Relationship between gene expression networks and muscle contractile physiology differences in Anolis lizards.

Muscles facilitate most animal behavior, from eating to fleeing. However, to generate the variation in behavior necessary for survival, different muscles must perform differently; for instance, sprinting requires multiple rapid muscle contractions, whereas biting may require fewer contractions but greater force. Here, we use a transcriptomic approach to identify genes associated with variation in muscle contractile physiology among different muscles from the same individual.

QUANTILE REGRESSION FOR MIXED MODELS WITH AN APPLICATION TO EXAMINE BLOOD PRESSURE TRENDS IN CHINA.

Cardiometabolic diseases have substantially increased in China in the past 20 years and blood pressure is a primary modifiable risk factor. Using data from the China Health and Nutrition Survey we examine blood pressure trends in China from 1991 to 2009, with a concentration on age cohorts and urbanicity. Very large values of blood pressure are of interest, so we model the conditional quantile functions of systolic and diastolic blood pressure.

Multilevel quantile function modeling with application to birth outcomes.

Infants born preterm or small for gestational age have elevated rates of morbidity and mortality. Using birth certificate records in Texas from 2002 to 2004 and Environmental Protection Agency air pollution estimates, we relate the quantile functions of birth weight and gestational age to ozone exposure and multiple predictors, including parental age, race, and education level. We introduce a semi-parametric Bayesian quantile approach that models the full quantile function rather than just a few quantile levels.

Bayesian quantile regression for censored data.

In this paper we propose a semiparametric quantile regression model for censored survival data. Quantile regression permits covariates to affect survival differently at different stages in the follow-up period, thus providing a comprehensive study of the survival distribution. We take a semiparametric approach, representing the quantile process as a linear combination of basis functions.