Integrative analysis of metabolic disorders by means of medical bioinformatics

We present a strategy of bioinformatics analysis to exploit the current data available both on genomic and metabolic levels and integrate these at novel levels of understanding of metabolic disorders. PathAligner is applied to predict biomedical data based on a given disorder. A case study on urea cycle disorders is demonstrated. Both genetic data and metabolic information are retrieved. We integratively analyze the transcription factors, signaling pathways and associated disorders to interpret the occurrence and regulation of the urea cycle.