Temporal data mining aims at finding patterns in historical data. Our work proposes an approach to extract temporal patterns from data to predict the occurrence of target events,...
Time series data poses a significant variation to the traditional segmentation techniques of data mining because the observation is derived from multiple instances of the same und...
Background: Motif patterns of maximal saturation emerged originally in contexts of pattern discovery in biomolecular sequences and have recently proven a valuable notion also in t...
Our dynamic graph-based relational mining approach has been developed to learn structural patterns in biological networks as they change over time. The analysis of dynamic network...
eraction networks. In this abstract, we extend this approach by mining functional flow patterns for the purpose of detecting small-sized modules for specific functions. Methods Our...