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Clinical bioinformatics, translational bioinformatics and personalised medicine are connected by the common task of analysing and integrating clinical data and results, in order to find important biomarkers related to pathologies and facilitate their prediction, diagnosis and treatment. New technologies provides the possibility to have more and more clinical data available in online databases. This data can be reused for studying complex disease from novel point of views. This work show how it is possible considering online microarray data from coeliac disease and some of its comorbidities, combining both the data and the results. The main goal is the extraction of common evidences among the selected pathologies, from genes to different kinds of functional annotation, showing which biological processes are more involved in these autoimmune disorders and quantifying the similarity between coeliac disease and its comorbidities. The pipeline of the work is developed in R language, and it is semi-automated. Methodologically, the advantage of this work is the possibility of performing the entire analysis starting from a different pathology; clinically, scientists can have the possibility of using data already published to highlight old and new evidences, with the possibility of improve the knowledge on a complex disease according to the availability of new microarray data.
This is an abstract which has been accepted for the BBCC2018 Conference