Sergio Baranzini

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UNLABELLED Protein interaction network-based pathway analysis (PINBPA) for genome-wide association studies (GWAS) has been developed as a Cytoscape app, to enable analysis of GWAS data in a network fashion. Users can easily import GWAS summary-level data, draw Manhattan plots, define blocks, prioritize genes with random walk with restart, detect enriched(More)
We introduce the integrative protein-interaction-network-based pathway analysis (iPINBPA) for genome-wide association studies (GWAS), a method to identify and prioritize genetic associations by merging statistical evidence of association with physical evidence of interaction at the protein level. First, the strongest associations are used to weight all(More)
While networks models have often been applied to complex biological systems, they are increasingly being implemented to investigate clinical questions. Clinical trials have been studied extensively by traditional statistical methods but never, to our knowledge, using networks. We obtained data for 6,847 clinical trials from five "Nervous System Diseases"(More)
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