et al.. (2009). Incorporation of correlation between SNPs into the genomic evaluation model. Bulletin - International Bull Evaluation Service/Interbull bulletin. 193. 3 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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