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Bayesian modeling

Yu-Han Chiu, Andrea Bellavia, Tamarra James-Todd, Katharine F Correia, Linda Valeri, Carmen Messerlian, Jennifer B Ford, Lidia Mínguez-Alarcón, Antonia M Calafat, Russ Hauser, Paige L Williams
OBJECTIVES: We applied three statistical approaches for evaluating associations between prenatal urinary concentrations of a mixture of phthalate metabolites and birth weight. METHODS: We included 300 women who provided 732 urine samples during pregnancy and delivered a singleton infant. We measured urinary concentrations of metabolites of di(2-ethylhexyl)-phthalate, di-isobutyl-, di-n-butyl-, butylbenzyl-, and diethyl phthalates. We applied 1) linear regressions; 2) classification methods [principal component analysis (PCA) and structural equation models (SEM)]; and 3) Bayesian kernel machine regression (BKMR), to evaluate associations between phthalate metabolite mixtures and birth weight adjusting for potential confounders...
February 13, 2018: Environment International
(no author information available yet)
BACKGROUND: Surgical site infection (SSI) is one of the most common infections associated with health care, but its importance as a global health priority is not fully understood. We quantified the burden of SSI after gastrointestinal surgery in countries in all parts of the world. METHODS: This international, prospective, multicentre cohort study included consecutive patients undergoing elective or emergency gastrointestinal resection within 2-week time periods at any health-care facility in any country...
February 13, 2018: Lancet Infectious Diseases
Ajay Anand Kumar, Lut Van Laer, Maaike Alaerts, Amin Ardeshirdavani, Yves Moreau, Kris Laukens, Bart Loeys, Geert Vandeweyer, Inanc Birol
Motivation: Computational gene prioritization can aid in disease gene identification. Here, we propose pBRIT (prioritization using Bayesian Ridge regression and Information Theoretic model), a novel adaptive and scalable prioritization tool, integrating Pubmed abstracts, Gene Ontology, Sequence similarities, Mammalian and Human Phenotype Ontology, Pathway, Interactions, Disease Ontology, Gene Association database and Human Genome Epidemiology database, into the prediction model.We explore and address effects of sparsity and inter-feature dependencies within annotation sources, and the impact of bias towards specific annotations...
February 14, 2018: Bioinformatics
Mark Renfrew, Mark Griswold, M Cenk Çavuşoğlu
This paper describes a framework of algorithms for the active localization and tracking of flexible needles and targets during image-guided percutaneous interventions. The needle and target configurations are tracked by Bayesian filters employing models of the needle and target motions and measurements of the current system state obtained from an intra-operative imaging system which is controlled by an entropy-minimizing active localization algorithm. Versions of the system were built using particle and unscented Kalman filters and their performance was measured using both simulations and hardware experiments with real magnetic resonance imaging data of needle insertions into gel phantoms...
January 2018: Autonomous Robots
J A Romero, S A Dettrick, E Granstedt, T Roche, Y Mok
Active control of field reversed configuration (FRC) devices requires a method to determine the flux surface geometry and dynamic properties of the plasma during both transient and steady-state conditions. The current tomography (CT) method uses Bayesian inference to determine the plasma current density distribution using both the information from magnetic measurements and a physics model in the prior. Here we show that, from the inferred current sources, the FRC topology and its axial stability properties are readily obtained...
February 15, 2018: Nature Communications
Tiago P Peixoto
We present a Bayesian formulation of weighted stochastic block models that can be used to infer the large-scale modular structure of weighted networks, including their hierarchical organization. Our method is nonparametric, and thus does not require the prior knowledge of the number of groups or other dimensions of the model, which are instead inferred from data. We give a comprehensive treatment of different kinds of edge weights (i.e., continuous or discrete, signed or unsigned, bounded or unbounded), as well as arbitrary weight transformations, and describe an unsupervised model selection approach to choose the best network description...
January 2018: Physical Review. E
Jeremy R Manning, Xia Zhu, Theodore L Willke, Rajesh Ranganath, Kimberly Stachenfeld, Uri Hasson, David M Blei, Kenneth A Norman
Recent research shows that the covariance structure of functional magnetic resonance imaging (fMRI) data - commonly described as functional connectivity - can change as a function of the participant's cognitive state (for review see (Turk-Browne, 2013)). Here we present a Bayesian hierarchical matrix factorization model, termed hierarchical topographic factor analysis (HTFA), for efficiently discovering full-brain networks in large multi-subject neuroimaging datasets. HTFA approximates each subject's network by first re-representing each brain image in terms of the activities of a set of localized nodes, and then computing the covariance of the activity time series of these nodes...
February 12, 2018: NeuroImage
Tyler Bowman, Tanny Chavez, Kamrul Khan, Jingxian Wu, Avishek Chakraborty, Narasimhan Rajaram, Keith Bailey, Magda El-Shenawee
This paper investigates terahertz (THz) imaging and classification of freshly excised murine xenograft breast cancer tumors. These tumors are grown via injection of E0771 breast adenocarcinoma cells into the flank of mice maintained on high-fat diet. Within 1 h of excision, the tumor and adjacent tissues are imaged using a pulsed THz system in the reflection mode. The THz images are classified using a statistical Bayesian mixture model with unsupervised and supervised approaches. Correlation with digitized pathology images is conducted using classification images assigned by a modal class decision rule...
February 2018: Journal of Biomedical Optics
Adnan Sarwar, Faisal Khan, Majeed Abimbola, Lesley James
Resilience is the capability of a system to adjust its functionality during a disturbance or perturbation. The present work attempts to quantify resilience as a function of reliability, vulnerability, and maintainability. The approach assesses proactive and reactive defense mechanisms along with operational factors to respond to unwanted disturbances and perturbation. This article employs a Bayesian network format to build a resilience model. The application of the model is tested on hydrocarbon-release scenarios during an offloading operation in a remote and harsh environment...
February 15, 2018: Risk Analysis: An Official Publication of the Society for Risk Analysis
Charles L Nunn, David R Samson
OBJECTIVES: Primates vary in their sleep durations and, remarkably, humans sleep the least per 24-hr period of the 30 primates that have been studied. Using phylogenetic methods that quantitatively situate human phenotypes within a broader primate comparative context, we investigated the evolution of human sleep architecture, focusing on: total sleep duration, rapid eye movement (REM) sleep duration, non-rapid eye movement (NREM) sleep duration, and proportion of sleep in REM. MATERIALS AND METHODS: We used two different Bayesian methods: phylogenetic prediction based on phylogenetic generalized least squares and a multistate Onrstein-Uhlenbeck (OU) evolutionary model of random drift and stabilizing selection...
February 14, 2018: American Journal of Physical Anthropology
Steven Novick, Perceval Sondag, Tim Schofield, Kenneth Miller
For biotherapeutics and vaccines, potency is measured in a bioassay which compares the concentration-response curves of a new batch to that of a reference standard. Acceptable accuracy and precision of potency measurement is critical to the manufacturing of these products. These characteristics of a bioassay are typically assessed in a procedure which is carried out with samples spanning the acceptable range for the product. During early development, however, a full validation study such as that which is carried out in late development can be costly as it relates to the likelihood of eventual program success...
February 14, 2018: PDA Journal of Pharmaceutical Science and Technology
Solon Karapanagiotis, Paul D P Pharoah, Christopher H Jackson, Paul J Newcombe
PURPOSE: To compare PREDICT and CancerMath, two widely used prognostic models for invasive breast cancer, taking into account their clinical utility. Furthermore, it is unclear whether these models could be improved. Experimental Design: A dataset of 5729 women was used for model development. A Bayesian variable selection algorithm was implemented to stochastically search for important interaction terms among the predictors. The derived models were then compared in three independent datasets (n = 5534)...
February 14, 2018: Clinical Cancer Research: An Official Journal of the American Association for Cancer Research
Satoshi Kakiuchi, Motoi Suzuki, Bhim Gopal Dhoubhadel, Akitsugu Furumoto, Hiroyuki Ito, Kei Matsuki, Yoshiko Tsuchihashi, Norichika Asoh, Michio Yasunami, Koya Ariyoshi, Konosuke Morimoto
The lack of reliable diagnostic tests for detecting vaccine serotype pneumococcal pneumonia (VTPP) remains a challenging issue in pneumococcal vaccine studies. This study assessed the performances of high-throughput nanofluidic PCR-based pneumococcal serotyping and quantification assay methods using sputum samples (nanofluidic Sp-qPCR) to diagnose the 13-valent pneumococcal conjugate VTPP compared with that of the serotype-specific urinary antigen detection (UAD) assay using urine samples. Adult pneumonia patients from Japan were enrolled in this study between September 2012 and August 2014...
February 14, 2018: Journal of Clinical Microbiology
K H C Massa, R Pabayo, A D P Chiavegatto Filho
Background: The association between income inequality and health has been analyzed predominantly in developed countries with modest levels of inequality. The study aimed to analyze the association between income inequality and self-reported health (SRH) in the adult population of the 27 Brazilian capitals. Methods: Individuals aged 18 years or older from the National Health survey residing in Brazilian capitals in 2013 were analyzed (n = 27 017). Bayesian multilevel models were applied after controlling for individual factors and area-level socioeconomic characteristics...
February 1, 2018: Journal of Public Health
Maitreyee Bose, James S Hodges, Sudipto Banerjee
Gaussian processes (GPs) are widely used as distributions of random effects in linear mixed models, which are fit using the restricted likelihood or the closely related Bayesian analysis. This article addresses two problems. First, we propose tools for understanding how data determine estimates in these models, using a spectral basis approximation to the GP under which the restricted likelihood is formally identical to the likelihood for a gamma-errors GLM with identity link. Second, to examine the data's support for a covariate and to understand how adding that covariate moves variation in the outcome y out of the GP and error parts of the fit, we apply a linear-model diagnostic, the added variable plot (AVP), both to the original observations and to projections of the data onto the spectral basis functions...
February 13, 2018: Biometrics
Jeffrey N Rouder, Julia M Haaf, Joachim Vandekerckhove
In the psychological literature, there are two seemingly different approaches to inference: that from estimation of posterior intervals and that from Bayes factors. We provide an overview of each method and show that a salient difference is the choice of models. The two approaches as commonly practiced can be unified with a certain model specification, now popular in the statistics literature, called spike-and-slab priors. A spike-and-slab prior is a mixture of a null model, the spike, with an effect model, the slab...
February 13, 2018: Psychonomic Bulletin & Review
Aristóteles Góes-Neto, Marcelo V C Diniz, Daniel S Carvalho, Gilberto C Bomfim, Angelo A Duarte, Jerzy A Brzozowski, Thierry C Petit Lobão, Suani T R Pinho, Charbel N El-Hani, Roberto F S Andrade
Complex networks have been successfully applied to the characterization and modeling of complex systems in several distinct areas of Biological Sciences. Nevertheless, their utilization in phylogenetic analysis still needs to be widely tested, using different molecular data sets and taxonomic groups, and, also, by comparing complex networks approach to current methods in phylogenetic analysis. In this work, we compare all the four main methods of phylogenetic analysis (distance, maximum parsimony, maximum likelihood, and Bayesian) with a complex networks method that has been used to provide a phylogenetic classification based on a large number of protein sequences as those related to the chitin metabolic pathway and ATP-synthase subunits...
2018: PeerJ
Najla Saad Elhezzani
Linear mixed models (LMM) are widely used to estimate narrow sense heritability explained by tagged single-nucleotide polymorphisms (SNPs). However, those estimates are valid only if large sample sizes are used. We propose a Bayesian covariance component model (BCCM) that takes into account the genetic correlation among phenotypes and genetic correlation among individuals. The use of the BCCM allows us to circumvent issues related to small sample sizes, including overfitting and boundary estimates. Using expression of genes in breast cancer pathway, obtained from the Multiple Tissue Human Expression Resource (MuTHER) project, we demonstrate a significant improvement in the accuracy of SNP-based heritability estimates over univariate and likelihood-based methods...
February 13, 2018: European Journal of Human Genetics: EJHG
Chloé R Nater, Atle Rustadbakken, Torbjørn Ergon, Øystein Langangen, S Jannicke Moe, Yngvild Vindenes, L Asbjørn Vøllestad, Per Aass
Body size can have profound impacts on survival, movement, and reproductive schedules shaping individual fitness, making growth a central process in ecological and evolutionary dynamics. Realized growth is the result of a complex interplay between life history schedules, individual variation, and environmental influences. Integrating all of these aspects into growth models is methodologically difficult, depends on the availability of repeated measurements of identifiable individuals, and consequently represents a major challenge in particular for natural populations...
February 13, 2018: Ecology
Markus Drag, Mathias B Hansen, Haja N Kadarmideen
Boar taint is an offensive odour and/or taste from a proportion of non-castrated male pigs caused by skatole and androstenone accumulation during sexual maturity. Castration is widely used to avoid boar taint but is currently under debate because of animal welfare concerns. This study aimed to identify expression quantitative trait loci (eQTLs) with potential effects on boar taint compounds to improve breeding possibilities for reduced boar taint. Danish Landrace male boars with low, medium and high genetic merit for skatole and human nose score (HNS) were slaughtered at ~100 kg...
2018: PloS One
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