Kaja A. Wasik

536 total citations
13 papers, 319 citations indexed

About

Kaja A. Wasik is a scholar working on Molecular Biology, Genetics and Plant Science. According to data from OpenAlex, Kaja A. Wasik has authored 13 papers receiving a total of 319 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 5 papers in Genetics and 4 papers in Plant Science. Recurrent topics in Kaja A. Wasik's work include Chromosomal and Genetic Variations (4 papers), Genetic Associations and Epidemiology (3 papers) and Cancer Genomics and Diagnostics (3 papers). Kaja A. Wasik is often cited by papers focused on Chromosomal and Genetic Variations (4 papers), Genetic Associations and Epidemiology (3 papers) and Cancer Genomics and Diagnostics (3 papers). Kaja A. Wasik collaborates with scholars based in United States, United Kingdom and Madagascar. Kaja A. Wasik's co-authors include Gregory J. Hannon, Vasily V. Vagin, Molly Hammell, Ilaria Falciatori, Giorgia Battistoni, James Gurtowski, Matteo Da Ros, Osama E. Demerdash, Jorma Toppari and Oliver Meikar and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Genes & Development.

In The Last Decade

Kaja A. Wasik

10 papers receiving 319 citations

Peers

Kaja A. Wasik

MB

PS

GENET

GPC

ECOLO

Elena A. Kizilova Russia

Yude Wang China

Jin Gao China

Jasmin Zohren United Kingdom

Daniel Gebert Germany

J Mácha Czechia

Åsa Rasmuson-Lestander Sweden

Bridlin Barckmann France

Kadoo Miyaki Japan

P. Lécher France

Elena A. Kizilova Russia

Kaja A. Wasik

173 ×0.7

MB

113 ×1.0

PS

153 ×1.9

GENET

15 ×0.3

GPC

31 ×1.2

ECOLO

Citations per year, relative to Kaja A. Wasik Kaja A. Wasik (= 1×) peers Elena A. Kizilova

Countries citing papers authored by Kaja A. Wasik

Since Specialization

Citations

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

Fields of papers citing papers by Kaja A. Wasik

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kaja A. Wasik. 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 Kaja A. Wasik. The network helps show where Kaja A. Wasik may publish in the future.

Co-authorship network of co-authors of Kaja A. Wasik

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

All Works

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13 of 13 papers shown

1.

Yerges-Armstrong, Laura M., et al.. (2025). Vitamin D status in the Faroe Islands: insights from the FarGen 2 cohort. Scandinavian Journal of Public Health. 54(2). 131–138.

2.

Fox, Keolu, et al.. (2024). Earth Friendly Computation: Applying Indigenous Data Lifecycles in Medical and Sovereign AI. PubMed. 30. 711–716.

3.

Mughal, Mehreen R., Anne‐Katrin Emde, Melissa Hendershott, et al.. (2024). Mid-pass whole-genome sequencing in a Malagasy cohort uncovers body composition associations. Human Genetics and Genomics Advances. 5(4). 100343–100343.

4.

Ranaivoarisoa, Jean Freddy, et al.. (2024). Why community consultation matters in genomic research benefit-sharing models. Genome Research. 34(1). 1–6. 4 indexed citations

5.

Ranaivoarisoa, Jean Freddy, Tristan Pascart, Stephane E. Castel, et al.. (2024). Nothing about us without us: Sharing results with communities that provide genomic data. Cell. 187(20). 5483–5489. 2 indexed citations

6.

Emde, Anne‐Katrin, Amanda Phipps‐Green, Murray Cadzow, et al.. (2021). Mid-pass whole genome sequencing enables biomedical genetic studies of diverse populations. BMC Genomics. 22(1). 666–666. 4 indexed citations

7.

Wasik, Kaja A., Tomaz Berisa, Joseph K. Pickrell, et al.. (2021). Comparing low-pass sequencing and genotyping for trait mapping in pharmacogenetics. BMC Genomics. 22(1). 197–197. 32 indexed citations

8.

Zhou, Xin, Giorgia Battistoni, Osama E. Demerdash, et al.. (2015). Dual functions of Macpiwi1 in transposon silencing and stem cell maintenance in the flatworm Macrostomum lignano. RNA. 21(11). 1885–1897. 24 indexed citations

9.

Wasik, Kaja A., Oliver H. Tam, Simon Knott, et al.. (2015). RNF17 blocks promiscuous activity of PIWI proteins in mouse testes. Genes & Development. 29(13). 1403–1415. 44 indexed citations

10.

Wasik, Kaja A., James Gurtowski, Xin Zhou, et al.. (2015). Genome and transcriptome of the regeneration-competent flatworm, Macrostomum lignano. Proceedings of the National Academy of Sciences. 112(40). 12462–12467. 74 indexed citations

11.

Meikar, Oliver, Vasily V. Vagin, Frédéric Chalmel, et al.. (2014). An atlas of chromatoid body components. RNA. 20(4). 483–495. 89 indexed citations

12.

Vagin, Vasily V., Yang Yu, Yicheng Luo, et al.. (2013). Minotaur is critical for primary piRNA biogenesis. RNA. 19(8). 1064–1077. 45 indexed citations

13.

Wasik, Kaja A. & Clare A. Rebbeck. (2011). Keystone Symposia 40th Season: MicroRNAs and Noncoding RNAs in Cancer. Cancer Research. 71(19). 6102–6105. 1 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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