Network-based elucidation of human disease similarity reveals common functional modules enriched for pluripotent drug targets.

Current work in elucidating relationships between diseases has largely been based on pre-existing knowledge of disease genes. Consequently, these studies are limited in their discovery of new and unknown disease relationships. We present the first quantitative framework to compare and contrast diseases by an integrated analysis of disease-related mRNA expression data and the human protein interaction network. We identified 4,620 functional...

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Progressive histological damage in renal allografts is associated with expression of innate and adaptive immunity genes.

The degree of progressive chronic histological damage is associated with long-term renal allograft survival. In order to identify promising molecular targets for timely intervention, we examined renal allograft protocol and indication biopsies from 120 low-risk pediatric and adolescent recipients by whole-genome microarray expression profiling. In data-driven analysis, we found a highly regulated pattern of adaptive and innate immune gene...

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Identifying compartment-specific alloimmune targets after renal transplantation by integrating transcriptome and antibodyome measures.

Microarray technology has evolved as a powerful tool over the last decade, to identify biomarkers and study the mechanisms of diseases. We propose a novel application of integrated genomics by combining transcriptional levels with serological antibody profiling after kidney transplantation, with the aim of uncovering the relative immunogenicity of seven different renal compartments after allo-transplantation. Thirty-six paired pre- and...

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Similarly strong purifying selection acts on human disease genes of all evolutionary ages.

A number of studies have showed that recently created genes differ from the genes created in deep evolutionary past in many aspects. Here, we determined the age of emergence and propensity for gene loss (PGL) of all human protein-coding genes and compared disease genes with non-disease genes in terms of their evolutionary rate, strength of purifying selection, mRNA expression, and genetic redundancy. The older and the less prone to loss,...

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FitSNPs: highly differentially expressed genes are more likely to have variants associated with disease.

BACKGROUND: Candidate single nucleotide polymorphisms (SNPs) from genome-wide association studies (GWASs) were often selected for validation based on their functional annotation, which was inadequate and biased. We propose to use the more than 200,000 microarray studies in the Gene Expression Omnibus to systematically prioritize candidate SNPs from GWASs. RESULTS: We analyzed all human microarray studies from the Gene Expression Omnibus, and...

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