A5018100435- Genetic Associations and Epidemiology
- Gene expression and cancer classification
- Cutaneous Melanoma Detection and Management
- Statistical Methods in Clinical Trials
- Bioinformatics and Genomic Networks
- Health Systems, Economic Evaluations, Quality of Life
- AI in cancer detection
- Molecular Biology Techniques and Applications
- Cardiac electrophysiology and arrhythmias
- Cell Image Analysis Techniques
- Sepsis Diagnosis and Treatment
- Acute Kidney Injury Research
- Human-Animal Interaction Studies
- Optimal Experimental Design Methods
- Statistical Methods and Inference
- Radiology practices and education
- Clinical Reasoning and Diagnostic Skills
- Meta-analysis and systematic reviews
- Genetic Mapping and Diversity in Plants and Animals
- Cardiomyopathy and Myosin Studies
- Statistical Methods and Bayesian Inference
- Diet and metabolism studies
- Cancer-related molecular mechanisms research
- Heart Rate Variability and Autonomic Control
- Nonmelanoma Skin Cancer Studies
University of Washington
2016-2025
Seattle University
2005-2022
Los Angeles County Department of Health Services
2020
Yale University
2018
Sullivan Nicolaides Pathology
2018
Fred Hutch Cancer Center
2011-2017
Uppsala University
2017
Science for Life Laboratory
2017
University Medical Center Groningen
2017
University of Groningen
2017
Spotted cDNA microarrays are emerging as a powerful and cost-effective tool for large-scale analysis of gene expression. Microarrays can be used to measure the relative quantities specific mRNAs in two or more tissue samples thousands genes simultaneously. While power this technology has been recognized, many open questions remain about appropriate microarray data. One question is how make valid estimates expression that not biased by ancillary sources variation. Recognizing there inherent...
We examine experimental design issues arising with gene expression microarray technology. Microarray experiments have multiple sources of variation, and plans should ensure that effects interest are not confounded ancillary effects. A commonly used is shown to violate this principle be generally inefficient. explore the connection between designs classical block use a family ANOVA models as guide choosing design. combine principles good A‐optimality give general set recommendations for...
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The decision curve is a graphical summary recently proposed for assessing the potential clinical impact of risk prediction biomarkers or models recommending treatment intervention. It was applied in an article Journal Clinical Oncology to measure using genomic model deciding on adjuvant radiation therapy prostate cancer treated with radical prostatectomy. We illustrate use curves evaluating clinical- and biomarker-based predicting man’s cancer, which could be used guide biopsy. Decision are...
We introduce a general technique for making statistical inference from clustering tools applied to gene expression microarray data. The approach utilizes an analysis of variance model achieve normalization and estimate differential genes across multiple conditions. Statistical is based on the application randomization technique, bootstrapping. Bootstrapping has previously been used obtain confidence intervals estimates individual genes. Here we apply bootstrapping assess stability results...
The FDA approved drug rapamycin increases lifespan in rodents and delays age-related dysfunction humans. Nevertheless, important questions remain regarding the optimal dose, duration, mechanisms of action context healthy aging. Here we show that 3 months treatment is sufficient to increase life expectancy by up 60% improve measures healthspan middle-aged mice. This transient also associated with a remodeling microbiome, including dramatically increased prevalence segmented filamentous...
Authors have proposed new methodology in recent years for evaluating the improvement prediction performance gained by adding a predictor, Y , to risk model containing set of baseline predictors, X binary outcome D . We prove theoretically that null hypotheses concerning no are equivalent simple hypothesis is not factor when controlling H 0 : P ( = 1 | ) ). Therefore, testing redundant if has already been shown be factor. also investigate properties tests through simulation studies, focusing...
Plasma low-density lipoprotein cholesterol (LDL-C) has been associated with aortic stenosis in observational studies; however, randomized trials cholesterol-lowering therapies individuals established valve disease have failed to demonstrate reduced progression.To evaluate whether genetic data are consistent an association between LDL-C, high-density (HDL-C), or triglycerides (TG) and disease.Using a Mendelian randomization study design, we evaluated weighted risk scores (GRSs), measure of...
Abstract Introduction Alzheimer's disease (AD) and Parkinson's (PD) involve tau pathology. Tau is detectable in blood, but its clearance from neuronal cells the brain poorly understood. Methods efflux to blood was evaluated by administering radioactively labeled unlabeled intracerebroventricularly wild‐type knock‐out mice, respectively. Central nervous system (CNS)–derived L1CAM‐containing exosomes further characterized extensively human plasma, including single molecule array technology...
Despite a higher burden of standard atrial fibrillation (AF) risk factors, African Americans have lower AF than whites. It is unknown whether the due to genetic or environmental factors. Because varying degrees European ancestry, we sought test hypothesis that ancestry an independent factor for AF.
Summary . This article describes the theoretical and practical issues in experimental design for gene expression microarrays. Specifically, this 1) discusses basic principles of (randomization, replication, blocking) as they pertain to microarrays, 2) provides some general guidelines statisticians designing microarray studies.
The integrated discrimination improvement (IDI) index is a popular tool for evaluating the capacity of marker to predict binary outcome interest.Recent reports have proposed that IDI more sensitive than other metrics identifying useful predictive markers.In this article, authors use simulated data sets and theoretical analysis investigate statistical properties IDI.The consider common situation in which risk model fitted set with without new, candidate predictor(s).Results demonstrate...