Artificial Neural Networks in Action for an Automated Cell-Type Classification of Biological Neural Networks
Troullinou E., Tsagkatakis G., Chavlis S., Turi G.F., Li W., Losonczy A., Tsakalides P, and Poirazi P.
IEEE TETCI, 13 October 2020 | DOI: https://doi.org/10.1109/TETCI.2020.3028581​

Tags: 2020 , Interneurons , Machine Learning , Neuroscience

Large-Scale 3D Two-Photon Imaging of Molecularly Identified CA1 Interneuron Dynamics in Behaving Mice
Geiller, T, Vancura, V, …, Chavlis, …, S, Tsakalides, P, …, Poirazi, P Rózsa, BJ Losonczy, A
Neuron, 05 Oct 2020 | DOI: 10.1016/j.neuron.2020.09.013

Tags: 2020 , Interneurons , Machine Learning , Neuroscience , Spatial Navigation

A deep learning framework for neuroscience
Richards B.A., Lillicrap T.P., … Poirazi P. … Kording K.P.
Nature Neuroscience, 2019 | DOI: http://dx.doi.org/10.1038/s41593-019-0520-2

Tags: 2019 , Machine Learning , Neuroscience , Perspective , Structure-Function

A novel and simple spike sorting implementation
Petrantonakis P.C., Poirazi P.
IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2016 Dec., DOI: 10.1109/TNSRE.2016.2640858

Tags: 2016 , Machine Learning , Neuroscience , Spike Sorting

Dentate Gyrus Circuitry Features Improve Performance of Sparse Approximation Algorithms
Petrantonakis, P.C. and Poirazi, P.
PLoS One. 2015; 10(1): e0117023.  doi: 10.1371/journal.pone.0117023

Tags: 2015 , Hippocampus , Machine Learning , Neuroscience

Improved grading and survival prediction of human astrocytic brain tumors by artificial neural network analysis of gene expression microarray data
Petalidis, L.P., Oulas, A., Backlund, M., Wayland, M.T., Liu, L., Plant, K., Happerfield, L., Freeman, T.C., Poirazi, P., Collins, V.P.
Mol Cancer Ther. 2008 May;7(5):1013-24. doi: 10.1158/1535-7163.MCT-07-0177

Tags: 2008 , Bioinformatics , Machine Learning

Towards predicting persistent activity of neurons by statistical and fractal dimension-based features
Petrantonakis, P.C., Papoutsi, A., Poirazi, P.
The 2013 International Joint Conference on Neural Networks (IJCNN), Dallas, TX, 4-9 August, 2013. doi: 10.1109/IJCNN.2013.6707083

Tags: 2013 , Machine Learning , Neuroscience

Modeling regulatory cascades using Artificial Neural Networks: the case of transcriptional regulatory networks shaped during the yeast stress response
Manioudaki, M.E., Poirazi, P.
Front Genet. 2013 Jun 20;4:110. doi: 10.3389/fgene.2013.00110

Tags: 2013 , Bioinformatics , Machine Learning

MatureBayes: a probabilistic algorithm for identifying the mature miRNA within novel precursors
Gkirtzou, K., Tsamardinos, I., Tsakalides, P., Poirazi, P.
PLoS One. 2010 Aug 6;5(8):e11843. doi: 10.1371/journal.pone.0011843

Tags: 2010 , Bioinformatics , Machine Learning

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, M.D., Aktypis, A., De Vuyst, L., Tsakalidou, E.
Appl Environ Microbiol. 2007 Feb;73(3):768-76. doi: https://doi.org/10.1128/aem.01721-06

Tags: 2007 , Bioinformatics , Machine Learning

Classification Capacity of a Modular Neural Network Implementing Neurally Inspired Architecture and Training
Poirazi, P., Neocleous, C., Pattichis, C.S., Schizas, C.N.
IEEE Trans Neural Netw. 2004 May;15(3):597-612. DOI: 10.1109/TNN.2004.826225

Tags: 2004 , Dendrites , Learning and Memory , Machine Learning

Pyramidal Neuron as 2-Layer Neural Network.
Poirazi, P., Brannon, T., Mel, B.W.
Neuron. 2003 Mar 27;37(6):989-99. DOI: 10.1016/s0896-6273(03)00149-1

 

Tags: 2003 , Biophysical Model , CA1 , Dendritic Computations , Hippocampus , Machine Learning , Neural Computations , Neuroscience , Single Neuron Model

Impact of Active Dendritic Processing and Structural Plasticity on Learning and Memory
Poirazi, P., Mel, B.W.
Neuron. 2001 Mar;29(3):779-96. DOI: 10.1016/s0896-6273(01)00252-5

 

Tags: 2001 , Dendrites , Dendritic Computations , Dendritic Plasticity , Learning and Memory , Machine Learning , Neural Computations , Structure-Function

Choice and value flexibility jointly contribute to the capacity of a subsampled quadratic classifier.
Poirazi, P, Mel, B.W.
Neural Comput. 2000 May;12(5):1189-205. DOI: 10.1162/089976600300015556

Tags: 2000 , Dendrites , Dendritic Computations , Learning and Memory , Machine Learning , Neuroscience