Olli Yli-Harja, PhD

Affiliate Faculty

Professor, Tampere University of Technology Department of Signal Processing

Professor Olli Yli-Harja leads the computational systems biology (CSB) group in the Faculty of  Medicine and Health Technology at TUNI since 2002. His research group is composed of interdisciplinary backgrounds: signal processing, molecular biology, biotechnology, and computer science. He has more than 140 articles in peer reviewed scientific journals and has supervised 31 doctoral theses. The CSB group has developed many computational methods based on the understanding of the role of mathematical models in theoretical biology, rooted in complex systems theory. One of the notable achievements in the research field is the experimental verification of the self-organized criticality in the regulatory systems of yeast and mammalian cells (Rämö et al., 2006, Nykter et al., 2008). Improved understanding of the biological processes has led to many achievements within the CSB group, such as a large scale network model in yeast (Aho et el., 2010). We have created a methodology for integration of heterogeneous biological data in the context of cancer (Närvä et al., 2010). The team has developed computational methods and resources for stem cell research for the ESTOOL research consortium  (Kong et al.,2013). Furthermore, we have developed computational methods for large-scale data analysis for glioblastoma (Turner et al., 2015, Doan et al. 2020). Also, we have developed new  computational methods for microscopy, for validation and extraction of single cell information from cancer cells. We have widened the scope of research to new applications in health and psychology  (Emmert-Streib et al. 2019, Yang et al, 2020). 



P. Rämö, J. Kesseli, and O. Yli-Harja, Perturbation avalanches and criticality in gene regulatory  networks, Journal of Theoretical Biology, 242:164–170, May 2006. 

M. Nykter, N. D. Price, M. Aldana, S. A. Ramsey, S. A. Kau man, L. Hood, O. Yli-Harja, and I. f Shmulevich. Gene expression dynamics in the macrophage exhibit criticality, Proceedings of the  National Academy of Sciences USA, 105(6):1897–1900, 2008. 

T. Aho, H. Almusa, J. Matilainen, A. Larjo, P. Ruusuvuori, K.-L. Aho, T. Wilhelm, H. Lähdesmäki,  A. Beyer,M. Harju, S. Chowdhury, K. Leinonen, C. Roos, and O. Yli-Harja, Reconstruction and  validation of RefRec: a global model for the yeast molecular interaction network, PLoS ONE, 2010. 

L. Kong, K.-L. Aho, K. Granberg, R. Lund, L. Järvenpää, J. Seppälä, P. Gokhale, K. Leinonen, L.  Hahne, J. Mäkelä, K. Laurila, H. Pukkila, E. Närvä, O. Yli-Harja, P. W. Andrews, M. Nykter, R.  Lahesmaa, C. Roos, R. Autio, Reija, ESTOOLS Data@Hand: human stem cell gene expression  resource, Nature Methods, vol. 10(9), 814-815, (2013). 

K. Turner, Y. Sun, P. Ji, K. Granberg, B. Bernard, L. Hu, D. Cogdell, X. Zhou, O. Yli- Harja, M.  Nykter, I. Shmulevich, W. Yungd, G. Fuller, W. Zhang, Genomically amplified Akt3 activates DNA  repair pathway and promotes glioma progression, Proceedings of the National Academy of Sciences USA, vol. 112 no. 11, (2015). 

E. Närvä, R. Autio, N. Rahkonen, L. Kong, N. Harrison, D. Kitsberg, L. Borghese, J. Itskovitz Eldor, O. Rasool, P. Dvorak, O. Hovatta, T. Otonkoski, T. Tuuri, W. Cui, O. Brüstle, D. Baker, E.  MaltbY, H. Moore, N. Benvenisty, P. Andrews, O. Yli-Harja, R. Lahesmaa, High resolution DNA  analysis reveals loss of heterozygosity and copy number variation changes associated with culture  and affecting gene expression in human embryonic stem cell lines, Nature Biotechnology,  28(4):371–377, (2010).

P. Doan, A. Musa, A. Murugesan, V. Sipilä, N. Candeias, F. Emmert-Streib, P. Ruusuvuori, K.  Granberg, O. Yli-Harja, M. Kandhavelu, Glioblastoma Multiforme Stem Cell Cycle Arrest by  Alkylaminophenol through the Modulation of EGFR and CSC Signaling Pathways, CELLS, 2020.   

Z. Yang, M. Dehmer, O. Yli-Harja & F. Emmert-Streib, Combining deep learning with token  selection for patient phenotyping from electronic health records, Scientific Reports, 2020 

F. Emmert-Streib, O. Yli-Harja, M. Dehmer, Utilizing Social Media Data for Psychoanalysis to  Study Human Personality, Frontiers in Psychology, 2019

Computational Systems Biology

PhD, Computer science and applied mathematics, Lappeenranta University of Technology, Finland, 1989