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This project explores and implements robust relational data models for efficiently storing and querying large-scale genetic Variant Call Format (VCF) data. Leveraging PostgreSQL, we present and evaluate eight distinct schema designs, demonstrating how traditional relational databases can offer competitive performance, scalability, and full database management system (DBMS) features for complex genomic workloads, complementing specialized tools like BCF Tools and TileDB-VCF.

EAGLES: Preliminary Recommendations on Spoken Texts.

Backend Docker Compose app featuring PostgreSQL, Ontop, LodView, and NGINX serving the frontend (production SPARQL endpoint, staging SPARQL endpoint)

vhi operational

Text Normalization on Learner Texts (South Tyrolean German as a L2)

EPLANopt (EnergyPLAN Optimization) is a script to run a genetic optimization for the EnergyPLAN software (http://www.energyplan.eu/) based on the DEAP (Distributed Evolutionary Algorithms in Python - http://deap.readthedocs.org/).