Publications by authors named "Zhaohui Steve Qin"

A/B compartments are observed in Hi-C data and coincide with eu/hetero-chromatin. However, many genomic regions are ambiguous under A/B compartment scheme. We develop MOSAIC (MOdularity and Singular vAlue decomposition-based Identification of Compartments), an accurate compartmental state detection scheme.

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Background: Targeting mitochondrial oncoproteins presents a new concept in the development of effective cancer therapeutics. ATAD3A is a nuclear-encoded mitochondrial enzyme contributing to mitochondrial dynamics, cholesterol metabolism, and signal transduction. However, its impact and underlying regulatory mechanisms in cancers remain ill-defined.

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Background: Nucleosome plays a role in transcriptional regulation through occluding the binding of proteins to DNA sites. Nucleosome occupancy varies among different cell types. Identification of such variation will help to understand regulation mechanism.

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The interactions of protein kinases and phosphatases with their regulatory subunits and substrates underpin cellular regulation. We identified a kinase and phosphatase interaction (KPI) network of 1844 interactions in budding yeast by mass spectrometric analysis of protein complexes. The KPI network contained many dense local regions of interactions that suggested new functions.

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Article Synopsis
  • The study analyzes over 3 million genetic variations from the International HapMap Project to identify regions of the human genome that have undergone positive natural selection.
  • Using advanced methods, researchers pinpointed over 300 candidate regions, specifically narrowing down to 22 strong areas for further scrutiny.
  • The analysis highlights 26 specific gene variations under positive selection, demonstrating similar evolutionary pressures in related genes across different populations, including regions tied to virus infection and traits like skin pigmentation and hair follicle development.
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We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.

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