People:

Amoutzias GD

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

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Current Lab Members:

Marios Nikolaidis, PhD student since October 2020: Development of Bioinformatics tools and computational analyses for comparative genomics. In collaboration with Prof. Oliver, Cambridge University, UK, Prof. Van de Peer, VIB/UGent, Belgium, Dr. Balazs Papp, Biological Research Centre in Szeged. During his thesis and his stay in the Bioinformatics Laboratory (since he has been a first year undergraduate student), Mr Nikolaidis has already published 18 peer-reviewed papers, with six of them as first author (one of them in the prestigious journal Molecular Biology and Evolution) and has developed two published computational tools. Mr Nikolaidis has been the recipient of a Bodossakis MSc studentship and of a University of Thessaly PhD studentship (DEKA).

Panayotis Vlastaridis, former 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.

Undergraduate Theses completed:

  • Vergou A. 2022. Core genome analysis of Salmonella strains
  • Banti E. 2022. Core genome analysis of the Staphylococcus genus with Bioinformatics methods
  • Kapetanos D. 2022. Core genome analysis of E. coli strains with Bioinformatics methods
  • Fragkou N. 2022. Bionformatic and phylogenomic analysis of the core genome amongst members of the genus Streptomyces
  • Kalogianni G. 2022. Bioinformatics and Evolutionary Analysis of Glucose Carriers and Their Relationship with Species Adaptability
  • Kostopoulos K. 2022. Evolutionary and Bioinformatic analysis of Bacillus cereus group representatives
  • Sforou V. 2021. Evolutionary analysis of Adenoviruses using Bioinformatics methods
  • Bakoulas A. 2021. Evolutionary analysis of HPV16 using Bioinformatics methods
  • Bramis C. 2020. Evolutionary analysis of Coronaviruses using Bioinformatics Methods
  • Nikolaidis M. 2019. Development of a Bioinformatics tool for the identification and evolutionary classification of the eukaryotic MFS superfamily of sugar transporters
  • Pateraki G. 2019. Prediction of N-glycosylation sites with machine learning methods
  • Mpachoumis 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:

  • Makri S. 2022. Predicting post-translational modifications of proteins using machine learning methods
  • Nikolaidis M. 2021. Phylogenomic and comparative genomic analysis of the bacillus evolutionary group B. altitudinis - B. pumilus - B. safensis with bioinformatic 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
  • Tsionos G. 2018. Prediction of phosphorylation sites in rat proteins with machine learning methods
  • 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 and bioinformatics analyses of publicly available phosphoproteomics datasets
  • 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.