Browsing by Author "Liu, Jun"

Now showing items 1-20 of 112

    • An Adaptive Exchange Algorithm for Sampling From Distributions With Intractable Normalizing Constants 

      Liang, Faming; Jin, Ick Hoon; Song, Qifan; Liu, Jun (Informa UK Limited, 2016)
      Sampling from the posterior distribution for a model whose normalizing constant is intractable is a long-standing problem in statistical research. We propose a new algorithm, adaptive auxiliary variable exchange algorithm, ...

    • Advances in translational bioinformatics facilitate revealing the landscape of complex disease mechanisms 

      Yang, Jack Y; Dunker, A Keith; Liu, Jun S; Qin, Xiang; Arabnia, Hamid R; Yang, William; Niemierko, Andrzej; Chen, Zhongxue; Luo, Zuojie; Wang, Liangjiang; Liu, Yunlong; Xu, Dong; Deng, Youping; Tong, Weida; Yang, Mary Qu (BioMed Central, 2014)
      Advances of high-throughput technologies have rapidly produced more and more data from DNAs and RNAs to proteins, especially large volumes of genome-scale data. However, connection of the genomic information to cellular ...

    • Association pattern discovery via theme dictionary models 

      Deng, Ke; Geng, Zhi; Liu, Jun (Wiley-Blackwell, 2013)
      Discovering patterns from a set of text or, more generally, categorical data is an important problem in many disciplines such as biomedical research, linguistics, artificial intelligence and sociology. We consider here the ...

    • Assumptions behind Intercoder Reliability Indices 

      Zhao, Xinshu; Liu, Jun; Deng, Ke (Routledge, 2012)
      Inter-coder reliability is the most often used quantitative indicator of measurement quality in content studies. Researchers in psychology, sociology, education, medicine, marketing and other disciplines also use reliability ...

    • BALSA: Bayesian algorithm for local sequence alignment 

      Webb, B.-J. M.; Liu, Jun; Lawrence, Charles E. (Oxford University Press (OUP), 2002)
      The Smith–Waterman algorithm yields a single alignment, which, albeit optimal, can be strongly affected by the choice of the scoring matrix and the gap penalties. Additionally, the scores obtained are dependent upon the ...

    • Bayesian Analysis of Haplotypes for Linkage Disequilibrium Mapping 

      Liu, Jun; Sabatti, Chiara; Teng, Jun; Keats, Bronya J.B.; Risch, Neil (Cold Spring Harbor Laboratory Press, 2001)
      Haplotype analysis of disease chromosomes can help identify probable historical recombination events and localize disease mutations. Most available analyses use only marginal and pairwise allele frequency information. We ...

    • Bayesian Biclustering of Gene Expression Data 

      Liu, Jun; Gu, Jiajun (BioMed Central, 2008)
      Background: Biclustering of gene expression data searches for local patterns of gene expression. A bicluster (or a two-way cluster) is defined as a set of genes whose expression profiles are mutually similar within a subset ...

    • Bayesian Biclustering on Discrete Data: Variable Selection Methods 

      Guo, Lei (2013-10-18)
      Biclustering is a technique for clustering rows and columns of a data matrix simultaneously. Over the past few years, we have seen its applications in biology-related fields, as well as in many data mining projects. As ...

    • Bayesian Functional Data Clustering for Temporal Microarray Data 

      Ma, Ping; Zhong, Wenxuan; Feng, Yang; Liu, Jun (Hindawi Publishing Corporation, 2008)
      We propose a Bayesian procedure to cluster temporal gene expression microarray profiles, based on a mixed-effect smoothing-spline model, and design a Gibbs sampler to sample from the desired posterior distribution. Our ...

    • Bayesian Inference for Assessing Effects of Email Marketing Campaigns 

      Wu, Jiexing; Li, Kate J.; Liu, Jun (Informa UK Limited, 2016)
      Email marketing has been an increasingly important tool for today’s businesses. In this paper, we propose a counting-process-based Bayesian method for quantifying the effectiveness of email marketing campaigns in conjunction ...

    • Bayesian Inference of Spatial Organizations of Chromosomes 

      Hu, Ming; Deng, Ke; Qin, Zhaohui; Dixon, Jesse; Selvaraj, Siddarth; Fang, Jennifer; Ren, Bing; Liu, Jun (Public Library of Science, 2013)
      Knowledge of spatial chromosomal organizations is critical for the study of transcriptional regulation and other nuclear processes in the cell. Recently, chromosome conformation capture (3C) based technologies, such as ...

    • Bayesian meta-analysis for identifying periodically expressed genes in fission yeast cell cycle 

      Fan, Xiaodan; Pyne, Saumyadipta; Liu, Jun (Institute of Mathematical Statistics, 2010)
      The effort to identify genes with periodic expression during the cell cycle from genome-wide microarray time series data has been ongoing for a decade. However, the lack of rigorous modeling of periodic expression as well ...

    • Bayesian Models for Detecting Epistatic Interactions from Genetic Data 

      Zhang, Yu; Jiang, Bo; Zhu, Jun; Liu, Jun (Wiley-Blackwell, 2010)
      Current disease association studies are routinely conducted on a genome-wide scale, testing hundreds of thousands or millions of genetic markers. Besides detecting marginal associations of individual markers with the ...

    • Bayesian Models for Pooling Microarray Studies with Multiple Sources of Replications 

      Conlon, Erin M; Song, Joon J; Liu, Jun (BioMed Central, 2006)
      Background: Biologists often conduct multiple but different cDNA microarray studies that all target the same biological system or pathway. Within each study, replicate slides within repeated identical experiments are often ...

    • A Bayesian Partition Method for Detecting Pleiotropic and Epistatic eQTL Modules 

      Zhang, Wei; Zhu, Jun; Schadt, Eric E.; Liu, Jun; Stormo, Gary D. (Public Library of Science, 2010)
      Studies of the relationship between DNA variation and gene expression variation, often referred to as “expression quantitative trait loci (eQTL) mapping”, have been conducted in many species and resulted in many significant ...

    • Bayesian Partition Models for Identifying Expression Quantitative Trait Loci 

      Jiang, Bo; Liu, Jun (Informa UK Limited, 2015)
      Expression quantitative trait loci (eQTLs) are genomic locations associated with changes of expression levels of certain genes. By assaying gene expressions and genetic variations simultaneously on a genome-wide scale, ...

    • The Behaviour of 5-Hydroxymethylcytosine in Bisulfite Sequencing 

      Huang, Yun; Pastor, William Abraham; Shen, Yinghua; Tahiliani, Mamta V.; Liu, David Ruchien; Rao, Anjana; Liu, Jun (Public Library of Science, 2010)
      Background: We recently showed that enzymes of the TET family convert 5-mC to 5-hydroxymethylcytosine (5-hmC) in DNA. 5-hmC is present at high levels in embryonic stem cells and Purkinje neurons. The methylation status of ...

    • Biopolymer Structure Simulation and Optimization via Fragment Regrowth Monte Carlo 

      Zhang, Jinfeng; Kou, Samuel; Liu, Jun (American Institute of Physics, 2007)
      An efficient exploration of the configuration space of a biopolymer is essential for its structure modeling and prediction. In this study, the authors propose a new Monte Carlo method, fragment regrowth via energy-guided ...

    • Block-based Bayesian epistasis association mapping with application to WTCCC type 1 diabetes data 

      Zhang, Yu; Zhang, Jing; Liu, Jun (Institute of Mathematical Statistics, 2011)
      Interactions among multiple genes across the genome may contribute to the risks of many complex human diseases. Whole-genome single nucleotide polymorphisms (SNPs) data collected for many thousands of SNP markers from ...

    • Broadly heterogeneous activation of the master regulator for sporulation in Bacillus subtilis 

      Chastanet, A.; Vitkup, D.; Yuan, Guocheng; Norman, Thomas Maxwell; Liu, Jun; Losick, Richard M. (Proceedings of the National Academy of Sciences, 2010)
      A model system for investigating how developmental regulatory networks determine cell fate is spore formation in Bacillus subtilis. The master regulator for sporulation is Spo0A, which is activated by phosphorylation via ...