Marko Laakso

1.3k total citations
20 papers, 924 citations indexed

About

Marko Laakso is a scholar working on Molecular Biology, Cancer Research and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Marko Laakso has authored 20 papers receiving a total of 924 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 7 papers in Cancer Research and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Marko Laakso's work include Bioinformatics and Genomic Networks (7 papers), Gene expression and cancer classification (6 papers) and Cancer Genomics and Diagnostics (5 papers). Marko Laakso is often cited by papers focused on Bioinformatics and Genomic Networks (7 papers), Gene expression and cancer classification (6 papers) and Cancer Genomics and Diagnostics (5 papers). Marko Laakso collaborates with scholars based in Finland, United States and Netherlands. Marko Laakso's co-authors include Sampsa Hautaniemi, Kristian Ovaska, Biswajyoti Sahu, Olli A. Jänne, Päivi Pihlajamaa, Juho Konsti, Olli Kallioniemi, Tuomas Mirtti, Antti Rannikko and Mikael Lundin and has published in prestigious journals such as The EMBO Journal, Bioinformatics and Cancer Research.

In The Last Decade

Marko Laakso

17 papers receiving 912 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Marko Laakso Finland 13 621 318 191 177 115 20 924
Kristian Ovaska Finland 13 753 1.2× 335 1.1× 202 1.1× 206 1.2× 126 1.1× 18 1.1k
Renjie Jin United States 12 398 0.6× 295 0.9× 172 0.9× 89 0.5× 130 1.1× 22 636
Steven Kregel United States 14 616 1.0× 507 1.6× 256 1.3× 156 0.9× 254 2.2× 23 1.1k
Sarah Hawley United States 19 542 0.9× 444 1.4× 328 1.7× 139 0.8× 254 2.2× 29 1.3k
Jae‐Kyung Myung Austria 11 442 0.7× 381 1.2× 163 0.9× 151 0.9× 79 0.7× 22 765
Yi Zhu China 22 609 1.0× 343 1.1× 271 1.4× 234 1.3× 125 1.1× 75 1.2k
William E. Bingman United States 10 412 0.7× 360 1.1× 137 0.7× 325 1.8× 62 0.5× 11 710
Philip G. Febbo United States 8 644 1.0× 451 1.4× 265 1.4× 76 0.4× 215 1.9× 15 1.0k
Simon J. Baumgart Germany 16 672 1.1× 296 0.9× 191 1.0× 78 0.4× 255 2.2× 27 949
Beate C. Litzenburger United States 14 421 0.7× 168 0.5× 286 1.5× 108 0.6× 329 2.9× 23 770

Countries citing papers authored by Marko Laakso

Since Specialization
Citations

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

Fields of papers citing papers by Marko Laakso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marko Laakso

This figure shows the co-authorship network connecting the top 25 collaborators of Marko Laakso. A scholar is included among the top collaborators of Marko Laakso 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 Marko Laakso. Marko Laakso 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.
Cervera, Alejandra, Ville Rantanen, Kristian Ovaska, et al.. (2019). Anduril 2: upgraded large-scale data integration framework. Bioinformatics. 35(19). 3815–3817. 17 indexed citations
2.
Louhimo, Riku, et al.. (2016). Data integration to prioritize drugs using genomics and curated data. BioData Mining. 9(1). 21–21. 11 indexed citations
3.
Singh, Abhishek A., Amit Mandoli, Koen H.M. Prange, Marko Laakso, & Joost H.A. Martens. (2016). AML associated oncofusion proteins PML-RARA, AML1-ETO and CBFB-MYH11 target RUNX/ETS-factor binding sites to modulate H3ac levels and drive leukemogenesis. Oncotarget. 8(8). 12855–12865. 19 indexed citations
4.
Fleischer, Thomas, Jovana Klajic, Miriam R. R. Aure, et al.. (2016). DNA methylation signature (SAM40) identifies subgroups of the Luminal A breast cancer samples with distinct survival. Oncotarget. 8(1). 1074–1082. 16 indexed citations
5.
Englund, Johanna I., Topi A. Tervonen, Marko Laakso, et al.. (2015). Par6G suppresses cell proliferation and is targeted by loss-of-function mutations in multiple cancers. Oncogene. 35(11). 1386–1398. 19 indexed citations
6.
Louhimo, Riku, et al.. (2015). Identification of sample-specific regulations using integrative network level analysis. BMC Cancer. 15(1). 319–319. 9 indexed citations
7.
Louhimo, Riku, Viljami Aittomäki, Ali Faisal, et al.. (2013). Systematic use of computational methods allows stratification of treatment responders in glioblastoma multiforme. 1(2). 130–136. 1 indexed citations
8.
Hautaniemi, Sampsa & Marko Laakso. (2013). High-performance computing in biomedicine. 233–233.
9.
Louhimo, Riku, Marko Laakso, Tuomas Heikkinen, et al.. (2013). Identification of genetic markers with synergistic survival effect in cancer. BMC Systems Biology. 7(S1). S2–S2. 3 indexed citations
10.
Laakso, Marko, Ilja Ritamo, Olga Tatti, et al.. (2012). An optimized isolation of biotinylated cell surface proteins reveals novel players in cancer metastasis. Journal of Proteomics. 77. 87–100. 37 indexed citations
11.
Sahu, Biswajyoti, Marko Laakso, Päivi Pihlajamaa, et al.. (2012). FoxA1 Specifies Unique Androgen and Glucocorticoid Receptor Binding Events in Prostate Cancer Cells. Cancer Research. 73(5). 1570–1580. 187 indexed citations
12.
Sahu, Biswajyoti, Marko Laakso, Kristian Ovaska, et al.. (2011). Dual role of FoxA1 in androgen receptor binding to chromatin, androgen signalling and prostate cancer. The EMBO Journal. 30(19). 3962–3976. 296 indexed citations
13.
Heinonen, Mira, Annabrita Hemmes, Kaisa Salmenkivi, et al.. (2011). Role of RNA binding protein HuR in ductal carcinoma in situ of the breast. The Journal of Pathology. 224(4). 529–539. 39 indexed citations
14.
Ovaska, Kristian, Marko Laakso, Saija Haapa-Paananen, et al.. (2010). Large-scale data integration framework provides a comprehensive view on glioblastoma multiforme. Genome Medicine. 2(9). 65–65. 137 indexed citations
15.
Niittymäki, Iina, Alexandra E. Gylfe, Marko Laakso, et al.. (2010). High frequency of TTK mutations in microsatellite-unstable colorectal cancer and evaluation of their effect on spindle assembly checkpoint. Carcinogenesis. 32(3). 305–311. 13 indexed citations
16.
Laakso, Marko & Sampsa Hautaniemi. (2010). Integrative platform to translate gene sets to networks. Bioinformatics. 26(14). 1802–1803. 21 indexed citations
17.
Ovaska, Kristian, Marko Laakso, & Sampsa Hautaniemi. (2008). Fast Gene Ontology based clustering for microarray experiments. BioData Mining. 1(1). 11–11. 74 indexed citations
18.
Laakso, Marko. (2007). Computational Identification of Recessive Mutations in Cancers using High Throughput SNP-arrays. Työväentutkimus Vuosikirja.
19.
Laakso, Marko, Sari Tuupanen, Auli Karhu, et al.. (2007). Computational identification of candidate loci for recessively inherited mutation using high-throughput SNP arrays. Bioinformatics. 23(15). 1952–1961.
20.
Johansson, Gunnar, S.‐L. Karonen, & Marko Laakso. (1983). Reversal of an elevated plasma level of prolactin during prolonged psychological stress. Acta Physiologica Scandinavica. 119(4). 463–464. 25 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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