• Nowe, Ann (Administrative Promotor)
  • Hugues, Bersini (Coördinator)


Many experiments investigating gene expression at the genome-wide scale need to be performed only once and can then be turned into in silico assays. An in silico assay is the combination of a genome-wide database and a dedicated data mining tool to query it with a gene or a group of genes. We propose to develop know-how in in silico assay design that will lay the foundation of a spin-off providing services to the drug and biotech industry R&D.
It must be recognized that most biology-oriented computational tools developed by the engineering community are seldom known and used by bench biologists. Although multiple factors contribute to this, we believe many computational tools failed to grasp the attention of a large community of scientists because they lack a landmark application that strikingly demonstrates their relevance, establishes their credibility, and brings visibility. We will develop and demonstrate our know-how through the development of two in silico assays with high stakes in cancer research. The feasibility of both assays is backed by proof-of-principle studies.
The first assay will determine whether a group of genes is associated with cancer aggressiveness. This assay will rely on the development of new ICT tools taking advantage of the vast corpus of published data.
The second assay will determine whether a group of genes is related to susceptibility to radiation-induced cancer. It will be developed from scratch using the results of in vitro
Effective start/end date1/09/1031/08/12

    Research areas

  • complex systems, multiagent systems, machine learning, reinforcement learning

    Flemish discipline codes

  • Information and computing sciences
  • Mathematical sciences

ID: 3381085