4期

最新文章

• ESTIMATING THE RATE CONSTANT FROM BIOSENSOR DATA VIA AN ADAPTIVE VARIATIONAL BAYESIAN APPROACH AI翻译
  作者：Zhang, Ye; Yao, Zhigang; Forssen, Patrik; Fornstedt, Torgny
  作者单位：Technische Universitat Chemnitz; National University of Singapore; Karlstad University
  摘要：The means to obtain the rate constants of a chemical reaction is a fundamental open problem in both science and the industry. Traditional techniques for finding rate constants require either chemical modifications of the reactants or indirect measurements. The rate constant map method is a modern technique to study binding equilibrium and kinetics in chemical reactions. Finding a rate constant map from biosensor data is an ill-posed inverse problem that is usually solved by regularization. In ...
• A GENERAL THEORY FOR PREFERENTIAL SAMPLING IN ENVIRONMENTAL NETWORKS AI翻译
  作者：Watson, Joe; Zidek, James, V; Shaddick, Gavin
  作者单位：University of British Columbia; University of Exeter
  摘要：This paper presents a general model framework for detecting the preferential sampling of environmental monitors recording an environmental process across space and/or time. This is achieved by considering the joint distribution of an environmental process with a site-selection process that considers where and when sites are placed to measure the process. The environmental process may be spatial, temporal or spatio-temporal in nature. By sharing random effects between the two processes, the joi...
• A SIMPLE, CONSISTENT ESTIMATOR OF SNP HERITABILITY FROM GENOME-WIDE ASSOCIATION STUDIES AI翻译
  作者：Schwartzman, Armin; Schork, Andrew J.; Zablocki, Rong; Thompson, Wesley K.
  作者单位：University of California System; University of California San Diego; University of California System; University of California San Diego
  摘要：Analysis of genome-wide association studies (GWAS) is characterized by a large number of univariate regressions where a quantitative trait is regressed on hundreds of thousands to millions of single-nucleotide polymorphism (SNP) allele counts, one at a time. This article proposes an estimator of the SNP heritability of the trait, defined here as the fraction of the variance of the trait explained by the SNPs in the study. The proposed GWAS heritability (GWASH) estimator is easy to compute, hig...
• BAYESIAN INDICATOR VARIABLE SELECTION TO INCORPORATE HIERARCHICAL OVERLAPPING GROUP STRUCTURE IN MULTI-OMICS APPLICATIONS AI翻译
  作者：Zhu, Li; Huo, Zhiguang; Ma, Tianzhou; Oesterreich, Steffi; Tseng, George C.
  作者单位：Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; State University System of Florida; University of Florida; University System of Maryland; University of Maryland College Park; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh; Pennsylvania Commonwealth System of Higher Education (PCSHE); University of Pittsburgh
  摘要：Variable selection is a pervasive problem in modern high-dimensional data analysis where the number of features often exceeds the sample size (a.k.a. small-n-large-p problem). Incorporation of group structure knowledge to improve variable selection has been widely studied. Here, we consider prior knowledge of a hierarchical overlapping group structure to improve variable selection in regression setting. In genomics applications, for instance, a biological pathway contains tens to hundreds of g...
• PREDICTING PALEOCLIMATE FROM COMPOSITIONAL DATA USING MULTIVARIATE GAUSSIAN PROCESS INVERSE PREDICTION AI翻译
  作者：Tipton, John R.; Hooten, Mevin B.; Nolan, Connor; Booth, Robert K.; McLachlan, Jason
  作者单位：University of Arkansas System; University of Arkansas Fayetteville; Colorado State University System; Colorado State University Fort Collins; United States Department of the Interior; United States Geological Survey; University of Arizona; Lehigh University; University of Notre Dame
  摘要：Multivariate compositional count data arise in many applications including ecology, microbiology, genetics and paleoclimate. A frequent question in the analysis of multivariate compositional count data is what underlying values of a covariate(s) give rise to the observed composition. Learning the relationship between covariates and the compositional count allows for inverse prediction of unobserved covariates given compositional count observations. Gaussian processes provide a flexible framewo...
• FITTING A DEEPLY NESTED HIERARCHICAL MODEL TO A LARGE BOOK REVIEW DATASET USING A MOMENT-BASED ESTIMATOR AI翻译
  作者：Zhang, Ningshan; Schmaus, Kyle; Perry, Patrick O.
  作者单位：New York University
  摘要：We consider a particular instance of a common problem in recommender systems, using a database of book reviews to inform user-targeted recommendations. In our dataset, books are categorized into genres and subgenres. To exploit this nested taxonomy, we use a hierarchical model that enables information pooling across across similar items at many levels within the genre hierarchy. The main challenge in deploying this model is computational. The data sizes are large and fitting the model at scale...
• A LATENT DISCRETE MARKOV RANDOM FIELD APPROACH TO IDENTIFYING AND CLASSIFYING HISTORICAL FOREST COMMUNITIES BASED ON SPATIAL MULTIVARIATE TREE SPECIES COUNTS AI翻译
  作者：Berg, Stephen; Zhu, Jun; Clayton, Murray K.; Shea, Monika E.; Mladenoff, David J.
  作者单位：University of Wisconsin System; University of Wisconsin Madison; University of Wisconsin System; University of Wisconsin Madison
  摘要：The Wisconsin Public Land Survey database describes historical forest composition at high spatial resolution and is of interest in ecological studies of forest composition in Wisconsin just prior to significant Euro-American settlement. For such studies it is useful to identify recurring subpopulations of tree species known as communities, but standard clustering approaches for subpopulation identification do not account for dependence between spatially nearby observations. Here, we develop an...
• EMPIRICAL BAYES ANALYSIS OF RNA SEQUENCING EXPERIMENTS WITH AUXILIARY INFORMATION AI翻译
  作者：Liang, Kun
  作者单位：University of Waterloo
  摘要：Finding differentially expressed genes is a common task in high-throughput transcriptome studies. While traditional statistical methods rank the genes by their test statistics alone, we analyze an RNA sequencing dataset using the auxiliary information of gene length and the test statistics from a related microarray study. Given the auxiliary information, we propose a novel nonparametric empirical Bayes procedure to estimate the posterior probability of differential expression for each gene. We...
• JOINT MODEL OF ACCELERATED FAILURE TIME AND MECHANISTIC NONLINEAR MODEL FOR CENSORED COVARIATES, WITH APPLICATION IN HIV/AIDS AI翻译
  作者：Zhang, Hongbin; Wu, Lang
  作者单位：City University of New York (CUNY) System; University of British Columbia
  摘要：For a time-to-event outcome with censored time-varying covariates, a joint Cox model with a linear mixed effects model is the standard modeling approach. In some applications such as AIDS studies, mechanistic nonlinear models are available for some covariate process such as viral load during anti-HIV treatments, derived from the underlying data-generation mechanisms and disease progression. Such a mechanistic nonlinear covariate model may provide better-predicted values when the covariates are...
• A NONPARAMETRIC SPATIAL TEST TO IDENTIFY FACTORS THAT SHAPE A MICROBIOME AI翻译
  作者：Singh, Susheela P.; Staicu, Ana-Maria; Dunn, Robert R.; Fierer, Noah; Reich, Brian J.
  作者单位：North Carolina State University
  摘要：The advent of high-throughput sequencing technologies has made data from DNA material readily available, leading to a surge of microbiome-related research establishing links between markers of microbiome health and specific outcomes. However, to harness the power of microbial communities we must understand not only how they affect us, but also how they can be influenced to improve outcomes. This area has been dominated by methods that reduce community composition to summary metrics, which can ...