Biomedical research is at a critical juncture in which vast amounts of information on molecules and molecular interactions have been collected, but methods to integrate and analyze these data are still in their infancy. The sheer number and variety of technologies is staggering. In terms of molecules, global mRNA profiles are obtained using DNA microarrays 178 or next-generation sequencing 179, while changes in protein abundance 180, protein phosphorylation state 181 and metabolite concentrations 182 are quantified with mass spectrometry, NMR and other advanced techniques. In terms of molecular interactions, protein-protein binding is measured using yeast-two-hybrid assays 183,184,185,186,187,188,189,190, LUMIER 191, affinity purification coupled to mass spectrometry 192,193,194, or kinase-substrate arrays 195. Protein-DNA and protein-RNA binding are measured with technologies such as chIP-chip 196,197,198, chIP-PET 199,200, DAM-ID 201, double-stranded DNA arrays 202, yeastone- hybrid 203,204, or RIP-chip 205. There has also been an explosion in techniques for mapping genetic networks, including Synthetic Genetic Arrays 206, dSLAM 207, EMAP 208, high-throughput liquid culture assays 209, and combinatorial RNAi 210, which rapidly identify epistatic relationships such as synthetic lethality or suppression in an automated fashion. Large networks are generated by functional genomic studies, involving panels of gene knock-outs 211,212,213,214,215 or analysis of expression Quantitative Trait Loci (eQTL) 216,217,218,219. Alternatively, networks are being defined using functional inter-relationships, such as linking two proteins that are co-expressed or that are given the same protein functional annotation 220. This enormous collection of measurement types necessitates a bioinformatic framework to integrate, filter, and interpret the resulting data. The Mission of the Network Assembly Core is to provide tools for integration and visualization of network level and other genome-scale data, assembly of these data into biological networks in which functional network modules can be identified, and storage and dissemination of data and resulting models. The director, Dr. Ideker is an established leader in the area of bioinformatics dedicated to developing such methods.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Specialized Center (P50)
Project #
5P50GM085764-03
Application #
8380342
Study Section
Special Emphasis Panel (ZGM1-CBCB-2)
Project Start
Project End
Budget Start
2012-09-01
Budget End
2013-08-31
Support Year
3
Fiscal Year
2012
Total Cost
$156,006
Indirect Cost
$55,357
Name
University of California San Diego
Department
Type
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
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