George Kargas Email & Phone Number

Greece

Athens, Attiki, Greece

Research Assistant at Vakirlis Research Group.• Led a comprehensive bioinformatics analysis of long non-coding RNAs (lncRNAs) from 9 diverse organisms including human, mammals (rat, rhesus, cow), invertebrates (fruitfly, C. elegans), and plants (TPR, VVI, CRE), focusing on sequence characterization and evolutionary patterns in non-coding genomic regions.• Conducted extensive sequence analysis through the characterization of intergenic ORFs (iORFs) and small ORFs (sORFs), focusing on GC content patterns, sequence length distributions, and transmembrane domain predictions using Phobius, revealing significant species-specific patterns and evolutionary insights.• Performed sophisticated statistical analyses to identify structural and compositional patterns across species, including sequence property distributions, correlation analyses, and disease associations, demonstrating systematic differences between organisms and sequence types.

Vári, Attiki, Greece

Research Assistant at Moulos Research Group.• Integrated Machine Learning (ML) algorithms with the metaseqR2 package to enhance the accuracy and efficiency of differential gene expression analysis.• Evaluated the effectiveness of ML algorithms against the traditional PANDORA algorithm across various organisms, aiming to improve gene expression studies.• Managed the extraction, preprocessing, and analysis of extensive genomic datasets, transforming raw data into actionable biological insights.• Developed innovative computational methodologies that contribute to advancements in genomic research and improve overall analysis outcomes.

Athens, Attiki, Greece

Research assistant at Michalopoulos Laboratory | Computational Biology and Bioinformatics.• Conducted research focusing on identifying gene hubs in Arabidopsis thaliana through a combination of text mining, gene expression analysis, and machine learning algorithms. This involved extensive data preprocessing, feature extraction, and the application of clustering and classification models to uncover functional relationships between genes.• Utilized dimensionality reduction techniques such as PCA and t-SNE to visualize high-dimensional data, improving our understanding of complex biological interactions.• Developed machine learning pipelines in Python using libraries such as scikit-learn, TensorFlow, and Keras to automate the analysis and ensure reproducibility across multiple experiments.• Played a key role in the co-supervision of a graduate student's master's thesis on Parkinson's disease. In this project, I applied a variety of machine learning techniques, including support vector machines (SVM), random forests, and neural networks, to analyze patient data. The work involved building predictive models for disease progression, feature selection, and optimizing hyperparameters to improve model accuracy. Additionally, I collaborated in writing code for data preprocessing, model training, and evaluation.

Pisa, Tuscany, Italy

Research fellow at Raimondi group | Laboratorio di Biologia Bio@SNS.• Played a pivotal role in a groundbreaking project focusing on the dysregulation of GPCR ligand signaling systems across cancer transcriptomics datasets at the Raimondi Group, Laboratorio di Biologia Bio@SNS.• Tasked with extracting data from various databases, preprocessing this data, and preparing it for in-depth analysis to uncover new therapeutic opportunities in oncology.• Analyzed interaction networks of receptors, ligands, and biosynthetic enzymes to assess their impact on patient survival across cancer subtypes.• Contributed findings to a dedicated webapp, enhancing accessibility and understanding of GPCR signaling in cancer and identifying novel drug targets.• Honed skills in data engineering, analysis, and interpretation, contributing to advanced insights into cancer phenotypes and potential therapeutic strategies.

Vári, Attiki, Greece

Research intern at Pavlopoulos Lab | Bioinformatics and Integrative Biology.• Embarked on a rigorous endeavor to recreate and analyze protein families, closely mirroring methodologies utilized by the renowned Pfam database.• Deployed advanced bioinformatics algorithms and machine learning techniques for the meticulous classification of proteins into families based on structural and functional characteristics.• Gained profound insights into protein domain architecture, significantly contributing to the enrichment of our understanding of protein functions and their evolutionary relationships.• Enhanced the bioinformatics field by applying innovative approaches to protein family analysis, fostering a deeper comprehension of molecular biology and evolutionary studies.

Agia Paraskevi, Attiki, Greece

Master’s Thesis Research Associate in Computational Genetics, Software and Knowledge Engineering Laboratory.• Spearheaded a pioneering research project aimed at enhancing genetic therapies for Duchenne Muscular Dystrophy (DMD), leveraging cutting-edge CRISPR/Cas9 and prime editing techniques.• Developed an automated computational approach for the creation and evaluation of prime editing guide RNAs (pegRNAs), significantly advancing the precision and efficiency of genome editing methodologies.• Applied machine learning algorithms to predict the efficiency of pegRNAs, minimizing laboratory resources and expediting the identification of potential therapeutic candidates.• Collaborated with a multidisciplinary team of researchers, contributing to a groundbreaking study that has the potential to correct up to 89% of known genetic variants associated with Duchenne Muscular Dystrophy.• Published findings and methodologies that contribute significantly to the body of knowledge in genetic engineering, offering novel solutions for the treatment of muscular dystrophy.

Hinxton, England, United Kingdom

Research Intern at Petsalaki group | Whole Cell Signaling group.• Developed predictive models to identify key characteristics of drugs that suggest their potential to form effective drug synergy pairs.• Utilized comprehensive drug similarity data across 25 biological complexity levels from the Chemical Checker database (Duran-Frigola et al., 2020).• Integrated data with the extensive drug synergy database DrugCombDb (Liu et al., 2020) to enhance model accuracy and relevance.• Crafted unique drug similarity metrics, setting a new standard in the evaluation of drug interactions.• Correlated these newly developed drug similarity metrics with drug synergy scores, pinpointing specific features indicating a drug's compatibility for synergistic effects.• Contributed to the advancement of personalized medicine by identifying potential drug combinations that could lead to more effective treatments with reduced side effects.

Zográfos, Attiki, Greece

Master’s Thesis Research Associate in Computational Chemistry, School of Chemical Engineering, Unit of Process Control and Informatics.• Spearheaded the development and implementation of an advanced computational workflow for predicting the bioactivity of small molecules, emphasizing psychosis-related proteins.• Utilized state-of-the-art machine learning algorithms and chemogenomics approaches to analyze and predict drug-protein interactions, substantially reducing the time and cost associated with experimental testing.• Engaged in extensive data analysis, employing tools like KNIME and Python to process and interpret complex datasets, leading to the identification of novel drug targets and bioactive compounds.• Collaborated closely with a multidisciplinary team, contributing to a significant advancement in the field of computer-aided drug design (CADD) and systems biology.

Asprópirgos, Attiki, Greece

• Translated technical manuals from English to Greek and got familiar with the refinery's terminology• Evaluated the chemicals' supply and supervised the reserves

Pallíni, Attiki, Greece

• Training in GMP (Good Manufacturing Practices)• Training in the procedure of wet granulation and dry mixing• Training in the procedure of sugar coating and film coating• Quality control assistant , assistant in the operation of analytical techniques and machines like UV – spectrophotometer , HPLC , AA , IR , Dissolution Apparatus and Karl Fischer• Training in the microbiology department• Validation department assistant , temperature mapping of condition controlled spaces , assistant in the planned evaluation of production machines

Master Of Science - Ms, Information Systems And Services: Big Data And Analytics, 3.7/4.0

Core Modules: • Big Data and Analytics I: Techniques and Tools • Cloud computing with Hadoop • Machine Learning: Methods and Algorithms •.

Master Of Engineering - Meng, Chemical Engineering, 3.0/4.0

B.Eng. and M.Eng. (5-year joint degree, 300 ECTS), Chemical Engineering. Dissertation title: "Enrichment method for improving prediction.