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Zhaoxia Yu

Researcher at University of California, Irvine

Publications -  59
Citations -  1997

Zhaoxia Yu is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Population & Computer science. The author has an hindex of 19, co-authored 55 publications receiving 1592 citations. Previous affiliations of Zhaoxia Yu include Mayo Clinic & University of California, Berkeley.

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Simultaneous Genotype Calling and Haplotype Phasing Improves Genotype Accuracy and Reduces False-Positive Associations for Genome-wide Association Studies

TL;DR: Results from single-marker and haplotypic analysis of the BEAGLE method's genotype calls for the bipolar disorder study indicate that the method is highly effective at eliminating genotyping artifacts that cause false-positive associations in genome-wide association studies.
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Effect of phenylephrine and ephedrine bolus treatment on cerebral oxygenation in anaesthetized patients

TL;DR: Associated with changes in CO, decreased after phenylephrine treatment, but remained unchanged after ephedrine treatment, implies a cause-effect relationship between global and regional haemodynamics.
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Accuracy and Precision of Continuous Noninvasive Arterial Pressure Monitoring Compared with Invasive Arterial Pressure: A Systematic Review and Meta-analysis

TL;DR: The results from this meta-analysis found that inaccuracy and imprecision of continuous noninvasive arterial pressure monitoring devices are larger than what was defined as acceptable, which may have implications for clinical situations where continuous non invasive arterIAL pressure is being used for patient care decisions.
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Genetics and the environment converge to dysregulate N -glycosylation in multiple sclerosis

TL;DR: It is shown that MS risk modulators converge to alter N-glycosylation and/or CTLA-4 surface retention conditional on metabolism and vitamin D3, including genetic variants in interleukin-7 receptor-α (IL7RA*C), interleokin-2 receptor- α (IL2RA*T), MGAT1 (IVAVT−T) and CTLA
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SNP-based pathway enrichment analysis for genome-wide association studies

TL;DR: The SNP-based pathway enrichment method described here offers a new alternative approach for analysing GWAS data, and is able to identify statistically significant pathways, and importantly, pathways that can be replicated in large genetically distinct samples.