Sonja T. Kujala

1.1k total citations
16 papers, 360 citations indexed

About

Sonja T. Kujala is a scholar working on Genetics, Molecular Biology and Nature and Landscape Conservation. According to data from OpenAlex, Sonja T. Kujala has authored 16 papers receiving a total of 360 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Genetics, 6 papers in Molecular Biology and 5 papers in Nature and Landscape Conservation. Recurrent topics in Sonja T. Kujala's work include Genetic diversity and population structure (8 papers), Genetic and phenotypic traits in livestock (5 papers) and Species Distribution and Climate Change (3 papers). Sonja T. Kujala is often cited by papers focused on Genetic diversity and population structure (8 papers), Genetic and phenotypic traits in livestock (5 papers) and Species Distribution and Climate Change (3 papers). Sonja T. Kujala collaborates with scholars based in Finland, France and Poland. Sonja T. Kujala's co-authors include Outi Savolainen, Tanja Pyhäjärvi, Katri Kärkkäinen, Minna Allinen, Robert Winqvist, Timo Knürr, Sanna‐Maria Karppinen, Jaana Lahti‐Domenici, Virpi Launonen and Komlan Avia and has published in prestigious journals such as SHILAP Revista de lepidopterología, New Phytologist and The Plant Journal.

In The Last Decade

Sonja T. Kujala

14 papers receiving 340 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sonja T. Kujala Finland 11 160 133 99 76 53 16 360
Áki J. Láruson United States 7 102 0.6× 56 0.4× 32 0.3× 45 0.6× 71 1.3× 12 260
Jianfeng Huang China 10 91 0.6× 294 2.2× 45 0.5× 164 2.2× 35 0.7× 28 504
Jasmin Zohren United Kingdom 6 138 0.9× 240 1.8× 24 0.2× 81 1.1× 34 0.6× 10 348
Alejandra Martínez‐Berdeja United States 7 30 0.2× 58 0.4× 63 0.6× 99 1.3× 24 0.5× 13 274
Caroline Bacquet Ecuador 12 169 1.1× 134 1.0× 28 0.3× 48 0.6× 35 0.7× 20 357
Sofia Adolfsson Sweden 9 161 1.0× 64 0.5× 45 0.5× 57 0.8× 93 1.8× 12 401
Eva Dušková Czechia 8 78 0.5× 228 1.7× 64 0.6× 121 1.6× 24 0.5× 8 423
Sin‐Che Lee Taiwan 12 184 1.1× 157 1.2× 158 1.6× 15 0.2× 90 1.7× 26 382
Daniela C. Soto United States 9 54 0.3× 140 1.1× 13 0.1× 81 1.1× 53 1.0× 14 247
Nathaniel K. Jue United States 12 219 1.4× 200 1.5× 86 0.9× 54 0.7× 109 2.1× 26 462

Countries citing papers authored by Sonja T. Kujala

Since Specialization
Citations

This map shows the geographic impact of Sonja T. Kujala'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 Sonja T. Kujala with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sonja T. Kujala more than expected).

Fields of papers citing papers by Sonja T. Kujala

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sonja T. Kujala. 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 Sonja T. Kujala. The network helps show where Sonja T. Kujala may publish in the future.

Co-authorship network of co-authors of Sonja T. Kujala

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

All Works

16 of 16 papers shown
1.
Terhonen, Eeva, Sonja T. Kujala, Tanja Pyhäjärvi, & Suvi Sutela. (2025). Genetic variation of resistance in Scots pine as possible solution against Diplodia sapinea. Silva Fennica. 59(2).
2.
Niskanen, Alina K., Sonja T. Kujala, Katri Kärkkäinen, Outi Savolainen, & Tanja Pyhäjärvi. (2024). Does the seed fall far from the tree? Weak fine-scale genetic structure in a continuous Scots pine population. SHILAP Revista de lepidopterología. 4. 1 indexed citations
3.
Kujala, Sonja T., Tiina M. Mattila, Jaakko Tyrmi, et al.. (2024). Optimising Exome Captures in Species With Large Genomes Using Species‐Specific Repetitive DNA Blocker. Molecular Ecology Resources. 25(3). e14053–e14053.
4.
Kujala, Sonja T., Komlan Avia, Hannu Kärkkäinen, et al.. (2023). Within- and between-population comparisons suggest independently acting selection maintaining parallel clines in Scots pine (Pinus sylvestris). Evolution Letters. 8(2). 231–242. 3 indexed citations
5.
Niskanen, Alina K., Annika Perry, Sonja T. Kujala, et al.. (2021). Taming the massive genome of Scots pine with PiSy50k, a new genotyping array for conifer research. The Plant Journal. 109(5). 1337–1350. 20 indexed citations
6.
Ramírez‐Valiente, José Alberto, Tanja Pyhäjärvi, Outi Savolainen, et al.. (2020). Selection patterns on early‐life phenotypic traits in Pinus sylvestris are associated with precipitation and temperature along a climatic gradient in Europe. New Phytologist. 229(5). 3009–3025. 20 indexed citations
7.
Ojeda, Darío I., Tiina M. Mattila, Tom Ruttink, et al.. (2019). Utilization of Tissue Ploidy Level Variation in de Novo Transcriptome Assembly of Pinus sylvestris. G3 Genes Genomes Genetics. 9(10). 3409–3421. 11 indexed citations
8.
Pyhäjärvi, Tanja, Sonja T. Kujala, & Outi Savolainen. (2019). 275 years of forestry meets genomics inPinus sylvestris. Evolutionary Applications. 13(1). 11–30. 36 indexed citations
9.
Kujala, Sonja T., Timo Knürr, Katri Kärkkäinen, et al.. (2016). Genetic heterogeneity underlying variation in a locally adaptive clinal trait in Pinus sylvestris revealed by a Bayesian multipopulation analysis. Heredity. 118(5). 413–423. 17 indexed citations
10.
Kujala, Sonja T.. (2015). Dissecting genetic variation in European Scots pine ( Pinus sylvestris L.) : special emphasis on polygenic adaptation. 5 indexed citations
11.
Kujala, Sonja T. & Outi Savolainen. (2012). Sequence variation patterns along a latitudinal cline in Scots pine (Pinus sylvestris): signs of clinal adaptation?. Tree Genetics & Genomes. 8(6). 1451–1467. 51 indexed citations
12.
Savolainen, Outi, Sonja T. Kujala, Tanja Pyhäjärvi, et al.. (2011). Adaptive Potential of Northernmost Tree Populations to Climate Change, with Emphasis on Scots Pine (Pinus sylvestris L.). Journal of Heredity. 102(5). 526–536. 54 indexed citations
13.
Sebastiani, Federico, et al.. (2011). Novel polymorphic nuclear microsatellite markers for Pinus sylvestris L.. Conservation Genetics Resources. 4(2). 231–234. 36 indexed citations
14.
Pyhäjärvi, Tanja, Sonja T. Kujala, & Outi Savolainen. (2010). Revisiting protein heterozygosity in plants—nucleotide diversity in allozyme coding genes of conifer Pinus sylvestris. Tree Genetics & Genomes. 7(2). 385–397. 20 indexed citations
15.
Peltoketo, Hellevi, Minna Allinen, Jaana Vuosku, et al.. (2004). Characterization and expression of the human WNT4; lack of associated germline mutations in high—to moderate—risk breast and ovarian cancer. Cancer Letters. 213(1). 83–90. 15 indexed citations
16.
Allinen, Minna, Sonja T. Kujala, Jaana Lahti‐Domenici, et al.. (2002). Analysis of 11q21–24 loss of heterozygosity candidate target genes in breast cancer: Indications of TSLC1 promoter hypermethylation. Genes Chromosomes and Cancer. 34(4). 384–389. 71 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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