Jonas Paulsen

2.3k total citations
30 papers, 887 citations indexed

About

Jonas Paulsen is a scholar working on Molecular Biology, Plant Science and Genetics. According to data from OpenAlex, Jonas Paulsen has authored 30 papers receiving a total of 887 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Molecular Biology, 7 papers in Plant Science and 6 papers in Genetics. Recurrent topics in Jonas Paulsen's work include Genomics and Chromatin Dynamics (20 papers), RNA Research and Splicing (10 papers) and Chromosomal and Genetic Variations (7 papers). Jonas Paulsen is often cited by papers focused on Genomics and Chromatin Dynamics (20 papers), RNA Research and Splicing (10 papers) and Chromosomal and Genetic Variations (7 papers). Jonas Paulsen collaborates with scholars based in Norway, United States and France. Jonas Paulsen's co-authors include Philippe Collas, Eivind Hovig, Tharvesh M. Liyakat Ali, Erwan Delbarre, Tonje G. Lien, Marco Di Stefano, Monika Sekelja, Nolwenn Briand, Corinne Vigouroux and Akshay Shah and has published in prestigious journals such as Nucleic Acids Research, Nature Genetics and The EMBO Journal.

In The Last Decade

Jonas Paulsen

28 papers receiving 872 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonas Paulsen Norway 16 775 156 137 71 47 30 887
Yong Wei China 10 459 0.6× 137 0.9× 52 0.4× 71 1.0× 17 0.4× 25 733
Cheng Ran Lisa Huang United States 10 947 1.2× 642 4.1× 157 1.1× 156 2.2× 22 0.5× 11 1.1k
Marie L. Rossi United States 13 837 1.1× 132 0.8× 93 0.7× 161 2.3× 22 0.5× 15 894
Marcel Méchali France 8 775 1.0× 85 0.5× 121 0.9× 84 1.2× 24 0.5× 11 847
Teng Zhang China 16 718 0.9× 237 1.5× 62 0.5× 264 3.7× 47 1.0× 30 921
Eva Alloza Spain 6 510 0.7× 70 0.4× 104 0.8× 78 1.1× 18 0.4× 9 681
Alejandro Barrera United States 15 642 0.8× 80 0.5× 133 1.0× 109 1.5× 23 0.5× 34 908
Sylvain Martineau France 11 381 0.5× 56 0.4× 137 1.0× 58 0.8× 19 0.4× 15 546
Stefanie Böhm Sweden 18 892 1.2× 90 0.6× 92 0.7× 98 1.4× 32 0.7× 31 1.0k
Artem V. Luzhin Russia 11 492 0.6× 85 0.5× 47 0.3× 62 0.9× 5 0.1× 19 663

Countries citing papers authored by Jonas Paulsen

Since Specialization
Citations

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

Fields of papers citing papers by Jonas Paulsen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonas Paulsen

This figure shows the co-authorship network connecting the top 25 collaborators of Jonas Paulsen. A scholar is included among the top collaborators of Jonas Paulsen 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 Jonas Paulsen. Jonas Paulsen 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.
Sandve, Simen R., et al.. (2025). TAD conservation in vertebrate genomes is driven by stabilising selection. BMC Biology. 23(1). 241–241. 2 indexed citations
2.
Paulsen, Jonas, et al.. (2025). Nuclear mechano-confinement induces geometry-dependent HP1α condensate alterations. Communications Biology. 8(1). 308–308. 1 indexed citations
3.
Paulsen, Jonas, et al.. (2024). Modeling properties of chromosome territories using polymer filaments in diverse confinement geometries. Chromosome Research. 32(3). 11–11.
4.
Paulsen, Jonas, et al.. (2024). hictk: blazing fast toolkit to work with .hic and .cool files. Bioinformatics. 40(7).
5.
Paulsen, Jonas, et al.. (2023). The shape of chromatin: insights from computational recognition of geometric patterns in Hi-C data. Briefings in Bioinformatics. 24(5). 6 indexed citations
6.
Ali, Tharvesh M. Liyakat, et al.. (2021). TAD cliques predict key features of chromatin organization. BMC Genomics. 22(1). 499–499. 8 indexed citations
7.
Paulsen, Jonas & Philippe Collas. (2021). Modeling the 3D Genome Using Hi-C and Nuclear Lamin-Genome Contacts. Methods in molecular biology. 2301. 337–352. 1 indexed citations
8.
Stefano, Marco Di, Jonas Paulsen, Daniel Jost, & Marc A. Martı́-Renom. (2020). 4D nucleome modeling. Current Opinion in Genetics & Development. 67. 25–32. 29 indexed citations
9.
Paulsen, Jonas, Tharvesh M. Liyakat Ali, Maxim Nekrasov, et al.. (2019). Long-range interactions between topologically associating domains shape the four-dimensional genome during differentiation. Nature Genetics. 51(5). 835–843. 85 indexed citations
10.
Briand, Nolwenn, et al.. (2018). Lamin A, Chromatin and FPLD2: Not Just a Peripheral Ménage-à-Trois. Frontiers in Cell and Developmental Biology. 6. 73–73. 4 indexed citations
11.
Paulsen, Jonas, Tharvesh M. Liyakat Ali, & Philippe Collas. (2018). Computational 3D genome modeling using Chrom3D. Nature Protocols. 13(5). 1137–1152. 39 indexed citations
12.
García-Nieto, Pablo E., Erin K. Schwartz, D. King, et al.. (2017). Carcinogen susceptibility is regulated by genome architecture and predicts cancer mutagenesis. The EMBO Journal. 36(19). 2829–2843. 64 indexed citations
13.
Paulsen, Jonas, Monika Sekelja, Anja R. Oldenburg, et al.. (2017). Chrom3D: three-dimensional genome modeling from Hi-C and nuclear lamin-genome contacts. Genome biology. 18(1). 21–21. 138 indexed citations
14.
Sekelja, Monika, Jonas Paulsen, & Philippe Collas. (2016). 4D nucleomes in single cells: what can computational modeling reveal about spatial chromatin conformation?. Genome biology. 17(1). 54–54. 15 indexed citations
15.
Stefano, Marco Di, Jonas Paulsen, Tonje G. Lien, Eivind Hovig, & Cristian Micheletti. (2016). Hi-C-constrained physical models of human chromosomes recover functionally-related properties of genome organization. Scientific Reports. 6(1). 35985–35985. 54 indexed citations
16.
Paulsen, Jonas, Odin Gramstad, & Philippe Collas. (2015). Manifold Based Optimization for Single-Cell 3D Genome Reconstruction. PLoS Computational Biology. 11(8). e1004396–e1004396. 33 indexed citations
17.
Paulsen, Jonas, Einar Andreas Rødland, Lars Holden, Marit Holden, & Eivind Hovig. (2014). A statistical model of ChIA-PET data for accurate detection of chromatin 3D interactions. Nucleic Acids Research. 42(18). e143–e143. 44 indexed citations
18.
Paulsen, Jonas, Tonje G. Lien, Geir Kjetil Sandve, et al.. (2013). Handling realistic assumptions in hypothesis testing of 3D co-localization of genomic elements. Nucleic Acids Research. 41(10). 5164–5174. 18 indexed citations
19.
Hamelryck, Thomas, Mikael Borg, Jonas Paulsen, et al.. (2010). Potentials of Mean Force for Protein Structure Prediction Vindicated, Formalized and Generalized. PLoS ONE. 5(11). e13714–e13714. 52 indexed citations
20.
Pálsson, Snæbjörn, Jonas Paulsen, & Einar Árnason. (2008). Rapid Evolution of the Intergenic T–P Spacer in the mtDNA of Arctic Cod Arctogadus glacialis. Marine Biotechnology. 10(3). 270–277. 4 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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