Amoutzias GD

Laboratory Director: Grigoris Amoutzias, Associate Professor of Bioinformatics with emphasis in Microbiology.

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Current Lab Members:

Panayotis Vlastaridis, PhD student: Organization and analysis of biological high-throughput data from multiple sources. In collaboration with Prof. Oliver, Cambridge University, UK, Prof. Van de Peer, VIB/UGent, Belgium, Dr Stratikos, Demokritos Research Center, Greece. Panos’ expertise is on database and web-front development. Technologies used: Java, Spring Framework, Angular, Matlab, Neo4j Graph Databases, Solr, MySQL, Linux.

Marios Nikolaidis, graduate student (Bodosaki fellow): Evolution of sugar transporters in eukaryotes.

Chrysoula Doudoumi, graduate student: Prediction of methylation and phosphorylation sites with Neural Networks.

Georgia Pateraki, graduate student: Prediction of N-glycosylation sites with machine learning methods

Previous Lab Members:

Athanasios Papakyriakou, Post-doctoral Researcher (2015-ARISTEIA II): In collaboration with Dr. Stratikos, Demokritos Research Center, Greece.

Alexandra Diakogeorgiou, undergraduate student: Evolution and Bioinformatics analyses of sugar transporters. Technologies used: Linux, Perl

Vicky Fliatoura, undergraduate student: Bioinformatics analysis of post-translational modification data. Technologies used: Linux, Perl.

Undergraduate Theses completed:

Nikolaidis N. 2019. Development of a Bioinformatics tool for the identification and evolutionary classification of the eukaryotic MFS superfamily sugar transporters.

Pateraki G. 2019. Prediction of N-glycosylation sites with machine learning methods.

Bachoumis G. 2019. BAC-TRECs: A Computational tool that detects recombination events among bacterial genomes.

Ntountoumi C. 2018. Bioinformatic analysis of Low Complexity Regions in prokaryotes.

Flatoura V. 2018. Prediction of methylation sites in eukaryotic proteins with machine learning algorithms.

Diakogeorgiou A. 2018. Bioinformatic and evolutionary analysis of the Major Facilitator Superfamily Sugar Transporters.

Tsimpidis M. 2014. Genomic and evolutionary analysis of human Enteroviruses with Bioinformatics methods.

Chaliotis A. 2012. Detection of microbial tRNA-synthetases with bioinformatics methods.

Postgraduate Theses completed:

Tsionos G. 2018. Prediction of phosphorylation sites in rat proteins with machine learning methods.

Spetsarias S. 2018. Development of a Bioinformatics protocol for genome analysis of microbes with toxicological and forensic interest, using Illumina and Pacific Biosciences technologies

Chaliotis A. 2017. The complex evolutionary history of aminoacyl-tRNA synthetases.

Tsimpidis M. 2016. T-RECS: Rapid and large-scale detection of recombination events among different evolutionary lineages of viral genomes

Kyriakidou P. 2016. Literature mining of phospho-proteomic data and bioinformatics analysis.

Tsouhlou P. 2015. Bioinformatics and evolutionary analysis of RNA-Sequencing data from Bivalvia.

Chalyvopoulou P. 2014. Bioinformatic analysis of microbial metagenomes from Next-Generation Sequencing data.

Sini C. 2013. Bioinformatics analysis of Human Exome data from Next-Generation Sequencing technologies.

Doxara A. 2012. Bioinformatics analysis of Mitochondrial gene networks and related diseases from Genomic and Systems Biology data.

In the Bioinformatics laboratory, undergraduate and postgraduate students learn to work primarily with Linux and Perl. Other programming languages may also be used, depending on the project and informatics expertise of the student, such as Java, Javascript, Python, Visual Basic, SQL, PHP, Graph Databases, Matlab. Student projects vary from analyzing large and diverse biological data (phylogenetics, phylogenomics, genomic recombination, RNA-Seq, High-throughput phosphoproteomic data) to developing computational tools (viral genotyping and recombination tools, protein motif detection, databases, prediction of phosphorylation sites with machine learning) or a combination of data analysis and software development.