Finding cancer genes in copy number data and insertional mutagenesis data

Cancer is a genetic disease. Step-wise alteration of genes that have a normal function in the cell can lead to the transformation of a healthy cell into a malignant cancer cell. Cancer genes provide several traits to the cell that allow it to become malignant. These traits have been researched for many years, and currently one knows quite well...

Personalised Access to Social Media

On many websites users can personally contribute information, ranging from short text messages to photos and videos. Users can see the information contributed by others and respond to it. These social media actively engage their community in the structuring of the collection by making use of collaborative annotation methods. Next to an improved...

Ant Colony Optimization for Control

The very basis of this thesis is the collective behavior of ants in colonies. Ants are an excellent example of how rather simple behavior on a local level can lead to complex behavior on a global level that is beneficial for the individuals. The key in the self-organization of ants is communication through pheromones. When an ant forages for...

Efficient Identification of Timed Automata: Theory and practice

This thesis contains a study in a subfield of artificial intelligence, learning theory, machine learning, and statistics, known as system (or language) identification. System identification is concerned with constructing (mathematical) models from observations. Such a model is an intuitive description of a complex system. One of the main nice...

Learning to recognise: A study on one-class classification and active learning

The thesis treats classification problems which are undersampled or where there exist an unbalance between classes in the sampling. The thesis is divided into three parts. The first two parts treat the problem of one-class classification. In the one-class classification problem, it is assumed that only examples of one of the classes, the target...

Fuzzy Probabilistic Learning and Reasoning, Rule Induction for Decision-Support Systems in Exacting Environments