Bayesian clustering
Melissa: Bayesian clustering and imputation of single cell methylomes
... a Bayesian hierarchical model that jointly learns the methy- lation profiles of genomic regions of interest and clusters cells based on their genome-wide methylation ...a Bayesian clustering approach ...
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Differing lifestyles of Staphylococcus epidermidis as revealed through Bayesian clustering of multilocus sequence types
... The MLST database represents the most complete catalog of S. epidermidis genetic variants at present, but we do not presume that it includes examples of all S. epidermidis lineages. Since the improved MLST scheme for S. ...
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Bayesian Clustering Using Hidden Markov Random Fields in Spatial Population Genetics
... a Bayesian clustering algorithm that incorporates hidden Markov random fields as prior dis- tributions on cluster ...a Bayesian framework generates con- ceptual difficulties because its stationary ...
12
Guided conjugate Bayesian clustering for uncovering rhythmically expressed genes
... However, the posterior distributions of the clusters in a chosen partition are entirely valid provided that we accept that they are based only on data from the genes they contain. So, as well as providing useful ...
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Genetic components of grey cattle in Estonia as revealed by microsatellite analysis using two Bayesian clustering methods
... A Bayesian clustering method was first employed to assess population structure using the program STRUC- TURE version 2.2 [11]. We performed 10 runs for each K value at 2 - 10 and ran the program assuming a ...
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Bayesian clustering of curves and the search of the partition space
... as clustering is often used as an exploratory technique to reduce the dimensionality of the data and choosing the number of clusters a priori is not always possible or sensible, especially because often in ...
220
The expanding pattern of Aedes aegypti in southern Yunnan, China: insights from microsatellite and mitochondrial DNA markers
... Genetic distance was calculated using GenAIEx (ver- sion 6.501) [26], and the result was used to conduct principal components analysis (PCoA) based on the codom-genotypic genetic distance. A neighbour-join- ing (NJ) tree ...
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Ecological and genetic relationships of the Forest M form among chromosomal and molecular forms of the malaria vector Anopheles gambiae sensu stricto
... for Bayesian clustering analysis of seven markers which include geno- types of molecular form and of 2La, 2Rj, 2Rb, 2Rc, 2Rd, and 2Ru chromosome ...of Bayesian analysis, either input represents ...
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Amazon divergence and cross Andean dispersal of a widespread Neotropical tree species (Jacaranda copaia, Bignoniaceae)
... cient information in the data to correctly resolve migration rates; alternatively, the model may not account for gene flow from populations not included in the scenario, even though Bayesian clustering ...
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Microsatellite Based Genetic Structure and Differentiation of Goldfish (Carassius auratus) with Sarcoma
... Furthermore, two methods were used to further reveal population differentiation in the studied samples. First, a principal components analysis (PCA) was performed using GENALEX version 6.1 [22] to reveal the internal ...
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A Tightly coupled Unsupervised Clustering and Bilingual Alignment Model for Transliteration
... We propose a simple, elegant, fully- unsupervised solution based on a single generative model able to both cluster and align simultaneous- ly. The coupled Dirichlet Process Mixture Model (cDPMM) integrates a Dirichlet ...
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A Bayesian space-time model for clustering areal units based on their disease trends
... the clustering par- adigm to group areas together that exhibit similar temporal risk ...propose clustering methodology to group areas together based on sharing common latent temporal trends, but the ...
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Detect Frauds in Credit Card using Data Mining Techniques
... K-mean clustering algorithm, K- nearest neighbor, Decision Tree, Fusion approach due using dumpster Shafer, Bayesian Network, Neural Network, SVM and Logistic Regression are ...
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Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics
... hierarchical clustering structure which is more informative than a flat ...uses Bayesian model selection to determine the hierarchical structure, rather than an ad hoc distance metric, thereby increasing ...
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Bayesian hierarchical clustering for microarray time series data with replicates and outlier measurements
... The Bayesian Hierarchical Clustering (BHC) algorithm [13] is a fast approximate inference method for a Dirich- let process mixture model, which performs agglomera- tive hierarchical clustering in a ...
13
Advances in Nonparametric Bayesian Methods for Clustering and Classification.
... nonparametric Bayesian model (Ghosh and Ramamoorthi, 2003) accomplishes both clustering and classification via discrimi- nant ...and clustering purposes (Jackson et ...the Bayesian false ...
94
Quantum and algorithmic Bayesian mechanisms
... for Bayesian implementation shall be amended by virtue of a quantum Bayesian ...algorithmic Bayesian mechanism, this amendment holds in the macro world ...
14
Title: Detection and Recovery of Faulty Nodes Using Clustering Optimization and Bayesian Analysis in Wireless Sensor Networks
... The task of accurately reconstructing a distributed signal through the collection of a small number of samples at a data gathering point using Compressive Sensing (CS) in conjunction with Principal Component Analysis ...
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Scalable Matching and Clustering of Entities with FAMER
... supports clustering matching entities and exploits both blocking and distributed (parallel) ...multiple clustering schemes to group matching entities; and the main goal of this article is to comparatively ...
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Lossless Online Bayesian Bagging
... Thus Bayesian bagging will generally have the same expected point estimates as ordinary ...under Bayesian bagging, as the variability of the weights is n+1 n times that of ordinary ...the Bayesian ...
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