Liisa Kauppi

3.0k total citations · 1 hit paper
33 papers, 2.1k citations indexed

About

Liisa Kauppi is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Liisa Kauppi has authored 33 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 8 papers in Genetics and 7 papers in Cancer Research. Recurrent topics in Liisa Kauppi's work include DNA Repair Mechanisms (14 papers), CRISPR and Genetic Engineering (8 papers) and Chromosomal and Genetic Variations (6 papers). Liisa Kauppi is often cited by papers focused on DNA Repair Mechanisms (14 papers), CRISPR and Genetic Engineering (8 papers) and Chromosomal and Genetic Variations (6 papers). Liisa Kauppi collaborates with scholars based in Finland, United States and United Kingdom. Liisa Kauppi's co-authors include Alec J. Jeffreys, Rita Neumann, Scott Keeney, Maria Jasin, Frédéric Baudat, Marco Barchi, Julian Lange, Peter Romanienko, Raymond Wang and Francesca Cole and has published in prestigious journals such as Nature, Science and Proceedings of the National Academy of Sciences.

In The Last Decade

Liisa Kauppi

31 papers receiving 2.0k citations

Hit Papers

Intensely punctate meiotic recombination in the class II ... 2001 2026 2009 2017 2001 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Liisa Kauppi Finland 19 1.4k 857 508 169 153 33 2.1k
Amber E. Alsop Australia 19 982 0.7× 578 0.7× 259 0.5× 176 1.0× 140 0.9× 26 1.5k
Sandrine Caburet France 23 1.3k 0.9× 686 0.8× 229 0.5× 103 0.6× 141 0.9× 39 1.9k
Ramaiah Nagaraja United States 20 1.1k 0.8× 609 0.7× 211 0.4× 122 0.7× 116 0.8× 44 1.5k
Anne‐Laure Todeschini France 25 1.1k 0.8× 641 0.7× 371 0.7× 89 0.5× 142 0.9× 41 1.7k
Bertrand Pain France 22 1.7k 1.2× 1.1k 1.3× 111 0.2× 148 0.9× 291 1.9× 69 2.2k
Mark Wossidlo United States 12 1.7k 1.2× 362 0.4× 374 0.7× 65 0.4× 146 1.0× 16 1.8k
Darío G. Lupiáñez Germany 15 1.2k 0.9× 449 0.5× 332 0.7× 60 0.4× 182 1.2× 28 1.5k
Bee Ling Ng United Kingdom 20 721 0.5× 487 0.6× 316 0.6× 249 1.5× 130 0.8× 48 1.4k
Ivo Renkens Netherlands 15 894 0.6× 524 0.6× 251 0.5× 49 0.3× 306 2.0× 21 1.3k
Kerry J. Schimenti United States 18 1.1k 0.8× 344 0.4× 216 0.4× 46 0.3× 184 1.2× 24 1.4k

Countries citing papers authored by Liisa Kauppi

Since Specialization
Citations

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

Fields of papers citing papers by Liisa Kauppi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liisa Kauppi

This figure shows the co-authorship network connecting the top 25 collaborators of Liisa Kauppi. A scholar is included among the top collaborators of Liisa Kauppi 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 Liisa Kauppi. Liisa Kauppi 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.
Dai, Jun, Shuyu Zheng, Matías Marín Falco, et al.. (2024). Tracing back primed resistance in cancer via sister cells. Nature Communications. 15(1). 1158–1158. 7 indexed citations
2.
Erkan, Erdoğan Pekcan, Matías Marín Falco, Kaisa Huhtinen, et al.. (2024). Locus-specific LINE-1 expression in clinical ovarian cancer specimens at the single-cell level. Scientific Reports. 14(1). 4322–4322. 1 indexed citations
3.
Zagidullin, Bulat, et al.. (2022). Single-Cell Mononucleotide Microsatellite Analysis Reveals Differential Insertion-Deletion Dynamics in Mouse T Cells. Frontiers in Genetics. 13. 913163–913163. 5 indexed citations
4.
Kauppi, Liisa, et al.. (2021). Tissue-specific reduction in MLH1 expression induces microsatellite instability in intestine of Mlh1 mice. DNA repair. 106. 103178–103178. 13 indexed citations
5.
Tumiati, Manuela, Jouko Sandholm, Katja Kaipio, et al.. (2021). Targeting DNA Homologous Repair Proficiency With Concomitant Topoisomerase II and c-Abl Inhibition. Frontiers in Oncology. 11. 733700–733700. 5 indexed citations
6.
Acquaviva, Laurent, Michiel Boekhout, Mehmet E. Karasu, et al.. (2020). Ensuring meiotic DNA break formation in the mouse pseudoautosomal region. Nature. 582(7812). 426–431. 64 indexed citations
7.
Hamer, Geert, Pirkka‐Pekka Laurila, Manuela Tumiati, et al.. (2019). Transcription Factor USF1 Is Required for Maintenance of Germline Stem Cells in Male Mice. Endocrinology. 160(5). 1119–1136. 17 indexed citations
8.
Kauppi, Liisa, et al.. (2019). Detection of Retrotransposition Activity of Hot LINE-1s by Long-Distance Inverse PCR. Journal of Visualized Experiments.
9.
Casado, Julia, Laura Turunen, Suvi‐Katri Leivonen, et al.. (2019). Drug screening approach combines epigenetic sensitization with immunochemotherapy in cancer. Clinical Epigenetics. 11(1). 192–192. 2 indexed citations
10.
Cajuso, Tatiana, Riku Katainen, Päivi Sulo, et al.. (2017). Detection of subclonal L1 transductions in colorectal cancer by long-distance inverse-PCR and Nanopore sequencing. Scientific Reports. 7(1). 14521–14521. 18 indexed citations
11.
Sarvilinna, Nanna, et al.. (2015). Detection and screening of chromosomal rearrangements in uterine leiomyomas by long‐distance inverse PCR. Genes Chromosomes and Cancer. 55(3). 215–226. 7 indexed citations
12.
Kauppi, Liisa, et al.. (2015). Sex chromosome recombination failure, apoptosis, and fertility in male mice. Chromosoma. 125(2). 227–235. 18 indexed citations
13.
Kauppi, Liisa, et al.. (2013). Dynamics of DOT1L localization and H3K79 methylation during meiotic prophase I in mouse spermatocytes. Chromosoma. 123(1-2). 147–164. 30 indexed citations
14.
Kauppi, Liisa, Marco Barchi, Julian Lange, et al.. (2013). Numerical constraints and feedback control of double-strand breaks in mouse meiosis. Genes & Development. 27(8). 873–886. 138 indexed citations
15.
Cole, Francesca, Liisa Kauppi, Julian Lange, et al.. (2012). Homeostatic control of recombination is implemented progressively in mouse meiosis. Nature Cell Biology. 14(4). 424–430. 179 indexed citations
16.
Kauppi, Liisa, Maria Jasin, & Scott Keeney. (2012). The tricky path to recombining X and Y chromosomes in meiosis. Annals of the New York Academy of Sciences. 1267(1). 18–23. 59 indexed citations
17.
Kauppi, Liisa, Marco Barchi, Frédéric Baudat, et al.. (2011). Distinct Properties of the XY Pseudoautosomal Region Crucial for Male Meiosis. Science. 331(6019). 916–920. 187 indexed citations
18.
Kauppi, Liisa, Michael P. H. Stumpf, & Alec J. Jeffreys. (2005). Localized breakdown in linkage disequilibrium does not always predict sperm crossover hot spots in the human MHC class II region. Genomics. 86(1). 13–24. 36 indexed citations
19.
Kauppi, Liisa, Alec J. Jeffreys, & Scott Keeney. (2004). Where the crossovers are: recombination distributions in mammals. Nature Reviews Genetics. 5(6). 413–424. 242 indexed citations
20.
Kauppi, Liisa. (2003). Recombination hotspots rather than population history dominate linkage disequilibrium in the MHC class II region. Human Molecular Genetics. 12(1). 33–40. 91 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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