Hypothesis

Initial hypothesis that will support the objectives of the project:

• Hypothesis 1: Accurate haplogroup prediction via extensive phylogenies is useful in detecting individual increased/decreased risk of certain neurodegenerative diseases. As existing studies of haplogroup related risk can be corroborated via pathogenic mutation analysis, the pathogenic character of mutations present in neurodegenerative disease patients can be assessed via automatic classifiers newly devised for this purpose. 
• Hypothesis 2: Non-rigid image registration methods able to deal with very large deformations may provide morphometric indicators valid for the diagnosis of neurodegenerative diseases.
• Hypothesis 3: Minimal cognitive modelling and complex linguistic networks provide formal, objective measures able to constitute the rough data for further mathematical analyses. Moreover, the presence and evolution of multiple scale in the form of 1/f scaling computed on the values of biomarkers extracted from these models, may provide indicators for the medical diagnosis in the progression of neurodegenerative diseases.
• Hypothesis 4: The combination of our knowledge from bioinformatics, computational anatomy, cognitive modeling using machine learning techniques, may set the basis of a novel framework for the potentially early diagnosis of neurodegenerative diseases.