Rebecka Jörnsten

2.2k total citations
44 papers, 1.4k citations indexed

About

Rebecka Jörnsten is a scholar working on Molecular Biology, Cancer Research and Computer Vision and Pattern Recognition. According to data from OpenAlex, Rebecka Jörnsten has authored 44 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Molecular Biology, 6 papers in Cancer Research and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in Rebecka Jörnsten's work include Gene expression and cancer classification (16 papers), Bioinformatics and Genomic Networks (15 papers) and Gene Regulatory Network Analysis (7 papers). Rebecka Jörnsten is often cited by papers focused on Gene expression and cancer classification (16 papers), Bioinformatics and Genomic Networks (15 papers) and Gene Regulatory Network Analysis (7 papers). Rebecka Jörnsten collaborates with scholars based in Sweden, United States and Netherlands. Rebecka Jörnsten's co-authors include Bin Yu, Ming Ouyang, Ronald P. Hart, Mikael Benson, William J. Welsh, Bonnie L. Firestein, Loyal A. Goff, Brad Love, Mika Gustafsson and Ralph Graichen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Nature Communications.

In The Last Decade

Rebecka Jörnsten

43 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rebecka Jörnsten Sweden 19 753 238 127 104 103 44 1.4k
Rubén Armañanzas Spain 17 755 1.0× 212 0.9× 308 2.4× 41 0.4× 74 0.7× 37 1.5k
Carlos Eduardo Ferreira Brazil 17 522 0.7× 88 0.4× 104 0.8× 23 0.2× 40 0.4× 69 1.2k
Radu Dobrin Sweden 22 1.6k 2.1× 179 0.8× 65 0.5× 102 1.0× 49 0.5× 82 2.8k
Weijia Zhang China 24 1.1k 1.5× 477 2.0× 111 0.9× 61 0.6× 28 0.3× 114 2.0k
Theodore J. Perkins Canada 25 1.5k 2.0× 159 0.7× 257 2.0× 91 0.9× 93 0.9× 100 2.3k
Cosmin Lazar Belgium 10 1.0k 1.3× 133 0.6× 277 2.2× 48 0.5× 33 0.3× 21 1.6k
Wessel N. van Wieringen Netherlands 30 1.3k 1.8× 606 2.5× 128 1.0× 63 0.6× 38 0.4× 99 2.5k
Tomáš Helikar United States 21 972 1.3× 72 0.3× 43 0.3× 114 1.1× 14 0.1× 72 1.5k
Michael D. Linderman United States 22 927 1.2× 167 0.7× 156 1.2× 187 1.8× 201 2.0× 45 2.4k
Sung‐Young Shin South Korea 20 960 1.3× 133 0.6× 83 0.7× 65 0.6× 42 0.4× 53 1.5k

Countries citing papers authored by Rebecka Jörnsten

Since Specialization
Citations

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

Fields of papers citing papers by Rebecka Jörnsten

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rebecka Jörnsten

This figure shows the co-authorship network connecting the top 25 collaborators of Rebecka Jörnsten. A scholar is included among the top collaborators of Rebecka Jörnsten 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 Rebecka Jörnsten. Rebecka Jörnsten 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.
Wang, Ziming, Nan Xue, Ling Lei, Rebecka Jörnsten, & Gui-Song Xia. (2025). Partial Distribution Matching via Partial Wasserstein Adversarial Networks. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(9). 7944–7959. 1 indexed citations
2.
Held, Felix, et al.. (2024). Reconstructing the regulatory programs underlying the phenotypic plasticity of neural cancers. Nature Communications. 15(1). 9699–9699. 1 indexed citations
3.
Gustafsson, Johan, Mihail Anton, Rebecka Jörnsten, et al.. (2023). Generation and analysis of context-specific genome-scale metabolic models derived from single-cell RNA-Seq data. Proceedings of the National Academy of Sciences. 120(6). e2217868120–e2217868120. 27 indexed citations
4.
Elgendy, Ramy, Mia Niklasson, Milena Doroszko, et al.. (2021). Modeling glioblastoma heterogeneity as a dynamic network of cell states. Molecular Systems Biology. 17(9). e10105–e10105. 26 indexed citations
5.
Elgendy, Ramy, Thale Kristin Olsen, Cecilia Dyberg, et al.. (2020). Integrative discovery of treatments for high-risk neuroblastoma. Nature Communications. 11(1). 71–71. 44 indexed citations
6.
Gustafsson, Johan, et al.. (2020). DSAVE: Detection of misclassified cells in single-cell RNA-Seq data. PLoS ONE. 15(12). e0243360–e0243360. 1 indexed citations
7.
Björnsson, Bergþór, Carl Borrebaeck, Nils Elander, et al.. (2019). Digital twins to personalize medicine. Genome Medicine. 12(1). 258 indexed citations
8.
Steineck, Gunnar, Fei Sjöberg, Cecilia Bull, et al.. (2017). Late radiation-induced bowel syndromes, tobacco smoking, age at treatment and time since treatment – gynecological cancer survivors. Acta Oncologica. 56(5). 682–691. 8 indexed citations
9.
Thor, Maria, Caroline Olsson, Rebecka Jörnsten, et al.. (2016). A Factor Analysis Approach for Clustering Patient Reported Outcomes. Methods of Information in Medicine. 55(5). 431–439. 13 indexed citations
10.
Kling, Teresia, Patrik Johansson, José Sánchez, et al.. (2015). Efficient exploration of pan-cancer networks by generalized covariance selection and interactive web content. Nucleic Acids Research. 43(15). e98–e98. 18 indexed citations
11.
Gerlee, Philip, Linnéa Schmidt, Naser Monsefi, et al.. (2013). Searching for Synergies: Matrix Algebraic Approaches for Efficient Pair Screening. PLoS ONE. 8(7). e68598–e68598. 6 indexed citations
12.
Moreau, Michael, Shannon Bruse, Rebecka Jörnsten, Yushi Liu, & Linda M. Brzustowicz. (2013). Chronological Changes in MicroRNA Expression in the Developing Human Brain. PLoS ONE. 8(4). e60480–e60480. 39 indexed citations
13.
Jauhiainen, Alexandra, Olle Nerman, George Michailidis, & Rebecka Jörnsten. (2012). Transcriptional and metabolic data integration and modeling for identification of active pathways. Biostatistics. 13(4). 748–761. 12 indexed citations
14.
Barrenäs, Fredrik, Sören Bruhn, Mika Gustafsson, et al.. (2012). Disease-Associated MRNA Expression Differences in Genes with Low DNA Methylation. 1 indexed citations
15.
Barrenäs, Fredrik, Sreenivas Chavali, Alexessander Couto Alves, et al.. (2012). Highly interconnected genes in disease-specific networks are enriched for disease-associated polymorphisms. Genome biology. 13(6). R46–R46. 52 indexed citations
16.
Lakshmipathy, Uma, Brad Love, Loyal A. Goff, et al.. (2007). MicroRNA Expression Pattern of Undifferentiated and Differentiated Human Embryonic Stem Cells. Stem Cells and Development. 16(6). 1003–1016. 140 indexed citations
17.
Charych, Erik I., et al.. (2006). Activity-Independent Regulation of Dendrite Patterning by Postsynaptic Density Protein PSD-95. Journal of Neuroscience. 26(40). 10164–10176. 120 indexed citations
18.
Stawicki, Tamara M., et al.. (2005). A Novel Role for Snapin in Dendrite Patterning: Interaction with Cypin. Molecular Biology of the Cell. 16(11). 5103–5114. 44 indexed citations
19.
Jörnsten, Rebecka. (2004). Clustering and classification based on the L1 data depth. Journal of Multivariate Analysis. 90(1). 67–89. 74 indexed citations
20.
Jörnsten, Rebecka. (2004). Clustering and classification based on the L1 data depth. Journal of Multivariate Analysis. 90(1). 67–89. 2 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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