The Department of Pharmacology & Toxicology

Proudly Presents

John Allen, PhD

Assistant Professor
Department of Pharmacology and Toxicology
The University of Texas Medical Branch at Galveston

“Novel ligands and molecular approaches to define dopamine receptor signaling”

Friday, April 20th, 2018

12:00 p.m. – 1:00 p.m.

Research Building 6, Room 1.206

UTMB - Biostatics and CTSA (Clinical & Translational Science Awards)

Presents

TRCC (Texas Regional CTSA Consortium)

Quantitative Seminar Series

“Selecting Important Variables and/or Genes

Across a Variety of Outcomes”

Michael D. Swartz, Ph.D.

Associate Professor

Department of Biostatistics and Data Science

School of Public Health

The University of Texas Health Science Center at Houston

Tuesday, April 24, 2018

Noon – 1 pm

Ewing Hall 1.104

This seminar contributes to achieving one or more of the CTSA core competencies in the category of Statistical Approaches.

Abstract: Variables are everywhere and the problem of variable selection is an active area of research across a variety of fields.  In this talk I will provide an overview of multiple variable selection developments and applications completed by my research group. Most of the early applications are to genetic data, answering the question of what genes area associated with a disease. The first method, Stochastic search gene suggestion, developed in 2006, incorporated genetic structures into the hierarchical priors for model selection. Specifically, we incorporated linkage disequilibrium, a type of genetic correlation. Originally the selection priors were designed to model the biological structure of multiple alleles within genetic loci, common in the genetic markers of the time, known as microsatellites. Then SSGS was updated to analyze more contemporary genetic markers known as Single nucleotide polymorphisms (SNPs) and applied to search for SNPs associated with Acute Lymphoblastic Leukemia.  Originally designed for family trios to be genotyped (both parents and one affected child) SSGS was next developed for case control data and genetic pathway information, and finally updated for computationally intense larger data sets by incorporating the EM algorithm for posterior mode hunting.  And we branched out of genetics to tackle identifying important factors associated with physical activity measured by accelerometers using penalized augmented estimating equations.

*** Lunch Provided ***

Participating TRCC Institutions include: UTMB, UTHSC-Houston, UTHSC-San Antonio, and UT Southwestern