Esa Pitkänen

13.8k total citations
60 papers, 1.7k citations indexed

About

Esa Pitkänen is a scholar working on Molecular Biology, Pathology and Forensic Medicine and Cancer Research. According to data from OpenAlex, Esa Pitkänen has authored 60 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 14 papers in Pathology and Forensic Medicine and 11 papers in Cancer Research. Recurrent topics in Esa Pitkänen's work include Cancer Genomics and Diagnostics (11 papers), Genetic factors in colorectal cancer (10 papers) and Microbial Metabolic Engineering and Bioproduction (10 papers). Esa Pitkänen is often cited by papers focused on Cancer Genomics and Diagnostics (11 papers), Genetic factors in colorectal cancer (10 papers) and Microbial Metabolic Engineering and Bioproduction (10 papers). Esa Pitkänen collaborates with scholars based in Finland, Sweden and Denmark. Esa Pitkänen's co-authors include Lauri A. Aaltonen, Pia Vahteristo, Eevi Kaasinen, Netta Mäkinen, Jari Sjöberg, Hanna-Riikka Heinonen, Riku Katainen, Juho Rousu, Outi Kilpivaara and Kati Kämpjärvi and has published in prestigious journals such as New England Journal of Medicine, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Esa Pitkänen

57 papers receiving 1.6k citations

Peers

Esa Pitkänen
Hao Wen China
Daryl Johnson Australia
Rosemary L. Balleine Australia
Bairong Xia China
Yoke-Eng Chiew Australia
Yuexin Liu China
Ardeshir Hakam United States
Jillian A. Hung Australia
Hao Wen China
Esa Pitkänen
Citations per year, relative to Esa Pitkänen Esa Pitkänen (= 1×) peers Hao Wen

Countries citing papers authored by Esa Pitkänen

Since Specialization
Citations

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

Fields of papers citing papers by Esa Pitkänen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Esa Pitkänen

This figure shows the co-authorship network connecting the top 25 collaborators of Esa Pitkänen. A scholar is included among the top collaborators of Esa Pitkänen 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 Esa Pitkänen. Esa Pitkänen 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.
Mehine, Miika, Pernilla von Nandelstadh, Annukka Pasanen, et al.. (2025). Genomic landscape of endometrial polyps. Genome Medicine. 17(1). 132–132.
2.
Ianevski, Aleksandr, Wojciech Senkowski, Daria Bulanova, et al.. (2024). Single-cell transcriptomes identify patient-tailored therapies for selective co-inhibition of cancer clones. Nature Communications. 15(1). 8579–8579. 13 indexed citations
3.
Ji, Shaoxiong, Hang Dong, Yijia Zhang, et al.. (2024). A Unified Review of Deep Learning for Automated Medical Coding. ACM Computing Surveys. 56(12). 1–41. 13 indexed citations
4.
Schwarz, Claudia, et al.. (2024). ArcheD, a residual neural network for prediction of cerebrospinal fluid amyloid‐beta from amyloid PET images. European Journal of Neuroscience. 59(11). 3030–3044. 1 indexed citations
5.
Kerkelä, Erja, Ulla Impola, Jukka Partanen, et al.. (2023). DeepIFC : Virtual fluorescent labeling of blood cells in imaging flow cytometry data with deep learning. Cytometry Part A. 103(10). 807–817. 3 indexed citations
6.
Dufva, Olli, Emmi Jokinen, Hanna Lähteenmäki, et al.. (2023). Primary Acute Myeloid Leukemia Cells Trigger Distinct Activation Patterns in Expanded NK Cells. Blood. 142(Supplement 1). 66–66.
7.
Keränen, Mikko, M. Koskenvuo, Caroline A. Heckman, et al.. (2022). Enrichment of cancer-predisposing germline variants in adult and pediatric patients with acute lymphoblastic leukemia. Scientific Reports. 12(1). 10670–10670. 7 indexed citations
8.
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
9.
Meriranta, Leo, Amjad Alkodsi, Annika Pasanen, et al.. (2021). Molecular features encoded in the ctDNA reveal heterogeneity and predict outcome in high-risk aggressive B-cell lymphoma. Blood. 139(12). 1863–1877. 71 indexed citations
10.
Zagidullin, Bulat, Ziyan Wang, Yuanfang Guan, Esa Pitkänen, & Jing Tang. (2021). Comparative analysis of molecular fingerprints in prediction of drug combination effects. Briefings in Bioinformatics. 22(6). 64 indexed citations
11.
Valenzuela, Daniel, et al.. (2018). Towards pan-genome read alignment to improve variation calling. BMC Genomics. 19(S2). 87–87. 20 indexed citations
12.
Katainen, Riku, Iikki Donner, Tatiana Cajuso, et al.. (2018). Discovery of potential causative mutations in human coding and noncoding genome with the interactive software BasePlayer. Nature Protocols. 13(11). 2580–2600. 29 indexed citations
13.
Kondelin, Johanna, Alexandra E. Gylfe, Tomas Tanskanen, et al.. (2017). Comprehensive Evaluation of Protein Coding Mononucleotide Microsatellites in Microsatellite-Unstable Colorectal Cancer. Cancer Research. 77(15). 4078–4088. 14 indexed citations
14.
Heinonen, Hanna-Riikka, Miika Mehine, Netta Mäkinen, et al.. (2017). Global metabolomic profiling of uterine leiomyomas. British Journal of Cancer. 117(12). 1855–1864. 32 indexed citations
15.
Mehine, Miika, Eevi Kaasinen, Hanna-Riikka Heinonen, et al.. (2016). Integrated data analysis reveals uterine leiomyoma subtypes with distinct driver pathways and biomarkers. Proceedings of the National Academy of Sciences. 113(5). 1315–1320. 157 indexed citations
16.
Castillo, Sandra, Dorothee Barth, Mikko Arvas, et al.. (2016). Whole-genome metabolic model of Trichoderma reesei built by comparative reconstruction. Biotechnology for Biofuels. 9(1). 252–252. 16 indexed citations
17.
Välimäki, Niko, Hande Demi̇r, Esa Pitkänen, et al.. (2015). Whole-Genome Sequencing of Growth Hormone (GH)-Secreting Pituitary Adenomas. The Journal of Clinical Endocrinology & Metabolism. 100(10). 3918–3927. 69 indexed citations
18.
Huhta, Veikko, Ritva Penttinen, & Esa Pitkänen. (2012). Cultural factors in the distribution of soil mites in Finland. 6 indexed citations
19.
Mielikäinen, Taneli, et al.. (2006). Ab initio prediction of molecular fragments from tandem mass spectrometry data. 40–53. 11 indexed citations
20.
Pitkänen, Esa, et al.. (2006). Pathway assistant: a web portal for metabolic modelling. 90–96.

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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