REMOD: A Tool for Analyzing and Remodeling the Dendritic Architecture of Neural Cells
Bozelos P, Stefanou SS, Bouloukakis G, Melachrinos C, Poirazi P
Frontiers in Neuroanatomy, January 2016 | DOI: 10.3389/fnana.2015.00156
A Simple Method to Simultaneously Detect and Identify Spikes from Raw Extracellular Recordings
Petrantonakis PC, Poirazi P
Frontiers in Neuroscience, Dec 2015 | DOI: 10.3389/fnins.2015.00452
Emerging applications of read profiles towards the functional annotation of the genome
Pundhir S, Poirazi P, Gorodkin J
Frontiers in Genetics, May 2015 | DOI: 10.3389/fgene.2015.00188
MiRduplexSVM: A High-Performing MiRNA-Duplex Prediction and Evaluation Methodology
Karathanasis N, Tsamardinos I, Poirazi P
PLoS One, May 2015 | DOI: 10.1371/journal.pone.0126151
Oulas A, Karathanasis N, Louloupi A, Pavlopoulos GA, Poirazi P, Kalantidis K, Iliopoulos I
Prediction of miRNA Targets. In: Picardi E (eds) RNA Bioinformatics: Methods in Molecular Biology, vol. 1269, pp. 207-229. Humana Press, New York, NY (2014) | DOI: 10.1007/978-1-4939-2291-8_13
GluA2 mRNA distribution and regulation by miR-124 in hippocampal neurons
Ho VM, Dallalzadeh LO, Karathanasis N, Keles MF, Vangala S, Grogan T, Poirazi P, Martin KC
Molecular and Cellular Neuroscience, Jul 2014 | DOI: 10.1016/j.mcn.2014.04.006.
Don’t use a cannon to kill the … miRNA mosquito
Karathanasis N, Tsamardinos I, Poirazi P
Bioinformatics, Mar 2014 | DOI: 10.1093/bioinformatics/btu100.
Modeling regulatory cascades using Artificial Neural Networks: the case of transcriptional regulatory networks shaped during the yeast stress response
Manioudaki ME, Poirazi P
Frontiers in Genetics, Jun 2013 | DOI: 10.3389/fgene.2013.00110
SVM-Based miRNA:miRNA* Duplex Prediction
Karathanassis N, Armen A, Tsamardinos I, Poirazi P
IEEE 12th International Conference on Bioinformatics & Bioengineering (BIBE), Larnaca Cyprus, 11-13 November, 2012 | DOI: 10.1109/BIBE.2012.6399670
A new microRNA target prediction tool identifies a novel interaction of a putative miRNA with CCND2
Oulas A, Karathanasis N, Louloupi A, Iliopoulos I, Kalantidis K, Poirazi P
RNA Biology, Sep 2012 | DOI: 10.4161/rna.21725
A computational exploration of bacterial metabolic diversity identifying metabolic interactions and growth-efficient strain communities
Tzamali E, Poirazi P, Tollis IG, Reczko M
BMC Systems Biology, Oct 2011 | DOI: 10.1186/1752-0509-5-167
Finding cancer-associated miRNAs: Methods and Tools
Oulas A, Karathanasis N, Louloupi A, Poirazi P
Molecular Biotechnology, May 2011 | DOI: 10.1007/s12033-011-9416-4
Oulas A, Poirazi P
Utilization of SSCprofiler to Predict a New miRNA Gene. In: Wu W (eds) MicroRNA and Cancer. Methods in Molecular Biology (Methods and Protocols), vol. 676, pp. 243-252. Humana Press, Totowa, NJ (2010) | DOI: 10.1007/978-1-60761-863-8_17
Oulas A, Karathanasis N, Poirazi P
Computational identification of miRNAs involved in cancer. In: Wu W. (eds.) MicroRNAs and Cancer. Methods in Molecular Biology (Methods and Protocols), vol. 676, pp. 23-41. Humana Press, Totowa, NJ (2010). DOI: 10.1007/978-1-60761-863-8_2
MatureBayes: a probabilistic algorithm for identifying the mature miRNA within novel precursors
Gkirtzou K, Tsamardinos I, Tsakalides P, Poirazi P
PLoS One, Aug 2010 | DOI: 10.1371/journal.pone.0011843
Manioudaki M, Tzamali E, Reczko M, Poirazi P
Methods for structural inference and functional module identification in intracellular networks. In: Krawetz S. (eds) Bioinformatics for Systems Biology, pp. 517-539. Humana Press (2009) | DOI: 10.1007/978-1-59745-440-7_27
Tzamali E, Poirazi P, Reczko M
Methods for Dynamical Inference in Intracellular Networks. In: Krawetz S. (eds) Bioinformatics for Systems Biology. Humana Press (2009) | DOI: 10.1007/978-1-59745-440-7_28
Prediction of novel microRNA genes in cancer-associated genomic regions–a combined computational and experimental approach
Oulas A, Boutla A, Gkirtzou K, Reczko M, Kalantidis K, Poirazi P
Nucleic Acids Research, Mar 2009 | DOI: 10.1093/nar/gkp120
MicroRNAs and Cancer-the search begins!
Oulas A, Reczko M, Poirazi P
IEEE Transactions on Information Technology in Biomedicine, Jan 2009 | DOI: 10.1109/TITB.2008.2007086
Improved grading and survival prediction of human astrocytic brain tumors by artificial neural network analysis of gene expression microarray data
Petalidis LP, Oulas A, Backlund M, Wayland MT, Liu L, Plant K, Happerfield L, Freeman TC, Poirazi P, Collins VP
Molecular Cancer Therapeutics, May 2008 | DOI: 10.1158/1535-7163.mct-07-0177
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
Poirazi P, Leroy F, Georgalaki MD, Aktypis A, De Vuyst L, Tsakalidou E
Applied and Environmental Microbiology, Feb 2007 | DOI: https://doi.org/10.1128/aem.01721-06
Individualized markers optimize class prediction of microarray data
Pavlidis P, Poirazi P
BMC Bioinformatics, Jul 2006 |DOI: 10.1186/1471-2105-7-345