Autism Spectrum Disorders (ASD) are heterogeneous neurodevelopmental disorders diagnosed in more than 1% of the population. For better prognosis and treatment, genetic stratification is suggested which aims to classify patients into more homogeneous subgroups.
My thesis project aims to design a Network Based Stratification (NBS) approach of ASD using Protein-Protein Interaction (PPI), especially through consideration of de novo and inherited mutations. After developing a complete open source NBS toolkit in Python (StratiPy), several biological parameters will be integrated like: origin of mutation (de novo, from paternal or maternal line); the developmental and anatomically prior of gene expression by constraining the PPI by spatio-temporal co-expression networks; statistical involvement in various diseases of nervous system.
