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Panayiota Poirazi
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.
Sidiropoulou, K. and Poirazi, P. (2012) Predictive Features of Persistent Activity Emergence in Regular Spiking and Intrinsic Bursting Model Neurons. PLoS Comput Biol 8: e1002489. doi:10.1371/journal.pcbi.1002489
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.
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.
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.
Poirazi, P. Brannon, T. & Mel, B.W. (2003) Pyramidal Neuron as 2-Layer Neural Network. Neuron/37: 989-999.
Journal Publications
2016
Poirazi, P., Belin, D., Gräff, J., Hanganu‐Opatz, I., and López‐Bendito, G. “Balancing family with a successful career in neuroscience”. European Journal of Neuroscience, 2016. | http://dx.doi.org/10.1111/ejn.13280
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Bozelos, P., Stefanou, S.S., Bouloukakis, G., Melachrinos, C., Poirazi, P., “REMOD: A Tool for Analyzing and Remodeling the Dendritic Architecture of Neural Cells:, Front. Neuroanat., 06 January 2016 | http://dx.doi.org/10.3389/fnana.2015.00156
2015
P.C. Petrantonakis, P.Poirazi, ”Dentate Gyrus Circuitry Features Improve Performance of Sparse Approximation Algorithms”, PLoS ONE
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2014
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2013
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Manioudaki ME and Poirazi P
Modeling regulatory cascades using Artificial Neural Networks: the case of transcriptional regulatory networks shaped during the yeast stress response.
Front. Genet. 4:110. doi: 10.3389/fgene.2013.00110
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A. Papoutsi, G. Kastellakis, M. Psarrou, S. Anastasakis, P. Poirazi.
Coding and Decoding with Dendrites
Journal of Physiology-Paris doi:10.1016/j.jphysparis.2013.05.003.
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Romani, A., Marchetti, C., Bianchi, D., Leinekugel, X., Poirazi, P., Migliore, M., Marie, H.
Computational modeling of the effects of amyloid-beta on release probability at hippocampal synapses.
Frontiers in Computational Neuroscience, January 2013; doi: 10.3389/fncom.2013.00001
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2012
2011
Gómez González JF, Mel BW, Poirazi P.
Distinguishing Linear vs. Non-Linear Integration in CA1 Radial Oblique Dendrites: It’s about Time.
Frontiers in Computational Neuroscience. 2011 November 14 ;5:44.
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Tzamali E, Poirazi P, Tollis IG, Reczko M.
A computational exploration of bacterial metabolic diversity identifying metabolic interactions and growth-efficient strain communities.
BMC Syst Biol. 2011 Oct 18;5:167.
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Oulas, A, Karathanassis N., Luloupi, A. and Poirazi, P.
Finding cancer-associated miRNAs: methods and tools
Molecular Biotechnology, DOI: 10.1007/s12033-011-9416-4, June 2011.
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2010
Pissadaki E.K., Sidiropoulou K., Reczko M., and Poirazi P.
Encoding of Spatio-temporal Input Characteristics by a CA1 Pyramidal Neuron Model.
PLoS Computational Biology 2010 Dec;6(12): e1001038.
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Gkirtzou K, Tsamardinos I, Tsakalides P, Poirazi P.
MatureBayes: a probabilistic algorithm for identifying the mature miRNA within novel precursors.
PLoS One 2010 Aug;5(8). pii: e11843
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Shilyansky C, Karlsgodt KH, Cummings DM, Sidiropoulou K, Hardt M, James AS, Ehninger D, Bearden CE, Poirazi P, Jentsch JD, Cannon TD, Levine MS, Silva AJ.
Neurofibromin regulates corticostriatal inhibitory networks during working memory performance.
Proc Natl Acad Sci U S A. 2010 Jul;107(29):13141-6.
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2009
Zhou Y, Won J, Karlsson MG, Zhou M, Rogerson T, Balaji J, Neve R, Poirazi P, Silva AJ.
CREB regulates excitability and the allocation of memory to subsets of neurons in the amygdala.
Nature Neuroscience 2009 Nov;12(11):1438-43.
[Abstract] [PDF]
Oulas A, Boutla A, Gkirtzou K, Reczko M, Kalantidis K and Poirazi P
Prediction of novel microRNA genes in cancer-associated genomic regions–a combined computational and experimental approach.
Nucleic Acids Research 2009 Jun;37(10):3276-87.
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Oulas A, Reczko M and Poirazi P.
MicroRNAs and Cancer-the search begins!
IEEE Trans Inf Technol Biomed. vol. 13, No 1, pg. 67-77, Jan 2009.
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2008
Petalidis LP, Oulas A, Backlund M, Wayland MT, Liu L, Plant K, Happerfield L, Freeman TC, Poirazi P, Collins VP.
Improved grading and survival prediction of human astrocytic brain tumors by artificial
neural network analysis of gene expression microarray data.
Molecular Cancer Therapeutics (on the cover) vol. 7, No 5, pg. 1013-1024, May 2008.
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Liebmann L, Karst H, Sidiropoulou K, van Gemert N, Meijer OC, Poirazi P, Joels M.
Differential effects of corticosterone on the slow afterhyperpolarization in the
basolateral amygdala and CA1 region: possible role of calcium channel subunits.
Journal of Neurophysiology vol. 99, No 2, pg. 958-968, Feb. 2008.
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2007
Poirazi, P., Leroy, F., Georgalaki, M.D., Aktypis, A., De Vuyst, L., and Tsakalidou, E.
Use of artificial neural networks and a gamma-concept-based approach to model growth of and bacteriocin production
by Streptococcus macedonicus ACA-DC 198 under conditions simulating Kasseri cheese technology.
Applied Environmental Microbiology vol. 73, No 3, pg. 768-776, Feb. 2007.
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Pissadaki, E.K. and Poirazi P.
Modulation of excitability in CA1 pyramidal neurons via the interplay of EC and CA3 inputs.
Neurocomputing, Special Issue for CNS 2006, vol. 70, No 11-12, pg. 1735-1740, June 2007.
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Sidiropoulou K., Joels M., and Poirazi P.
Modeling stress-induced adaptations in Ca++ dynamics.
Neurocomputing, Special Issue for CNS 2006, vol. 70, No 11-12, pg. 1640-1644, June 2007.
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2006
Pavlidis P. and Poirazi P.
Individualized markers optimize class prediction of microarray data.
BMC Bioinformatics, vol. 7, pg. 345-359, July 2006.
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Sidiropoulou K., Pissadaki E.K., and Poirazi P.
Inside the brain of a neuron.
EMBO Reports, vol. 7, pg. 886-892, September 2006.
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2005
Markaki M., Orphanoudakis S. and Poirazi P.
Modelling reduced excitability in aged CA1 neurons as a calcium-dependent process.
Neurocomputing, vol. 65-66, pg. 305-314, June 2005.
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2004
Poirazi, P. Neocleous, C., Pattichis, C. and Schizas, C.
Classification Capacity of a Modular Neural Network Implementing Neurally Inspired Architecture and Training.
IEEE Transactions in Neural Networks, vol 15, No. 3, pg. 597-612, May 2004.
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2003
Poirazi, P. Brannon, T. and Mel, B.W.
Arithmetic of Subthreshold Synaptic Summation in a Model CA1 Pyramidal Cell.
Neuron, vol 37, pg. 977-987, March 2003.
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Poirazi, P. Brannon, T. and Mel, B.W.
Pyramidal Neuron as 2-Layer Neural Network.
Neuron, vol 37, pg. 989-999, March 2003.
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Poirazi, P. Brannon, T. and Mel, B.W.
About the Model (online supplement)
Neuron, vol 37, pg. 988, March 2003.
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1999-2001
Poirazi, P. and Mel, B.W.
Impact of Active Dendritic Processing and Structural Plasticity on Learning and Memory.
Neuron, vol 29, pg. 779-796, March 2001.
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Poirazi, P. and Mel, B.W.
Choice and value flexibility jointly contribute to the capacity of a subsampled quadratic classifier.
Neural Computation, vol. 12, num. 5, pg. 1189-1207, 2000.
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Poirazi, P. and Mel, B.W.
Towards the Memory Capacity of Neurons with Active Dendrites.
Neurocomputing, vol. 26-27, pg. 237-245, 1999.
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