BioMediTech Research Groups

Computational Biology Group

Group Leader: Professor Matti Nykter

matti.nykter(at)uta.fi

About Us

Computational Biology group develops algorithms and computational models to address biomedical research problems. The group’s aim is to uncover the molecular basis of human cancers and to generate new avenues for treatment and diagnostics. To reach this goal we integrate both experimental and computational expertise within our research group.

For more information, please visit the https://ruoho.uta.fi/wp/ site.

Research interests and expertise

Core competence of the group is in the methods of statistical modeling, machine learning and computer science. We often utilize a data-driven approach based on high-throughput genomic, epigenomic, transcriptomic and/or proteomic data. These data are analyzed computationally in an effort to better understand the biological processes and networks driving a disease or phenotype. The generated hypotheses are then validated and refined experimentally.

We work as a part of the Prostate Cancer Research Center (PCRC) and have set up a brain tumor research program in collaboration with Tampere University Hospital.

Achievements

We have

  • identified and characterized several oncogenic gene fusions, including FGFR3 rearrangements in glioblastoma and SKIL rearrangements in prostate cancer
  • identified new driver mechanisms, modeled tumor evolution and participated in characterization of polyclonal evolution in prostate cancer
  • identified biomarkers and driver mechanisms for cancer subtypes in different cancer types
  • used data from cell free DNA to characterize resistance mechanisms obtained during prostate cancer treatment
  • successfully commercialized our research by spin-off companies

Collaboration offer and requests

We are interested to collaborate on scientifically ambitious projects where computational methods can be used to extend the research beyond what is possible with a purely experimental approach.

Major Publications

  1. Annala M, Struss WJ, Warner EW, Beja K, Vandekerkhove G, Wong A, Khalaf D, Seppälä IL, So A, Lo G, Aggarwal R, Small EJ, Nykter M, Gleave ME, Chi KN, Wyatt AW. Treatment Outcomes and Tumor Loss of Heterozygosity in Germline DNA Repair-deficient Prostate Cancer. Eur Urol; 2017.
  2. Gundem G, Van Loo P, Kremeyer B, Alexandrov LB, Tubio JM, Papaemmanuil E, Brewer DS, Kallio HM, Högnäs G, Annala M, Kivinummi K, Goody V, Latimer C, O’Meara S, Dawson KJ, Isaacs W, Emmert-Buck MR, Nykter M, Foster C, Kote-Jarai Z, Easton D, Whitaker HC, Neal DE, Cooper CS, Eeles RA, Visakorpi T, Campbell PJ, McDermott U, Wedge DC, Bova GS. The evolutionary history of lethal metastatic prostate cancer. Nature 2015; 520(7547)353-7.
  3. Ylipää A, Kivinummi K, Kohvakka A, Annala M, Latonen L, Scaravilli M, Kartasalo K, Leppänen SP, Karakurt S, Seppälä J, Yli-Harja O, Tammela TL, Zhang W, Visakorpi T, Nykter M. Transcriptome Sequencing Reveals PCAT5 as a Novel ERG-Regulated Long Noncoding RNA in Prostate Cancer. Cancer Res 2015; 75(19):4026-31.
  4. Annala M, Kivinummi K, Leinonen K, Tuominen J, Zhang W, Visakorpi T, Nykter M. DOT1L-HES6 fusion drives androgen independent growth in prostate cancer. EMBO Mol Med. 2014 Jul 8;6(9):1121-1123.
  5. Liuksiala T, Teittinen KJ, Granberg K, Heinäniemi M, Annala M, Mäki M, Nykter M, Lohi O. Overexpression of SNORD114-3 marks acute promyelocytic leukemia. Leukemia. 2014 Jan;28(1):233-236.
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