Marianthi Logotheti

Education:

2012-2016, PhD studies in Medical Science with a specialization in Biomedicine, Örebro University, Sweden • Title of Dissertation: Integration of Functional Genomics and Data Mining Methodologies in the Study of Bipolar Disorder and Schizophrenia

2004-2010, Diploma of Chemical Engineering, National Technical University of Athens, Direction: Food and Biotechnology

Previous Positions:

2011.06-2016.12, Metabolic Engineering and Bioinformatics Group, Institute of Biology, Medicinal Chemistry and Biotechnology in National Hellenic Research Foundation, Athens, Greece, Research Assistant

2010.09-2011.04, Laboratory of Enzyme and Synthetic Biotechnology, Institute of Biology, Medicinal Chemistry and Biotechnology in National Hellenic Research Foundation, Athens, Greece, Research Assistant

Current position:

2017.02-now, R&D engineer at Enios Applications Private Limited Company

Profile

PhD studies were performed with focus on psychiatric disorders and more specifically on schizophrenia and bipolar disorder. The related research activities included the use of skin fibroblast cell model, post-mortem brain data and blood for the study of major psychiatric disorders as non-invasive methods. Functional genomics and machine learning methodologies were used in order to elucidate underlying biological mechanisms and find biomarker gene panels. The current research interests include integrated solutions for Next Generation Sequencing data analysis, as well as the development of workflows coupled with interpretation analysis for biomarker discovery and target prioritization in diseases such as Parkinson’s disease.

List of activities

  • Experience in molecular biology experimental techniques such as cell culturing, RNA extraction from skin fibroblast cells and quantitative real-time polymerase chain reaction.
  • Analysis of high-throughput genomic data related to psychiatric disorders with the use of bioinformatic tools and programming languages.
  • Data mining and data analysis of transcriptomic data with the exploitation of machine learning algorithms.
  • Next Generation Sequencing data analysis and interpretation, focused on Whole Exome Sequencing – Variant calling.
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