The software packages are made available solely for research and educational purposes.
If you wish to use it for other purposes, you must contact the authors for permission.

  • bicpams: exploratory and unsupervised analysis of tabular and network data, integrating state-of-the-art contributions on pattern-based biclustering (see BMC’18 publication)
  • iluapp: recommendation system for the context-aware analysis of urban data
  • data2help: platform the descriptive and predictive analysis of emergency occurrences in Portugal
  • autoMTS: autonomous time series processing in sensor networks (see QShine’20 publication)
  • e2pat: emerging pattern discovery from heterogeneous spatiotemporal data (see MobiQuituous’20 publication)
  • schizoeeg: brain signal classification using pairwise learning for schizophrenia diagnosis (see AI in Medicine’20 publication)
  • di2: prior-free and multi-item discretization of biological data (see BMC’21 publication)
  • wisdomapp: platform for multivariate time series analysis and anomaly detection in water distribution systems (see Wate’21)
  • eeg2bold: deep neural networks for EEG to fMRI synthesis
  • rDenoiser: imputation in spatiotemporal data using recurrent denoiser
  • avatar: algorithms integrated within GINsim to find probability estimates of attractor reachability in asynchronous logical models (see FPhys’18 publication)
  • bsig: method to assess the statistical significance of flexible biclustering solutions (see DAMI’17 publication)
  • uOPPM : algorithm to find order-preserving pattern matches over indeterminate strings (see CPM’18 publication)
  • flebic: associative classifiers using discriminative biclusters with flexible properties (under publication)
  • bigen: generator of synthetic data to plant biclusters with parameterizable coherence (type and strength), structure (number, size and positioning) and quality (under publication)
  • bip: flexible plaid models for an effective discovery of complex structures of biclusters with meaningful overlaps (see TCBB’15 publication)
  • bicspam: pattern-based approaches for flexible, efficient and robust order-preserving biclustering based on sequential patterns (see BMC’14 publication)
  • bicpam: pattern-based approach to discover biclusters with multiple patterns of expression, varying quality and alternative underlying structures (see AMB’14 publication)
  • evoc: framework for multi-period classifiers sensitive to temporal patterns (see DAMI’14a and ICIS’12 publications)
  • hi-spm: adapted multivariate hidden Markov models to perform sequential pattern discovery over transactional data (see DAMI’14b and ICIS’14 publications)
  • indexspan efficient discovery of sequential patterns in item-indexable sequences (see nfMCP’13 publication)
  • fine-ally: software, collected data, MBTI tests and statistical results for the emotion-driven interactions (see PhyCS’14 and ACII’13 publications)
  • pmsat: codifications of the frequent itemset problem using propositional satisfiability with performance-enhancing criteria (see this report)
  • edapm: miner of physiological signals using symbolic approximation and HMM-based pattern discovery (see AAMAS’12 publication)