Stanford University
Showing 8,791-8,800 of 13,044 Results
-
Marco Perez
Associate Professor of Medicine (Cardiovascular Medicine)
BioDr. Marco Perez's research goal is to better understand the fundamental causes of cardiovascular disease through the study of genetics and epidemiology. His group studies the genetic variations and environmental exposures that are associated with conditions such as atrial fibrillation and heart failure. He has led the studies of atrial fibrillation in Women's Health Initiative, one of the largest nation-wide population-based cohorts. He is currently conducting a large study monitoring for silent or asymptomatic atrial fibrillation in women from the WHI randomized to exercise intervention, and was co-PI of the Apple Heart Study, a clinical trial that validated the ability of a smartwatch to detect atrial fibrillation. He is now PI of the Clinical Coordinating Center at Stanford for the REACT-AF which is a clinical trial to evaluate efficacy and safety of a "pill-in-the pocket" approach to anticoagulation for AF using a smartwatch. He is interested in understanding the paradox that atrial fibrillation is less common in African Americans and Hispanics, despite a greater burden of risk factors such as hypertension. As director of the Stanford Inherited Arrhythmia Clinic, he evaluates families with rare inherited arrhythmias associated with sudden death such as Long QT and Brugada Syndromes and explores their links with novel genes. He also studies the genetic causes of very early onset atrial fibrillation. He also studies how best to use the electrocardiogram and imaging modalities using Machine Learning techniques to identify patients at risk for cardiovascular disease. Dr. Perez receives funding from the NIH/NHLBI, Apple Inc., Janssen and the Colson Foundation.
-
Javier Perez-Garcia
Postdoctoral Scholar, Epidemiology
BioJavier Perez-Garcia is a postdoctoral scholar in the Department of Epidemiology and Population Health at Stanford University. His research has been focused on the integration of multi-omic data (e.g., genomics, epigenomics, transcriptomics, and microbiome) to identify potential biomarkers of treatment response for complex diseases like asthma. His research background includes experience both in molecular biology techniques (e.g., DNA extraction and sequencing libraries preparation) and bioinformatic analyses (e.g., processing of raw omic data, association studies at genomic scale, or multi-omic integration through machine learning and quantitative trait loci analyses). He holds a Ph.D. in Health Sciences and a B.Sc. in Pharmacy from the University of La Laguna (Spain).
