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  • A spatiotemporal case-crossover model of asthma exacerbation in the City of Houston 

    Schedler, Julia C.; Ensor, Katherine B. (2021)
    Case-crossover design is a popular construction for analyzing the impact of a transient effect, such as ambient pollution levels, on an acute outcome, such as an asthma exacerbation. Case-crossover design avoids the need to model individual, time-varying risk factors for cases by using cases as their own ‘controls’, chosen to be time periods for which ...
  • A Bayesian Nonparametric Spiked Process Prior for Dynamic Model Selection 

    Cassese, Alberto; Zhu, Weixuan; Guindani, Michele; Vannucci, Marina (2019)
    In many applications, investigators monitor processes that vary in space and time, with the goal of identifying temporally persistent and spatially localized departures from a baseline or “normal” behavior. In this manuscript, we consider the monitoring of pneumonia and influenza (P&I) mortality, to detect influenza outbreaks in the continental United ...
  • Filtering and Estimation for a Class of Stochastic Volatility Models with Intractable Likelihoods 

    Vankov, Emilian R.; Guindani, Michele; Ensor, Katherine B. (2019)
    We introduce a new approach to latent state filtering and parameter estimation for a class of stochastic volatility models (SVMs) for which the likelihood function is unknown. The α-stable stochastic volatility model provides a flexible framework for capturing asymmetry and heavy tails, which is useful when modeling financial returns. However, the ...
  • Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data 

    Wang, Minjie; Allen, Genevera I. (2021)
    In mixed multi-view data, multiple sets of diverse features are measured on the same set of samples. By integrating all available data sources, we seek to discover common group structure among the samples that may be hidden in individualistic cluster analyses of a single data view. While several techniques for such integrative clustering have been ...
  • Hierarchical Normalized Completely Random Measures for Robust Graphical Modeling 

    Cremaschi, Andrea; Argiento, Raffaele; Shoemaker, Katherine; Peterson, Christine; Vannucci, Marina (2019)
    Gaussian graphical models are useful tools for exploring network structures in multivariate normal data. In this paper we are interested in situations where data show departures from Gaussianity, therefore requiring alternative modeling distributions. The multivariate t-distribution, obtained by dividing each component of the data vector by a gamma ...
  • The Texas flood registry: a flexible tool for environmental and public health practitioners and researchers 

    Miranda, Marie Lynn; Callender, Rashida; Canales, Joally M.; Craft, Elena; Ensor, Katherine B.; (2021)
    Background: Making landfall in Rockport, Texas in August 2017, Hurricane Harvey resulted in unprecedented flooding, displacing tens of thousands of people, and creating environmental hazards and exposures for many more. Objective: We describe a collaborative project to establish the Texas Flood Registry to track the health and housing impacts of major ...
  • SIBaR: a new method for background quantification and removal from mobile air pollution measurements 

    Actkinson, Blake; Ensor, Katherine; Griffin, Robert J. (2021)
    Mobile monitoring is becoming increasingly popular for characterizing air pollution on fine spatial scales. In identifying local source contributions to measured pollutant concentrations, the detection and quantification of background are key steps in many mobile monitoring studies, but the methodology to do so requires further development to improve ...
  • Market truths: theory versus empirical simulations 

    Wojciechowski, William C.; Thompson, James R. (2006)
  • Nobels for nonsense 

    Thompson, James R.; Baggett, L. Scott; Wojciechowski, William C.; Williams, Edward E. (2005)
  • The Age of Tukey 

    Thompson, James R. (2001)
  • Downregulation of glial genes involved in synaptic function mitigates Huntington's disease pathogenesis 

    Onur, Tarik Seref; Laitman, Andrew; Zhao, He; Keyho, Ryan; Kim, Hyemin; (2021)
    Most research on neurodegenerative diseases has focused on neurons, yet glia help form and maintain the synapses whose loss is so prominent in these conditions. To investigate the contributions of glia to Huntington's disease (HD), we profiled the gene expression alterations of Drosophila expressing human mutant Huntingtin (mHTT) in either glia or ...
  • Electrochemical ammonia synthesis via nitrate reduction on Fe single atom catalyst 

    Wu, Zhen-Yu; Karamad, Mohammadreza; Yong, Xue; Huang, Qizheng; Cullen, David A.; (2021)
    Electrochemically converting nitrate, a widespread water pollutant, back to valuable ammonia is a green and delocalized route for ammonia synthesis, and can be an appealing and supplementary alternative to the Haber-Bosch process. However, as there are other nitrate reduction pathways present, selectively guiding the reaction pathway towards ammonia ...
  • Dynamic Regression Models for Time-Ordered Functional Data 

    Kowal, Daniel R. (2021)
    For time-ordered functional data, an important yet challenging task is to forecast functional observations with uncertainty quantification. Scalar predictors are often observed concurrently with functional data and provide valuable information about the dynamics of the functional time series. We develop a fully Bayesian framework for dynamic functional ...
  • Robust Multiple Regression 

    Scott, David W.; Wang, Zhipeng (2021)
    As modern data analysis pushes the boundaries of classical statistics, it is timely to reexamine alternate approaches to dealing with outliers in multiple regression. As sample sizes and the number of predictors increase, interactive methodology becomes less effective. Likewise, with limited understanding of the underlying contamination process, ...
  • A joint modeling approach for longitudinal microbiome data improves ability to detect microbiome associations with disease 

    Luna, Pamela N.; Mansbach, Jonathan M.; Shaw, Chad A. (2020)
    Changes in the composition of the microbiome over time are associated with myriad human illnesses. Unfortunately, the lack of analytic techniques has hindered researchers’ ability to quantify the association between longitudinal microbial composition and time-to-event outcomes. Prior methodological work developed the joint model for longitudinal and ...
  • Interferon Gamma Mediates Hematopoietic Stem Cell Activation and Niche Relocalization through BST2 

    Florez, Marcus A.; Matatall, Katie A.; Jeong, Youngjae; Ortinau, Laura; Shafer, Paul W.; (2020)
    During chronic infection, the inflammatory cytokine interferon gamma (IFNγ) damages hematopoietic stem cells (HSCs) by disrupting quiescence and promoting excessive terminal differentiation. However, the mechanism by which IFNγ hinders HSC quiescence remains undefined. Using intravital 3-dimensional microscopy, we find that IFNγ disrupts the normally ...
  • Quantifying cognitive resilience in Alzheimer’s Disease: The Alzheimer’s Disease Cognitive Resilience Score 

    Yao, Tianyi; Sweeney, Elizabeth; Nagorski, John; Shulman, Joshua M.; Allen, Genevera I. (2020)
    Even though there is a clear link between Alzheimer’s Disease (AD) related neuropathology and cognitive decline, numerous studies have observed that healthy cognition can exist in the presence of extensive AD pathology, a phenomenon sometimes called Cognitive Resilience (CR). To better understand and study CR, we develop the Alzheimer’s Disease ...
  • Mathematical model predicts response to chemotherapy in advanced non-resectable non-small cell lung cancer patients treated with platinum-based doublet 

    Kozłowska, Emilia; Suwiński, Rafał; Giglok, Monika; Świerniak, Andrzej; Kimmel, Marek (2020)
    We developed a computational platform including machine learning and a mechanistic mathematical model to find the optimal protocol for administration of platinum-doublet chemotherapy in a palliative setting. The platform has been applied to advanced metastatic non-small cell lung cancer (NSCLC). The 42 NSCLC patients treated with palliative intent ...
  • Urothelial-to-Neural Plasticity Drives Progression to Small Cell Bladder Cancer 

    Yang, Guoliang; Bondaruk, Jolanta; Cogdell, David; Wang, Ziqiao; Lee, Sangkyou; (2020)
    We report a comprehensive molecular analysis of 34 cases of small cell carcinoma (SCC) and 84 cases of conventional urothelial carcinoma (UC), with The Cancer Genome Atlas cohort of 408 conventional UC bladder cancers used as the reference. SCCs showed mutational landscapes characterized by nearly uniform inactivation of TP53 and were dominated by ...
  • Application of the Moran Model in Estimating Selection Coefficient of Mutated CSF3R Clones in the Evolution of Severe Congenital Neutropenia to Myeloid Neoplasia 

    Dinh, Khanh N.; Corey, Seth J.; Kimmel, Marek (2020)
    Bone marrow failure (BMF) syndromes, such as severe congenital neutropenia (SCN) are leukemia predisposition syndromes. We focus here on the transition from SCN to pre-leukemic myelodysplastic syndrome (MDS). Stochastic mathematical models have been conceived that attempt to explain the transition of SCN to MDS, in the most parsimonious way, using ...

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