Mining biomedical networks exploiting structure and background information

The overall research goal of this PhD project is to develop scalable data mining and machine learning methods using interaction data (i.e., drug-protein interactions, patients-drug interaction, patients-genes) integrated with background information. The fundamental contributions of this PhD project include the adaptation of existing, and the development of new machine learning techniques that 1) are able to efficiently exploit interaction data, and 2) are scalable and thus amenable to implementation on large computing clusters. The impact of this PhD project will be firstly, in the area of bioinformatics and medical technologies since the progress in understanding biological processes highly depends on the applied learning techniques and secondly, in the area of machine learning itself, since new learning algorithms for mining interaction data will be delivered. Moreover these techniques will be developed on an abstract level, which increases their applicability in other domains.

Jaar van publicatie:2019