Research Software Engineering
- Summary
- Optimization of scientific code to allow scientific breakthroughs.
Scientific research in the natural sciences today produces huge amounts of data. This data has to be processed computationally; unfortunately, the involved scientists often have neither the knowledge nor the time to optimize or accelerate their scientific code through parallelization.
RSE helps scientists improve and speed up their code by up to several orders of magnitude, making it possible to process much larger volumes of data in the same amount of time. As a result, the optimized programs may reveal more findings, produce better predictions, and enable insights that would be unattainable without RSE.
People
Jakub Yaghob
Collaborator
David Bednárek
Lecturer
Filip Zavoral
Scientific secretary, Lecturer
Miroslav Kratochvíl
Assistant professor
Latest publications
- Leveraging training expertise to build capacity in computational personalised medicine (2026)
- PrankWeb 4: a modular web server for protein--ligand binding site prediction and downstream analysis (2025)
- COBREXA 2: tidy and scalable construction of complex metabolic models (2025)
- Maboss for HPC environments: implementations of the continuous time Boolean model simulator for large CPU clusters and GPU accelerators (2024)
- FROG Analysis Ensures the Reproducibility of Genome Scale Metabolic Models (2024)
- Translational challenges of biomedical machine learning solutions in clinical and laboratory settings (2022)
- COBREXA.jl: constraint-based reconstruction and exascale analysis (2022)
- PrankWeb 3: accelerated ligand-binding site predictions for experimental and modelled protein structures (2022)
- Interrogating the effect of enzyme kinetics on metabolism using differentiable constraint-based models (2022)
- GPU-Accelerated Mahalanobis-Average Hierarchical Clustering Analysis (2021)
- ShinySOM: graphical SOM-based analysis of single-cell cytometry data (2020)
- GigaSOM.jl: High-performance clustering and visualization of huge cytometry datasets (2020)
- Generalized EmbedSOM on quadtree-structured self-organizing maps [version 2; peer review: 2 approved] (2020)
- Interoperable chemical structure search service (2019)
- Generalized EmbedSOM on quadtree-structured self-organizing maps (2019)
- PrankWeb: a web server for ligand binding site prediction and visualization (2019)
- MINERVA API and plugins: opening molecular network analysis and visualization to the community (2019)
- Sachem: a chemical cartridge for high-performance substructure search (2018)
- Player performance evaluation in team-based first-person shooter esport (2017)
- Data preprocessing of esport game records (2017)
