Publicly available resources
A number of free online tools are currently under development, or have been developed, as part of ongoing research at the Department of Data Science and Knowledge Engineering.
Ariadne: A C++ library for formal verification of cyber-physical systems
Ariadne is a library for formal verification of cyber physical systems. In particular, it allows to model such systems as hybrid systems, focusing on nonlinear behavior. The library is written in C++ and it is distributed using Git on BitBucket under the GPLv3 license.
Ariadne is developed in collaboration with the University of Verona, Italy.
DTW4Omics: Comparing Patterns in Biological Time Series
Dynamic time warping is a method for calculating the best alignment between two sequences. By applying this to time courses from omics data we can find associations between variables which would normally be obscured by time. The tool compares the alignment from the real data with permuted data and hence allows you to estimate the significance of the alignment found.
DTW4Omics is implemented in R.
GeneSetPCA is a tool for overlaying information about sets of variables onto loadings plots generated from multi-variate models. For instance, you can use it to visualize which pathways (represented by sets of genes) are important within a PCA model of your gene expression data. In this way you can add additional interpretation to your PCA, PLS or other multivariate models.
GeneSetPCA is implemented as a Matlab GUI.
Ludii: General Game System
Ludii is a general game system designed to play, evaluate and design a wide range of games, including board games, card games, dice games, mathematical games, simple video games, and so on. Download the Ludii player to explore a growing database of games, test your AI search algorithms, and design your own games.
Ludii is being developed as part of the ERC-funded Digital Ludeme Project.
Singular Spectrum Decomposition (SSD)
Singular Spectrum Decomposition is an adaptive method for decomposing nonlinear and nonstationary time series in narrow-banded components. The method takes its origin from singular spectrum analysis (SSA), a nonparametric spectral estimation method used for analysis and prediction of time series. Unlike SSA, SSD is a decomposition method in which the choice of fundamental parameters has been completely automated.