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Knowledge discovery from biological data

Research Area: Computational Biology and Biostatistics
Status: In progress  
Faculty: Annalisa Barla Participants: Alessandro Verri, Margherita Squillario
 
Description:

We aim at finding the appropriate mixture of classical statistical tools and advanced learning techniques for addressing problems like pattern discovery, finding relevant variables, and subtyping in the biomedical domain. The main challenges come from the need of integrating possibly incomplete and highly heterogeneous data sets.

We are involved in:

  • Uveal melanoma study (with E.O. Ospedali Galliera): use of clinical data in survival analysis based on treatment and prediction of tumor progression based on size
  • Head&Neck tumor study (with S.Martino-IST): use of clinical data in survival analysis and prediction of relapse