Patrik Edén

1.7k total citations
33 papers, 1.3k citations indexed

About

Patrik Edén is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Hematology. According to data from OpenAlex, Patrik Edén has authored 33 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 8 papers in Pathology and Forensic Medicine and 7 papers in Hematology. Recurrent topics in Patrik Edén's work include Gene expression and cancer classification (8 papers), Acute Myeloid Leukemia Research (7 papers) and Bioinformatics and Genomic Networks (6 papers). Patrik Edén is often cited by papers focused on Gene expression and cancer classification (8 papers), Acute Myeloid Leukemia Research (7 papers) and Bioinformatics and Genomic Networks (6 papers). Patrik Edén collaborates with scholars based in Sweden, Denmark and United States. Patrik Edén's co-authors include Carsten Peterson, Mårten Fernö, Mattias Ohlsson, Thomas Breslin, Thoas Fioretos, Morten Krogh, Carsten Rose, Carin Lassen, Bertil Johansson and Jesper Heldrup and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Blood and PLoS ONE.

In The Last Decade

Patrik Edén

31 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Patrik Edén Sweden 21 637 304 263 232 207 33 1.3k
Dorina Gui United States 23 862 1.4× 345 1.1× 243 0.9× 166 0.7× 236 1.1× 52 1.7k
Kimio Tanaka Japan 24 922 1.4× 241 0.8× 372 1.4× 311 1.3× 360 1.7× 112 2.0k
Benjamin Mow Singapore 11 567 0.9× 673 2.2× 272 1.0× 105 0.5× 168 0.8× 17 1.4k
Perry Maxwell United Kingdom 24 530 0.8× 676 2.2× 360 1.4× 335 1.4× 97 0.5× 63 1.6k
Patrick R. Blackburn United States 19 923 1.4× 250 0.8× 235 0.9× 130 0.6× 369 1.8× 74 1.7k
Rutika Mehta United States 19 468 0.7× 556 1.8× 331 1.3× 295 1.3× 44 0.2× 73 1.3k
Yuichi Shiraishi Japan 26 1.2k 1.9× 348 1.1× 545 2.1× 203 0.9× 538 2.6× 98 2.1k
Xinyi Wu China 18 1.3k 2.1× 425 1.4× 266 1.0× 335 1.4× 46 0.2× 75 2.0k
Siew‐Kee Low Japan 21 447 0.7× 408 1.3× 486 1.8× 267 1.2× 55 0.3× 46 1.3k
Jonathan R. Dry United States 19 818 1.3× 474 1.6× 473 1.8× 230 1.0× 65 0.3× 34 1.4k

Countries citing papers authored by Patrik Edén

Since Specialization
Citations

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

Fields of papers citing papers by Patrik Edén

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Patrik Edén

This figure shows the co-authorship network connecting the top 25 collaborators of Patrik Edén. A scholar is included among the top collaborators of Patrik Edén 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 Patrik Edén. Patrik Edén 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.
Bendahl, Pär‐Ola, Ida Arvidsson, Magnus Dustler, et al.. (2025). Deep learning on routine full-breast mammograms enhances lymph node metastasis prediction in early breast cancer. npj Digital Medicine. 8(1). 425–425.
2.
Merdasa, Aboma, et al.. (2025). Advancing non-invasive melanoma diagnostics with deep learning and multispectral photoacoustic imaging. Photoacoustics. 45. 100743–100743.
3.
Edén, Patrik, et al.. (2024). Identification of sentinel lymph node macrometastasis in breast cancer by deep learning based on clinicopathological characteristics. Scientific Reports. 14(1). 26970–26970. 1 indexed citations
4.
Ohlsson, Mattias, et al.. (2019). Artificial neural network models to predict nodal status in clinically node-negative breast cancer. BMC Cancer. 19(1). 610–610. 27 indexed citations
5.
6.
Edén, Patrik, et al.. (2015). Finding Risk Groups by Optimizing Artificial Neural Networks on the Area under the Survival Curve Using Genetic Algorithms. PLoS ONE. 10(9). e0137597–e0137597. 6 indexed citations
7.
Pina, Cristina, José Teles, Cristina Fugazza, et al.. (2015). Single-Cell Network Analysis Identifies DDIT3 as a Nodal Lineage Regulator in Hematopoiesis. Cell Reports. 11(10). 1503–1510. 49 indexed citations
8.
Teles, José, Cristina Pina, Patrik Edén, et al.. (2013). Transcriptional Regulation of Lineage Commitment - A Stochastic Model of Cell Fate Decisions. PLoS Computational Biology. 9(8). e1003197–e1003197. 42 indexed citations
9.
Joost, Patrick, Mats Ehinger, Patrik Edén, et al.. (2012). Gene expression profiling indicates that immunohistochemical expression of CD40 is a marker of an inflammatory reaction in the tumor stroma of diffuse large B-cell lymphoma. Leukemia & lymphoma. 53(9). 1764–1768. 10 indexed citations
10.
Andersson, Anna, Patrik Edén, Tor Olofsson, & Thoas Fioretos. (2010). Gene expression signatures in childhood acute leukemias are largely unique and distinct from those of normal tissues and other malignancies. BMC Medical Genomics. 3(1). 6–6. 25 indexed citations
11.
Järås, Marcus, Helena Ågerstam, Carin Lassen, et al.. (2009). Expression of P190 and P210 BCR/ABL1 in normal human CD34+ cells induces similar gene expression profiles and results in a STAT5-dependent expansion of the erythroid lineage. Experimental Hematology. 37(3). 367–375. 11 indexed citations
12.
Francis, Princy, Heidi M. Namløs, Christoph R. Müller, et al.. (2007). Diagnostic and prognostic gene expression signatures in 177 soft tissue sarcomas: hypoxia-induced transcription profile signifies metastatic potential. BMC Genomics. 8(1). 73–73. 134 indexed citations
13.
14.
Niméus, Emma, Patrik Edén, Anders Johnsson, et al.. (2006). Gene expression profilers and conventional clinical markers to predict distant recurrences for premenopausal breast cancer patients after adjuvant chemotherapy. European Journal of Cancer. 42(16). 2729–2737. 20 indexed citations
15.
Andersson, Anna, Tor Olofsson, David Lindgren, et al.. (2005). Molecular signatures in childhood acute leukemia and their correlations to expression patterns in normal hematopoietic subpopulations. Proceedings of the National Academy of Sciences. 102(52). 19069–19074. 78 indexed citations
16.
Andersson, Anna, Patrik Edén, David Lindgren, et al.. (2005). Gene expression profiling of leukemic cell lines reveals conserved molecular signatures among subtypes with specific genetic aberrations. Leukemia. 19(6). 1042–1050. 58 indexed citations
17.
Francis, Princy, Josefin Fernebro, Patrik Edén, et al.. (2005). Intratumor versus intertumor heterogeneity in gene expression profiles of soft‐tissue sarcomas. Genes Chromosomes and Cancer. 43(3). 302–308. 33 indexed citations
18.
Gruvberger-Saal, Sofia K., Patrik Edén, Markus Ringnér, et al.. (2004). Predicting continuous values of prognostic markers in breast cancer from microarray gene expression profiles. Molecular Cancer Therapeutics. 3(2). 161–168. 25 indexed citations
19.
Breslin, Thomas, Patrik Edén, & Morten Krogh. (2004). Comparing functional annotation analyses with Catmap. BMC Bioinformatics. 5(1). 193–193. 71 indexed citations
20.
Ringnér, Markus, Patrik Edén, Åke Borg, et al.. (2002). Expression profiling to predict outcome in breast cancer: the influence of sample selection. Breast Cancer Research. 5(1). 23–6. 34 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Dorina Gui Breakdown of academic impact, for papers by Kimio Tanaka Breakdown of academic impact, for papers by Benjamin Mow Breakdown of academic impact, for papers by Perry Maxwell Breakdown of academic impact, for papers by Patrick R. Blackburn Breakdown of academic impact, for papers by Rutika Mehta Breakdown of academic impact, for papers by Yuichi Shiraishi Breakdown of academic impact, for papers by Xinyi Wu Breakdown of academic impact, for papers by Siew‐Kee Low Breakdown of academic impact, for papers by Jonathan R. Dry
Rankless by CCL
2026