University of Cambridge
PhD, Cheminformatics, Centre for Molecular Informatics
2011 – 2015
University of Liverpool
MSc, Advanced Biological Sciences (Bioinformatics)
2009 – 2010
Trinity College Dublin
MSc, Computer Science (Interactive Entertainment Technology)
2008 – 2009
Aristotle University of Thessaloniki
BSc, Computer Science (Information Systems)
2003 – 2007
RTIN’s Cheminformatics & Bioinformatics Research Area covers research activities related to the application of machine learning, artificial intelligence and data science to the areas of chemistry, biochemistry, and biology to discover emerging patterns and acquire new information and increase our understanding in these fields. Topics of interest include traditional quantitative structure-activity relationships, mixture modeling, predictive toxicology, all the way to the analysis of protein sequences, using a variety of tools, statistical methods, algorithms and data integration.
Dr. Georgios Drakakis is currently the CEO of the in silico drug repurposing company Purposeful. He has worked as a research associate for 2.5 years at the National Technical University of Athens and one year at the University of Cambridge, after obtaining the Engineering and Physical Sciences Research Council Doctoral Prize. Georgios joined the American College of Greece in 2018, where he teaches Machine Vision and Semantic Web for the MSc in Data Science and Data Mining for the BSc in Information Technology. His research interests include methods for drug discovery and repurposing, machine learning, data mining, cheminformatics, computational chemistry and machine vision. Over the past few years, he has co-authored 13 original research publications in these fields and contributed to 2 book chapters.
Book Chapters
[1] Doganis P, Tsiliki G, Drakakis G, et al., Computational Modelling of Biological Responses to Engineered Nanomaterials. in (eds) Dhawan A., Anderson D. & Shanker R., Nanotoxicology: Experimental and Computational Perspectives (ISBN 9781782621584), RSC Publishing, 2017
[2] Perualila NJ, Shkedy Z, Ravindranath AC, Drakakis G, et al., Biclustering Methods in Chemoinformatics and Molecular Modeling. in (eds) Kasim A., Shkedy Z., Kaiser S., Hochreiter S. &Talloen W., Applied Biclustering Methods for Big and High-Dimensional Data Using R (ISBN 9781482208238), CRC Press, 2016
Journal Papers
[1] Drakakis G et al., Drug repurposing candidates against COVID-19, non-peer reviewed, available on Zenodo at <https://zenodo.org/record/3732347#.XpXJOcgzZPa> (2020)
[2] Drakakis G et al., Elucidating Compound Mechanism of Action and Predicting Cytotoxicity Using Machine Learning Approaches, Taking Prediction Confidence into Account., Curr Protocol Chem Biol 11, e73 (2019)
[3] Chomenidis C, Drakakis G, et al., Jaqpot Quattro: A novel computational web platform for modeling and analysis in nanoinformatics, J Chem Inf Model 57, 2161-2172, (2017)
[4] Drakakis G et al., Polypharmacological In Silico Bioactivity Profiling and Experimental Validation Uncovers Sedative-Hypnotic Effects of Approved and Experimental Drugs in Rat, ACS Chem Biol 12, 1593-1602 (2017)