Sergio Baranzini

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Many common diseases, such as asthma, diabetes or obesity, involve altered interactions between thousands of genes. High-throughput techniques (omics) allow identification of such genes and their products, but functional understanding is a formidable challenge. Network-based analyses of omics data have identified modules of disease-associated genes that(More)
Identity by descent (IBD) has played a fundamental role in the discovery of genetic loci underlying human diseases. Both pedigree-based and population-based linkage analyses rely on estimating recent IBD, and evidence of ancient IBD can be used to detect population structure in genetic association studies. Various methods for detecting IBD, including those(More)
OBJECTIVE Our objective was to determine whether altered naive CD4 T-cell biology contributes to development of disease progression in secondary progressive multiple sclerosis (SPMS). METHODS We compared the naive CD4 T-cell gene expression profiles of 19 patients with SPMS and 14 healthy controls (HCs) using a whole-genome microarray approach. We(More)
  • Anna V Molofsky, Stacey M Glasgow, Lesley S Chaboub, Hui-Hsin Tsai, Alice T Murnen, Kevin W Kelley +7 others
  • 2013
Developmental regulation of gliogenesis in the mammalian CNS is incompletely understood, in part due to a limited repertoire of lineage-specific genes. We used Aldh1l1-GFP as a marker for gliogenic radial glia and later-stage precursors of developing astrocytes and performed gene expression profiling of these cells. We then used this dataset to identify(More)
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)
iCTNet (integrated Complex Traits Networks) version 2 is a Cytoscape app and database that allows researchers to build heterogeneous networks by integrating a variety of biological interactions, thus offering a systems-level view of human complex traits. iCTNet2 is built from a variety of large-scale biological datasets, collected from public repositories(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)
A precondition for understanding if-and-when observations on wet-lab research models can translate to patients (and vice versa) is to have a method that enables anticipating how each system at the mechanism level will respond to the same or similar new intervention. A new class of mechanistic, in silico analogues is described. We argue that, although(More)