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Z Jiang, Z Dou, W L Song, J Xu, Z Y Wu
Objective: To compare results of different methods: in organizing HIV viral load (VL) data with missing values mechanism. Methods We used software SPSS 17.0 to simulate complete and missing data with different missing value mechanism from HIV viral loading data collected from MSM in 16 cities in China in 2013. Maximum Likelihood Methods Using the Expectation and Maximization Algorithm (EM), regressive method, mean imputation, delete method, and Markov Chain Monte Carlo (MCMC) were used to supplement missing data respectively...
November 10, 2017: Zhonghua Liu Xing Bing Xue za Zhi, Zhonghua Liuxingbingxue Zazhi
Emma Schwager, Himel Mallick, Steffen Ventz, Curtis Huttenhower
Compositional data consist of vectors of proportions normalized to a constant sum from a basis of unobserved counts. The sum constraint makes inference on correlations between unconstrained features challenging due to the information loss from normalization. However, such correlations are of long-standing interest in fields including ecology. We propose a novel Bayesian framework (BAnOCC: Bayesian Analysis of Compositional Covariance) to estimate a sparse precision matrix through a LASSO prior. The resulting posterior, generated by MCMC sampling, allows uncertainty quantification of any function of the precision matrix, including the correlation matrix...
November 15, 2017: PLoS Computational Biology
Wei Jiang, Hua Wang, Yu-Sheng Li, Tian-Jian Zhou, Xin-Jia Hu
There is no consensus on the optimal treatment for mid-shaft clavicular fracture. We conducted a meta-analysis to compare the effectiveness of non-operative treatment, plate fixation, and intramedullary pin fixation in terms of the Constant-Murley Score (CMS) for treatment of mid-shaft clavicular fracture. Comprehensive search of the Embase, Cochrane Library and PubMed was conducted to retrieve relevant randomized controlled trials (RCTs). A random-effect network meta-analysis was conducted within a Bayesian framework using Markov Chain Monte Carlo (MCMC) in OpenBUGS 3...
October 10, 2017: Oncotarget
John R Speakman
OBJECTIVES: Body fatness is widely assumed to be regulated by a lipostatic set-point system, which has evolved in response to trade-offs in the risks of mortality. Increasing fatness makes the risk of starvation lower but increases the risk of predation. Yet other models are available. The aim of this work is to evaluate using mathematical modeling whether set-point systems are more likely to evolve than the alternatives. METHODS: I modeled the trade-off in mortality risks using a simple mathematical model, which generates an optimum level of fatness that is presumed to be the driver for the evolution of a set-point...
October 21, 2017: Molecular Metabolism
Rocío Deanna, Gloria E Barboza, Carolina Carrizo García
Deprea is the genus with the second highest species richness in tribe Physalideae (Solanaceae) and comprises 50 species that are mainly distributed in the Andes of South America. The taxonomy of Deprea has been unstable after controversial hypotheses about its position and circumscription. Additionally, biogeographical inferences are only based on observations of the restricted area of distribution of some species and no ancestral area estimation have been performed. Here, we present a phylogenetic analysis and an ancestral area reconstruction of Deprea in order to establish its circumscription, resolve its position within Physalideae, and reconstruct its biogeographical history...
November 10, 2017: Molecular Phylogenetics and Evolution
Joseph E O'Reilly, Philip C J Donoghue
Consensus trees are required to summarise trees obtained through MCMC sampling of a posterior distribution, providing an overview of the distribution of estimated parameters such as topology, branch lengths and divergence times. Numerous consensus tree construction methods are available, each presenting a different interpretation of the tree sample. The rise of morphological clock and sampled-ancestor methods of divergence time estimation, in which times and topology are co-estimated, has increased the popularity of the maximum clade credibility (MCC) consensus tree method...
November 2, 2017: Systematic Biology
Bertil Wegmann, Anders Eklund, Mattias Villani
It is well-known that data from diffusion weighted imaging (DWI) follow the Rician distribution. The Rician distribution is also relevant for functional magnetic resonance imaging (fMRI) data obtained at high temporal or spatial resolution. We propose a general regression model for non-central χ (NC-χ) distributed data, with the heteroscedastic Rician regression model as a prominent special case. The model allows both parameters in the Rician distribution to be linked to explanatory variables, with the relevant variables chosen by Bayesian variable selection...
2017: Frontiers in Neuroscience
Xiaoyan Lin, Hua Chen, Don Edwards, Kerrie P Nelson
Many disease diagnoses involve subjective judgments by qualified raters. For example, through the inspection of a mammogram, MRI, or ultrasound image, the clinician himself becomes part of the measuring instrument. To reduce diagnostic errors and improve the quality of diagnoses, it is necessary to assess raters' diagnostic skills and to improve their skills over time. This paper focuses on a subjective binary classification process, proposing a hierarchical model linking data on rater opinions with patient true disease-development outcomes...
November 2, 2017: Statistics in Medicine
Panagiotis Papastamoulis, Magnus Rattray
Next generation sequencing allows the identification of genes consisting of differentially expressed transcripts, a term which usually refers to changes in the overall expression level. A specific type of differential expression is differential transcript usage (DTU) and targets changes in the relative within gene expression of a transcript. The contribution of this paper is to: (a) extend the use of cjBitSeq to the DTU context, a previously introduced Bayesian model which is originally designed for identifying changes in overall expression levels and (b) propose a Bayesian version of DRIMSeq, a frequentist model for inferring DTU...
November 1, 2017: Statistical Applications in Genetics and Molecular Biology
Alexander Wendel, James Underwood
Line scanning cameras, which capture only a single line of pixels, have been increasingly used in ground based mobile or robotic platforms. In applications where it is advantageous to directly georeference the camera data to world coordinates, an accurate estimate of the camera's 6D pose is required. This paper focuses on the common case where a mobile platform is equipped with a rigidly mounted line scanning camera, whose pose is unknown, and a navigation system providing vehicle body pose estimates. We propose a novel method that estimates the camera's pose relative to the navigation system...
October 30, 2017: Sensors
Ropo Ebenezer Ogunsakin, Lougue Siaka
Background: There has been no previous study to classify malignant breast tumor in details based on Markov Chain Monte Carlo (MCMC) convergence in Western, Nigeria. This study therefore aims to profile patients living with benign and malignant breast tumor in two different hospitals among women of Western Nigeria, with a focus on prognostic factors and MCMC convergence. Materials and Methods: A hospital-based record was used to identify prognostic factors for malignant breast cancer among women of Western Nigeria...
October 26, 2017: Asian Pacific Journal of Cancer Prevention: APJCP
Manupat Lohitnavy, Arnon Chitsakhon, Kritsada Jomprasert, Ornrat Lohitnavy, Brad Reisfeld
Paraquat (N, N'-dimethyl-4,4'-bipyridium dichloride) is a potent and widely used herbicide in agricultural countries, including Thailand. The presence of this chemical in the body can lead to toxic effects in the liver, kidney, and lung. Pulmonary toxicity has been identified as the main cause of acute toxicity in animals and humans. Chronic exposure to paraquat is associated with Parkinson's disease in humans. Paraquat is transported into the lungs by neutral amino acid transporter. Therefore, a physiologically based pharmacokinetic (PBPK) model of paraquat was developed with a description of the protein transporter mechanism...
July 2017: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Paul J Birrell, Richard G Pebody, André Charlett, Xu-Sheng Zhang, Daniela De Angelis
BACKGROUND: Real-time modelling is an essential component of the public health response to an outbreak of pandemic influenza in the UK. A model for epidemic reconstruction based on realistic epidemic surveillance data has been developed, but this model needs enhancing to provide spatially disaggregated epidemic estimates while ensuring that real-time implementation is feasible. OBJECTIVES: To advance state-of-the-art real-time pandemic modelling by (1) developing an existing epidemic model to capture spatial variation in transmission, (2) devising efficient computational algorithms for the provision of timely statistical analysis and (3) incorporating the above into freely available software...
October 2017: Health Technology Assessment: HTA
Erin M Shockley, Jasper A Vrugt, Carlos F Lopez
Summary: Biological models contain many parameters whose values are difficult to measure directly via experimentation and therefore require calibration against experimental data. Markov chain Monte Carlo (MCMC) methods are suitable to estimate multivariate posterior model parameter distributions, but these methods may exhibit slow or premature convergence in high-dimensional search spaces. Here, we present PyDREAM, a Python implementation of the (Multiple-Try) Differential Evolution Adaptive Metropolis (DREAM(ZS)) algorithm developed by Vrugt and ter Braak (2008) and Laloy and Vrugt (2012)...
October 4, 2017: Bioinformatics
Yang Zhao, Wei Zheng, Daisy Y Zhuo, Yuefeng Lu, Xiwen Ma, Hengchang Liu, Zhen Zeng, Glen Laird
Personalized medicine, or tailored therapy, has been an active and important topic in recent medical research. Many methods have been proposed in the literature for predictive biomarkers detection and subgroup identification. In this paper, we propose a novel decision tree based approach applicable in randomized clinical trials. We model the prognostic effects of the biomarkers using additive regression trees and the biomarker-by-treatment effect using a single regression tree. Bayesian approach is utilized to periodically revise the split variables and the split rules of the decision trees, which provides a better overall fitting...
October 11, 2017: Journal of Biopharmaceutical Statistics
Fabrícia F Nascimento, Mario Dos Reis, Ziheng Yang
Bayesian methods have become very popular in molecular phylogenetics due to the availability of user-friendly software implementing sophisticated models of evolution. However, Bayesian phylogenetic models are complex, and analyses are often carried out using default settings, which may not be appropriate. Here, we summarize the major features of Bayesian phylogenetic inference and discuss Bayesian computation using Markov chain Monte Carlo (MCMC), the diagnosis of an MCMC run, and ways of summarising the MCMC sample...
October 2017: Nature ecology & evolution
William Barcella, Maria De Iorio, Stefano Favaro, Gary L Rosner
We propose a novel Bayesian nonparametric process prior for modeling a collection of random discrete distributions. This process is defined by including a suitable Beta regression framework within a generalized Dirichlet process to induce dependence among the discrete random distributions. This strategy allows for covariate dependent clustering of the observations. Some advantages of the proposed approach include wide applicability, ease of interpretation, and availability of efficient MCMC algorithms. The motivation for this work is the study of the impact of asparginage metabolism on lipid levels in a group of pediatric patients treated for acute lymphoblastic leukemia...
September 6, 2017: Biostatistics
Zhenwen Dai, Mudassar Iqbal, Neil D Lawrence, Magnus Rattray
Motivation: Regulation of gene expression in prokaryotes involves complex co-regulatory mechanisms involving large numbers of transcriptional regulatory proteins and their target genes. Uncovering these genome-scale interactions constitutes a major bottleneck in systems biology. Sparse latent factor models, assuming activity of transcription factors (TFs) as unobserved, provide a biologically interpretable modelling framework, integrating gene expression and genome-wide binding data, but at the same time pose a hard computational inference problem...
August 26, 2017: Bioinformatics
Safi U Khan, Lydia Winnicka, Muhammad A Saleem, Hammad Rahman, Najeeb Rehman
Recent evidence challenges, the superiority of amiodarone, compared to other anti-arrhythmic medications, as the agent of choice in pulseless ventricular tachycardia (VT) or ventricular fibrillation (VF). We conducted Bayesian network and traditional meta-analyses to investigate the relative efficacies of amiodarone, lidocaine, magnesium (MgSO4) and placebo as treatments for pulseless VT or VF. Eleven studies [5200 patients, 7 randomized trials (4, 611 patients) and 4 non-randomized studies (589 patients)], were included in this meta-analysis...
November 2017: Heart & Lung: the Journal of Critical Care
DongHyuk Lee, Raymond J Carroll, Samiran Sinha
Frequentist standard errors are a measure of uncertainty of an estimator, and the basis for statistical inferences. Frequestist standard errors can also be derived for Bayes estimators. However, except in special cases, the computation of the standard error of Bayesian estimators requires bootstrapping, which in combination with Markov chain Monte Carlo (MCMC) can be highly time consuming. We discuss an alternative approach for computing frequentist standard errors of Bayesian estimators, including importance sampling...
September 2017: Computational Statistics
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