Panayiota Poirazi, Ph.D.

Research Associate Professor

Computational Biology Laboratory

Institute of Molecular Biology and Biotechnology (IMBB)

Foundation of Research and Technology-Hellas (FORTH)




Research Interests


My research interests lie in the field of computational biology with a focus on the development and application of in computo modelling techniques for the investigation of neural and gene functions. In my lab we develop computational methods and tools for (a) analyzing large-scale gene expression data related to human cancer in search for gene markers and disease sub-categories, (b) identifying regulatory elements such as miRNA precursors and their targets in whole genomes of plants and mammals, (c) building theoretical models of gene regulatory networks, and (d) modeling healthy and degenerated brain cells and neural networks in order to relate learning and memory capacity with biophysical and/or morphological properties. Our methodological approaches include (a) novel clustering and feature selection algorithms, (b) machine learning algorithms such as artificial neural networks, hidden Markov models etc, (c) detailed biophysical and/or simplified models of neurons and neural networks and (d) theoretical analysis and abstract mathematical modeling.


Selected Publications

1.                  Shilyansky, C, Karlsgodt, KH, Cummings, D, Sidiropoulou, K, Hardt, M, James, AS, Ehninger, D, Bearden, CE, Poirazi, P, Jentsch, D, Cannon, TD, Levine, MS, Silva, AJ. (2010) Increased corticostriatal inhibition underlies working memory deficits in Neurofibromatosis type I. Proc Natl Acad Sci USA 107: 13141-6.

2.                  Zhou Y, Won J, Karlsson MG, Zhou M, Rogerson T, Balaji J, Neve R, Poirazi P, Silva AJ. (2009) CREB regulates excitability and the allocation of memory to subsets of neurons in the amygdala. Nature Neuroscience 12: 1438-43.

3.                  Oulas, A. Boutla, A. Gkirtzou, K. Reczko, M. Kalantidis, K. and Poirazi, P. (2009) Prediction of novel microRNA genes in cancer associated genomic regions: a combined computational and experimental approach. Nucleic Acid Research 7: 3276-3287.

4.                  Petalidis, L.P., Oulas, A.,Wayland, M.T., Liu, L., Plant, K., Happerfield, L., Renault-Mihara, F., Freeman, T.C., Poirazi, P., & Collins, P.V. (2008) Grading of human astrocytic brain tumours by artificial neural network analysis of gene expression microarray data. Mol Cancer Ther. 7: 1013-24.

5.                  Poirazi, P. Brannon, T. & Mel, B.W. (2003) Pyramidal Neuron as 2-Layer Neural Network. Neuron/37: 989-999.