Sami Kilpinen

2.9k total citations
39 papers, 2.0k citations indexed

About

Sami Kilpinen is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Sami Kilpinen has authored 39 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Molecular Biology, 9 papers in Cancer Research and 8 papers in Oncology. Recurrent topics in Sami Kilpinen's work include Gene expression and cancer classification (8 papers), Molecular Biology Techniques and Applications (6 papers) and Cancer Genomics and Diagnostics (5 papers). Sami Kilpinen is often cited by papers focused on Gene expression and cancer classification (8 papers), Molecular Biology Techniques and Applications (6 papers) and Cancer Genomics and Diagnostics (5 papers). Sami Kilpinen collaborates with scholars based in Finland, United States and Norway. Sami Kilpinen's co-authors include Olli Kallioniemi, Rolf I. Skotheim, Anja Ruusulehto, Ragnhild A. Lothe, Anita Sveen, Kristiina Iljin, Henrik Edgren, Maija Wolf, Kalle Ojala and Henri Sara and has published in prestigious journals such as Cell, PLoS ONE and Development.

In The Last Decade

Sami Kilpinen

35 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sami Kilpinen Finland 20 1.4k 465 386 290 190 39 2.0k
Sara A. Byron United States 18 1.3k 0.9× 549 1.2× 375 1.0× 223 0.8× 161 0.8× 48 1.9k
Craig April United States 22 949 0.7× 506 1.1× 246 0.6× 274 0.9× 205 1.1× 41 1.8k
Audrey Kauffmann Switzerland 14 895 0.6× 311 0.7× 360 0.9× 397 1.4× 126 0.7× 24 1.8k
Jasper Mullenders Netherlands 17 2.0k 1.4× 440 0.9× 651 1.7× 204 0.7× 271 1.4× 25 2.7k
Qingrong Chen United States 25 1.3k 0.9× 450 1.0× 388 1.0× 216 0.7× 227 1.2× 61 2.0k
Alex Lash United States 15 1.5k 1.1× 295 0.6× 530 1.4× 235 0.8× 324 1.7× 24 2.3k
Sílvia Carvalho Israel 23 1.1k 0.8× 429 0.9× 516 1.3× 212 0.7× 137 0.7× 36 1.8k
Kshitij Srivastava United States 22 883 0.6× 530 1.1× 304 0.8× 135 0.5× 183 1.0× 72 1.8k
Ru‐Fang Yeh United States 20 1.9k 1.3× 670 1.4× 379 1.0× 142 0.5× 310 1.6× 26 2.7k
Joseph M. Amann United States 28 1.8k 1.3× 426 0.9× 825 2.1× 605 2.1× 212 1.1× 53 2.7k

Countries citing papers authored by Sami Kilpinen

Since Specialization
Citations

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

Fields of papers citing papers by Sami Kilpinen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sami Kilpinen

This figure shows the co-authorship network connecting the top 25 collaborators of Sami Kilpinen. A scholar is included among the top collaborators of Sami Kilpinen 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 Sami Kilpinen. Sami Kilpinen 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.
2.
Kilpinen, Sami, et al.. (2023). Transcriptomic analyses reveal three distinct molecular subgroups of Merkel cell carcinoma with differing prognoses. International Journal of Cancer. 152(10). 2099–2108. 8 indexed citations
3.
Kilpinen, Sami, et al.. (2023). PDE3A Is a Highly Expressed Therapy Target in Myxoid Liposarcoma. Cancers. 15(22). 5308–5308. 1 indexed citations
4.
5.
6.
Sveen, Anita, Sami Kilpinen, Anja Ruusulehto, Ragnhild A. Lothe, & Rolf I. Skotheim. (2015). Aberrant RNA splicing in cancer; expression changes and driver mutations of splicing factor genes. Oncogene. 35(19). 2413–2427. 346 indexed citations
7.
Oghabian, Ali, et al.. (2014). Biclustering Methods: Biological Relevance and Application in Gene Expression Analysis. PLoS ONE. 9(3). e90801–e90801. 58 indexed citations
8.
Miecznikowski, Jeffrey C., Alfiya Safina, Mairead Commane, et al.. (2013). Facilitates Chromatin Transcription Complex Is an “Accelerator” of Tumor Transformation and Potential Marker and Target of Aggressive Cancers. Cell Reports. 4(1). 159–173. 107 indexed citations
9.
Mpindi, John Patrick, Henri Sara, Saija Haapa-Paananen, et al.. (2011). GTI: A Novel Algorithm for Identifying Outlier Gene Expression Profiles from Integrated Microarray Datasets. PLoS ONE. 6(2). e17259–e17259. 24 indexed citations
10.
Kilpinen, Sami, Kalle Ojala, & Olli Kallioniemi. (2011). Abstract 52: A new method to interpret gene expression microarray data for individual tumors by profile alignment against a reference dataset of 10,000 samples. Cancer Research. 71(8_Supplement). 52–52. 1 indexed citations
11.
Ojala, Kalle, Sami Kilpinen, & Olli Kallioniemi. (2011). Classification of unknown primary tumors with a data-driven method based on a large microarray reference database. Genome Medicine. 3(9). 63–63. 9 indexed citations
12.
Sugiyama, Nami, Markku Varjosalo, Jouko Lohi, et al.. (2010). Fibroblast Growth Factor Receptor 4 Regulates Tumor Invasion by Coupling Fibroblast Growth Factor Signaling to Extracellular Matrix Degradation. Cancer Research. 70(20). 7851–7861. 44 indexed citations
13.
Kilpinen, Sami, Kalle Ojala, & Olli Kallioniemi. (2010). Analysis of Kinase Gene Expression Patterns across 5681 Human Tissue Samples Reveals Functional Genomic Taxonomy of the Kinome. PLoS ONE. 5(12). e15068–e15068. 41 indexed citations
14.
Varjosalo, Markku, Mikael Björklund, Fang Cheng, et al.. (2008). Application of Active and Kinase-Deficient Kinome Collection for Identification of Kinases Regulating Hedgehog Signaling. Cell. 133(3). 537–548. 142 indexed citations
15.
Sundvall, Maria, Kristiina Iljin, Sami Kilpinen, et al.. (2008). Role of ErbB4 in Breast Cancer. Journal of Mammary Gland Biology and Neoplasia. 13(2). 259–268. 118 indexed citations
16.
Wolf, Michael, Henrik Edgren, Ian G. Mills, et al.. (2006). Integrated DNA/RNA microarray profiling of hormone-refractory clinical prostate cancers and metastases indicates deregulation of several pathways, including androgen/AR, Hedgehog, MAPK and neuroactive ligand/receptor signalling. Cancer Research. 66. 1 indexed citations
17.
Iljin, Kristiina, Maija Wolf, Henrik Edgren, et al.. (2006). TMPRSS2 Fusions with Oncogenic ETS Factors in Prostate Cancer Involve Unbalanced Genomic Rearrangements and Are Associated with HDAC1 and Epigenetic Reprogramming. Cancer Research. 66(21). 10242–10246. 180 indexed citations
18.
Autio, Reija, Sami Kilpinen, Matti Saarela, et al.. (2006). The weibull distribution based normalization method for affymetrix gene expression microarray data. 9–10. 1 indexed citations
19.
Wolf, Maija, Henrik Edgren, Sami Kilpinen, et al.. (2005). NMD Microarray Analysis for Rapid Genome‐Wide Screen of Mutated Genes in Cancer. Analytical Cellular Pathology. 27(3). 169–173. 12 indexed citations
20.
Repo, Heikki, Sami Kilpinen, Aarno Palotie, et al.. (2002). CD14 and TNFα promoter polymorphisms in patients with acute arthritis. Scandinavian Journal of Rheumatology. 31(6). 355–361. 9 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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