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    JCB
    2007
    191views more  JCB 2007»
    Bayesian Haplotype Inference via the Dirichlet Process
    13 years 7 months ago
    Bayesian Haplotype Inference via the Dirichlet Process
    Download  www.cs.berkeley.edu
    The problem of inferring haplotypes from genotypes of single nucleotide polymorphisms (SNPs) is essential for the understanding of genetic variation within and among populations, ...
    Eric P. Xing, Michael I. Jordan, Roded Sharan
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    ICML
    2008
    IEEE
    127views Machine Learning» more  ICML 2008»
    Memory bounded inference in topic models
    14 years 8 months ago
    Memory bounded inference in topic models
    Download  vision.caltech.edu
    What type of algorithms and statistical techniques support learning from very large datasets over long stretches of time? We address this question through a memory bounded version...
    Ryan Gomes, Max Welling, Pietro Perona
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    NIPS
    2004
    99views Information Technology» more  NIPS 2004»
    Inference, Attention, and Decision in a Bayesian Neural Architecture
    13 years 9 months ago
    Inference, Attention, and Decision in a Bayesian Neural Architecture
    Download  www.cogsci.ucsd.edu
    We study the synthesis of neural coding, selective attention and perceptual decision making. We build a hierarchical neural architecture that implements Bayesian integration of no...
    Angela J. Yu, Peter Dayan
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    JCB
    2007
    130views more  JCB 2007»
    Bayesian Inference of MicroRNA Targets from Sequence and Expression Data
    13 years 7 months ago
    Bayesian Inference of MicroRNA Targets from Sequence and Expression Data
    Download  morrislab.med.utoronto.ca
    MicroRNAs (miRNAs) regulate a large proportion of mammalian genes by hybridizing to targeted messenger RNAs (mRNAs) and down-regulating their translation into protein. Although mu...
    Jim C. Huang, Quaid Morris, Brendan J. Frey
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    BMCBI
    2007
    164views more  BMCBI 2007»
    Comparison of probabilistic Boolean network and dynamic Bayesian network approaches for inferring gene regulatory networks
    13 years 7 months ago
    Comparison of probabilistic Boolean network and dynamic Bayesian network approaches for inferring gene regulatory networks
    Download  www.biomedcentral.com
    Background: The regulation of gene expression is achieved through gene regulatory networks (GRNs) in which collections of genes interact with one another and other substances in a...
    Peng Li, Chaoyang Zhang, Edward J. Perkins, Ping G...
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