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Imperial College London
PhD, Department of Mathematics
2003 – 2007
University College London
MSc in Statistics
2001 – 2002
University of Piraeus
BSc in Statistical and Actuarial Sciences
1996 – 2000
Biostatistics is the application of statistical methodologies and data analytics to the fields of biological sciences and medicine. In an era of emerging data sets, from genome sequencing to electronic medical records, new statistical tools are often needed to interpret massive amounts of data and detect correlations, patterns and causations.
RTIN’s Biostatistics Research Area covers activities related to genome-wide association studies and next-generation sequencing, statistical genetics, missing data, integration of analytic tools, Bayesian methods, and computationally-intensive methods. Areas of application include bioinformatics, computational biology, the environment, genetics, transcriptomics, among other areas.
Future directions of interest include sampling-based designs and analysis approaches for generalizing the results of case-control and cohort studies, sampling for disease screening or prevalence estimations, development and validation of models for minority populations, and evaluating the potential utility of genetic and other biomarkers in specific pathologies.
Dr Georgia Tsiliki is a biostatistician with research experience in bioinformatics as well as systems toxicology areas. She holds a BSc degree in Statistics and Actuarial Science from the University of Piraeus, Greece and a Master of Science degree in Statistics from the University College London, UK. She received her PhD in Statistics from the Department of Mathematics, Imperial College of Science, Technology and Medicine, where her main focus was on pattern recognition across different genotypic populations. Dr Tsiliki has joined The American College of Greece in 2018, where she teaches Statistics and Applied Statistics courses. She has major experience in data analysis techniques and statistical applications for large data processing and serves as the PI of two H2020 European projects. Her main interests are bioinformatics, systems toxicology, computational biology, genetics, transcriptomics analysis
Doganis P, Tsiliki G, Drakakis G, Chomenidis Ch, Sarimveis H, Nymark P, Kohonen P, Grafstrom R, Abdelaziz A, Farcal L, Exner T, Hardy B (2017) Computational Modeling of Biological Responses to Engineered Nanomaterials (Chapter 11), In: Nanotoxicology: Experimental and Computational Perspec- tives, Ed. Dhawan A, RCS, DOI: 10.1039/9781782623922-00276.
Arhondakis S, Tsiliki G, Kossida S (2011) Monitoring the Transcriptome (Chapter 6), In: Digital Forensics for the Health Sciences: Applications in Practice, Ed. Daskalaki A, IGI Global, DOI: 10.4018/978-1-60960-483-7.
Journal Papers (Appeared / accepted)
 Drakakis G, Chomenidis C, Dokoumetzidis A, Tsiliki G (2020) Drug repurposing candidates against COVID-19, non-peer reviewed, available on Zenodo at <https://zenodo.org/record/3732347#.XpXJOcgzZPa>
 Basei G, Hristozov D, Lamon L, Zabeo A, Jeliakova N, Tsiliki G, Marcomini A, Torsello A (2019) Making use of available and emerging data to predict the hazards of engineered nanomaterials by means of in silico tools: A critical review. Nanoimpact, doi: 10.1016/j.impact.2019.01.003
 Varsou DD, Tsiliki G, Nymark P, Kohonen P, Sarimveis H (2017) toxFlow: a shiny application for predicting toxicity with omics data. J Chem Inf Model, doi: 10.1021/acs.jcim.7b00160.
 Tsiliki G, Nymark P, Kohonen P, Grafstrom R, Sarimveis H (2017) Enriching nanomaterials omics data: an integration technique to generate biological descriptors. Small Methods, doi:10.1002/smtd.201700139.