Computation biology applied to Neuroscience

Abstract

The advances in Precision Medicine are conditional on the ability of processing great quantities of data and associating them to the outcomes of interest. Data generated by BRAINN are multimodal and comprised of omics, environmental and clinical information. Currently, we lack tools and statistical methodologies to appropriately process all this information in an integrative manner. We propose to address this issue by working on the following points: A) create data-driven strategies for the quantification of differences between subjects and groups of thereof; B) implement machine learning models devoted to prediction; C) develop a deep learning solution that allows the use of multimodal data; D) assess and implement somatic variant caller for neurological cases; E) develop a software platform to allow researchers to perform data preprocessing on raw omics datasets; and F) explore the use of blockchain technology in genomics. (AU)