Christopher C. Park

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The relationships between the levels of transcripts and the levels of the proteins they encode have not been examined comprehensively in mammals, although previous work in plants and yeast suggest a surprisingly modest correlation. We have examined this issue using a genetic approach in which natural variations were used to perturb both transcript levels(More)
We mapped regulatory loci for nearly all protein-coding genes in mammals using comparative genomic hybridization and expression array measurements from a panel of mouse-hamster radiation hybrid cell lines. The large number of breaks in the mouse chromosomes and the dense genotyping of the panel allowed extremely sharp mapping of loci. As the regulatory loci(More)
Mutations that inactivate the retinoblastoma (Rb) pathway are common in human tumors. Such mutations promote tumor growth by deregulating the G1 cell cycle checkpoint. However, uncontrolled cell cycle progression can also produce new liabilities for cell survival. To uncover such liabilities in Rb mutant cells, we performed a clonal screen in the Drosophila(More)
Our understanding of the genetic basis of learning and memory remains shrouded in mystery. To explore the genetic networks governing the biology of conditional fear, we used a systems genetics approach to analyze a hybrid mouse diversity panel (HMDP) with high mapping resolution. A total of 27 behavioral quantitative trait loci were mapped with a false(More)
There is only a limited understanding of the relation between copy number and expression for mammalian genes. We fine mapped cis and trans regulatory loci due to copy number change for essentially all genes using a human-hamster radiation hybrid (RH) panel. These loci are called copy number expression quantitative trait loci (ceQTLs). Unexpected findings(More)
Using radiation hybrid genotyping data, 99% of all possible gene pairs across the mammalian genome were tested for interactions based on co-retention frequencies higher (attraction) or lower (repulsion) than chance. Gene interaction networks constructed from six independent data sets overlapped strongly. Combining the data sets resulted in a network of more(More)
We performed an unbiased experimental search for enhancers and silencers in a 153-kb region containing the human apolipoprotein (APO) E/C1/C4/C2 gene cluster using shotgun cloning into a luciferase vector. A continuum of transcriptional effect sizes was observed, possibly explaining the limited success of bioinformatics in identifying regulatory regions. We(More)
Meiotic mapping of quantitative trait loci regulating expression (eQTLs) has allowed the construction of gene networks. However, the limited mapping resolution of these studies has meant that genotype data are largely ignored, leading to undirected networks that fail to capture regulatory hierarchies. Here we use high resolution mapping of copy number eQTLs(More)
Integrating quantitative proteomic and transcriptomic datasets promises valuable insights in unraveling the molecular mechanisms of the brain. We concentrate on recent studies using mass spectrometry and microarray data to investigate transcript and protein abundance in normal and diseased neural tissues. Highlighted are dual spatial maps of these molecules(More)
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