18 results on '"Markov-chain Monte Carlo (MCMC)"'
Search Results
2. Genome-wide association study of anogenital distance and its (co)variances with fertility in growing and lactating Holstein-Friesian dairy cattle
- Author
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M.A. Stephen, C.R. Burke, N. Steele, J.E. Pryce, S. Meier, P.R. Amer, C.V.C. Phyn, and D.J. Garrick
- Subjects
Bayesian ,cattle ,Markov-chain Monte Carlo (MCMC) ,androgen ,Dairy processing. Dairy products ,SF250.5-275 ,Dairying ,SF221-250 - Abstract
ABSTRACT: Anogenital distance (AGD) is a moderately heritable trait that can be measured at a young age that may provide an opportunity to indirectly select for improved fertility in dairy cattle. In this study, we characterized AGD and its genetic and phenotypic relationships with a range of body stature and fertility traits. We measured AGD, shoulder height, body length, and body weight in a population of 5,010 Holstein-Friesian and Holstein-Friesian × Jersey crossbred heifers at approximately 11 mo of age (AGD1). These animals were born in 2018 across 54 seasonal calving, pasture-based dairy herds. A second measure of AGD was collected in a subset of herds (n = 17; 1,956 animals) when the animals averaged 29 mo of age (AGD2). Fertility measures included age at puberty (AGEP), then time of calving, breeding, and pregnancy during the first and second lactations. We constructed binary traits reflecting the animal's ability to calve during the first 42 d of their herd's seasonal calving period (CR42), be presented for breeding during the first 21 d of the seasonal breeding period (PB21) and become pregnant during the first 42 d of the seasonal breeding period (PR42). The posterior mean of sampled heritabilities for AGD1 was 0.23, with 90% of samples falling within a credibility interval (90% CRI) of 0.20 to 0.26, whereas the heritability of AGD2 was 0.29 (90% CRI 0.24 to 0.34). The relationship between AGD1 and AGD2 was highly positive, with a genetic correlation of 0.89 (90% CRI 0.82 to 0.94). Using a GWAS analysis of 2,460 genomic windows based on 50k genotype data, we detected a region on chromosome 20 that was highly associated with variation in AGD1, and a second region on chromosome 13 that was moderately associated with variation in AGD1. We did not detect any genomic regions associated with AGD2 which was measured in fewer animals. The genetic correlation between AGD1 and AGEP was 0.10 (90% CRI 0.00 to 0.19), whereas the genetic correlation between AGD2 and AGEP was 0.30 (90% CRI 0.15 to 0.44). The timing of calving, breeding, and pregnancy (CR42, PB21, and PR42) during first or second lactations exhibited moderate genetic relationships with AGD1 (0.19 to 0.52) and AGD2 (0.46 to 0.63). Genetic correlations between AGD and body stature traits were weak (≤0.16). We conclude that AGD is a moderately heritable trait, which may have value as an early-in-life genetic predictor for reproductive success during lactation.
- Published
- 2023
- Full Text
- View/download PDF
3. Comparison of methods for deriving phenotypes from incomplete observation data with an application to age at puberty in dairy cattle
- Author
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Melissa A. Stephen, Chris R. Burke, Jennie E. Pryce, Nicole M. Steele, Peter R. Amer, Susanne Meier, Claire V. C. Phyn, and Dorian J. Garrick
- Subjects
Cattle ,Gibbs sampler ,Markov-chain Monte Carlo (MCMC) ,Puberty ,Animal culture ,SF1-1100 ,Veterinary medicine ,SF600-1100 - Abstract
Abstract Background Many phenotypes in animal breeding are derived from incomplete measures, especially if they are challenging or expensive to measure precisely. Examples include time-dependent traits such as reproductive status, or lifespan. Incomplete measures for these traits result in phenotypes that are subject to left-, interval- and right-censoring, where phenotypes are only known to fall below an upper bound, between a lower and upper bound, or above a lower bound respectively. Here we compare three methods for deriving phenotypes from incomplete data using age at first elevation (> 1 ng/mL) in blood plasma progesterone (AGEP4), which generally coincides with onset of puberty, as an example trait. Methods We produced AGEP4 phenotypes from three blood samples collected at about 30-day intervals from approximately 5,000 Holstein–Friesian or Holstein–Friesian × Jersey cross-bred dairy heifers managed in 54 seasonal-calving, pasture-based herds in New Zealand. We used these actual data to simulate 7 different visit scenarios, increasing the extent of censoring by disregarding data from one or two of the three visits. Three methods for deriving phenotypes from these data were explored: 1) ordinal categorical variables which were analysed using categorical threshold analysis; 2) continuous variables, with a penalty of 31 d assigned to right-censored phenotypes; and 3) continuous variables, sampled from within a lower and upper bound using a data augmentation approach. Results Credibility intervals for heritability estimations overlapped across all methods and visit scenarios, but estimated heritabilities tended to be higher when left censoring was reduced. For sires with at least 5 daughters, the correlations between estimated breeding values (EBVs) from our three-visit scenario and each reduced data scenario varied by method, ranging from 0.65 to 0.95. The estimated breed effects also varied by method, but breed differences were smaller as phenotype censoring increased. Conclusion Our results indicate that using some methods, phenotypes derived from one observation per offspring for a time-dependent trait such as AGEP4 may provide comparable sire rankings to three observations per offspring. This has implications for the design of large-scale phenotyping initiatives where animal breeders aim to estimate variance parameters and estimated breeding values (EBVs) for phenotypes that are challenging to measure or prohibitively expensive.
- Published
- 2023
- Full Text
- View/download PDF
4. Comparison of methods for deriving phenotypes from incomplete observation data with an application to age at puberty in dairy cattle.
- Author
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Stephen, Melissa A., Burke, Chris R., Pryce, Jennie E., Steele, Nicole M., Amer, Peter R., Meier, Susanne, Phyn, Claire V. C., and Garrick, Dorian J.
- Subjects
DAIRY cattle ,PHENOTYPES ,PUBERTY ,ANIMAL breeders ,ANIMAL breeding ,BLOOD plasma ,MILK quality ,CATTLE fertility - Abstract
Background: Many phenotypes in animal breeding are derived from incomplete measures, especially if they are challenging or expensive to measure precisely. Examples include time-dependent traits such as reproductive status, or lifespan. Incomplete measures for these traits result in phenotypes that are subject to left-, interval- and right-censoring, where phenotypes are only known to fall below an upper bound, between a lower and upper bound, or above a lower bound respectively. Here we compare three methods for deriving phenotypes from incomplete data using age at first elevation (> 1 ng/mL) in blood plasma progesterone (AGEP4), which generally coincides with onset of puberty, as an example trait. Methods: We produced AGEP4 phenotypes from three blood samples collected at about 30-day intervals from approximately 5,000 Holstein–Friesian or Holstein–Friesian × Jersey cross-bred dairy heifers managed in 54 seasonal-calving, pasture-based herds in New Zealand. We used these actual data to simulate 7 different visit scenarios, increasing the extent of censoring by disregarding data from one or two of the three visits. Three methods for deriving phenotypes from these data were explored: 1) ordinal categorical variables which were analysed using categorical threshold analysis; 2) continuous variables, with a penalty of 31 d assigned to right-censored phenotypes; and 3) continuous variables, sampled from within a lower and upper bound using a data augmentation approach. Results: Credibility intervals for heritability estimations overlapped across all methods and visit scenarios, but estimated heritabilities tended to be higher when left censoring was reduced. For sires with at least 5 daughters, the correlations between estimated breeding values (EBVs) from our three-visit scenario and each reduced data scenario varied by method, ranging from 0.65 to 0.95. The estimated breed effects also varied by method, but breed differences were smaller as phenotype censoring increased. Conclusion: Our results indicate that using some methods, phenotypes derived from one observation per offspring for a time-dependent trait such as AGEP4 may provide comparable sire rankings to three observations per offspring. This has implications for the design of large-scale phenotyping initiatives where animal breeders aim to estimate variance parameters and estimated breeding values (EBVs) for phenotypes that are challenging to measure or prohibitively expensive. [ABSTRACT FROM AUTHOR]
- Published
- 2023
- Full Text
- View/download PDF
5. Update of the keratin gene family: evolution, tissue-specific expression patterns, and relevance to clinical disorders.
- Author
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Ho, Minh, Thompson, Brian, Fisk, Jeffrey Nicholas, Nebert, Daniel W., Bruford, Elspeth A., Vasiliou, Vasilis, and Bunick, Christopher G.
- Abstract
Intermediate filament (IntFil) genes arose during early metazoan evolution, to provide mechanical support for plasma membranes contacting/interacting with other cells and the extracellular matrix. Keratin genes comprise the largest subset of IntFil genes. Whereas the first keratin gene appeared in sponge, and three genes in arthropods, more rapid increases in keratin genes occurred in lungfish and amphibian genomes, concomitant with land animal-sea animal divergence (~ 440 to 410 million years ago). Human, mouse and zebrafish genomes contain 18, 17 and 24 non-keratin IntFil genes, respectively. Human has 27 of 28 type I "acidic" keratin genes clustered at chromosome (Chr) 17q21.2, and all 26 type II "basic" keratin genes clustered at Chr 12q13.13. Mouse has 27 of 28 type I keratin genes clustered on Chr 11, and all 26 type II clustered on Chr 15. Zebrafish has 18 type I keratin genes scattered on five chromosomes, and 3 type II keratin genes on two chromosomes. Types I and II keratin clusters—reflecting evolutionary blooms of keratin genes along one chromosomal segment—are found in all land animal genomes examined, but not fishes; such rapid gene expansions likely reflect sudden requirements for many novel paralogous proteins having divergent functions to enhance species survival following sea-to-land transition. Using data from the Genotype-Tissue Expression (GTEx) project, tissue-specific keratin expression throughout the human body was reconstructed. Clustering of gene expression patterns revealed similarities in tissue-specific expression patterns for previously described "keratin pairs" (i.e., KRT1/KRT10, KRT8/KRT18, KRT5/KRT14, KRT6/KRT16 and KRT6/KRT17 proteins). The ClinVar database currently lists 26 human disease-causing variants within the various domains of keratin proteins. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
6. Joint Adaptation of ICP Proposal and Target Distribution for Probabilistic Surface Registration.
- Author
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Hou, Zeyi and Zhou, Xiuzhuang
- Subjects
RECORDING & registration ,MARKOV chain Monte Carlo ,MARKOV processes ,SURFACE preparation - Abstract
Non-rigid surface registration plays a crucial role in various vision applications. Recent advances in probabilistic surface registration implied the effectiveness of Markov-chain Monte Carlo (MCMC) sampling with ICP-based proposals. Despite the progress, the ICP proposal is still less informed for sampling from highly multi-modal parameter space of deformation field, and hence inferred registration solutions can be of limited accuracy. In this letter, we propose to jointly learn the ICP proposal and target distribution in a unified framework, where the step-size of the proposal and the invariant distribution are both adaptively adjusted during sampling, by making full use of geometric and statistical characteristics underlying history samples. Under the conditions of adaptation diminishing, the two adaptation modules can benefit from each other, leading to boosted registration accuracy. Experimental results on surfaces extracted from the SICAS Medical Image Repository demonstrate the improvements in terms of registration accuracy and convergence speed compared to alternative algorithms. [ABSTRACT FROM AUTHOR]
- Published
- 2022
- Full Text
- View/download PDF
7. Update of the keratin gene family: evolution, tissue-specific expression patterns, and relevance to clinical disorders
- Author
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Minh Ho, Brian Thompson, Jeffrey Nicholas Fisk, Daniel W. Nebert, Elspeth A. Bruford, Vasilis Vasiliou, Christopher G. Bunick, Bunick, Christopher G [0000-0002-4011-8308], Apollo - University of Cambridge Repository, Bunick, Christopher G. [0000-0002-4011-8308], and Bruford, Elspeth [0000-0002-8380-5247]
- Subjects
Intermediate filament ,Genome ,integumentary system ,Gene Family Update ,QH426-470 ,Gene duplications ,Synteny ,MrBayes program to estimate phylogeny ,Mice ,Keratin ,Evolutionary blooms ,Drug Discovery ,Genetics ,Keratins, Type I ,Molecular Medicine ,Medicine ,Markov-chain Monte Carlo (MCMC) ,Animals ,Keratins ,Gene expression ,Molecular Biology ,Zebrafish - Abstract
Intermediate filament (IntFil) genes arose during early metazoan evolution, to provide mechanical support for plasma membranes contacting/interacting with other cells and the extracellular matrix. Keratin genes comprise the largest subset of IntFil genes. Whereas the first keratin gene appeared in sponge, and three genes in arthropods, more rapid increases in keratin genes occurred in lungfish and amphibian genomes, concomitant with land animal-sea animal divergence (~ 440 to 410 million years ago). Human, mouse and zebrafish genomes contain 18, 17 and 24 non-keratin IntFil genes, respectively. Human has 27 of 28 type I “acidic” keratin genes clustered at chromosome (Chr) 17q21.2, and all 26 type II “basic” keratin genes clustered at Chr 12q13.13. Mouse has 27 of 28 type I keratin genes clustered on Chr 11, and all 26 type II clustered on Chr 15. Zebrafish has 18 type I keratin genes scattered on five chromosomes, and 3 type II keratin genes on two chromosomes. Types I and II keratin clusters—reflecting evolutionary blooms of keratin genes along one chromosomal segment—are found in all land animal genomes examined, but not fishes; such rapid gene expansions likely reflect sudden requirements for many novel paralogous proteins having divergent functions to enhance species survival following sea-to-land transition. Using data from the Genotype-Tissue Expression (GTEx) project, tissue-specific keratin expression throughout the human body was reconstructed. Clustering of gene expression patterns revealed similarities in tissue-specific expression patterns for previously described “keratin pairs” (i.e., KRT1/KRT10, KRT8/KRT18, KRT5/KRT14, KRT6/KRT16 and KRT6/KRT17 proteins). The ClinVar database currently lists 26 human disease-causing variants within the various domains of keratin proteins. Supplementary Information The online version contains supplementary material available at 10.1186/s40246-021-00374-9.
- Published
- 2022
8. Maximum likelihood and Bayesian estimators for the double Poisson distribution
- Author
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Aragon, Davi C., Achcar, Jorge A., and Martinez, Edson Z.
- Published
- 2018
- Full Text
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9. A Bayesian approach based on a Markov-chain Monte Carlo method for damage detection under unknown sources of variability.
- Author
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Figueiredo, Eloi, Radu, Lucian, Worden, Keith, and Farrar, Charles R.
- Subjects
- *
STRUCTURAL health monitoring , *BAYESIAN analysis , *MARKOV chain Monte Carlo , *DAMAGE models , *PATTERN recognition systems , *MATHEMATICAL programming , *DATA analysis - Abstract
In the Structural Health Monitoring of bridges, the effects of the operational and environmental variability on the structural responses have posed several challenges for early damage detection. In order to overcome those challenges, in the last decade recourse has been made to the statistical pattern recognition paradigm based on vibration data from long-term monitoring. This paradigm has been characterized by the use of purely data-based algorithms that do not depend on the physical descriptions of the structures. However, one drawback of this procedure is how to set up the baseline condition for new and existing bridges. Therefore, this paper proposes an algorithm with a Bayesian approach based on a Markov-chain Monte Carlo method to cluster structural responses of the bridges into a reduced number of global state conditions, by taking into account eventual multimodality and heterogeneity of the data distribution. This approach stands as an improvement over the classical maximum likelihood estimation based on the expectation–maximization algorithm. Along with the Mahalanobis squared-distance, this approach permits one to form an algorithm able to detect structural damage based on daily response data even under abnormal events caused by temperature variability. The applicability of this approach is demonstrated on standard data sets from a real-world bridge in Switzerland, namely the Z-24 Bridge. The analysis suggests that this algorithm might be useful for bridge applications because it permits one to overcome some of the limitations posed by the pattern recognition paradigm, especially when dealing with limited amounts of training data and/or data with nonlinear temperature dependency. [ABSTRACT FROM AUTHOR]
- Published
- 2014
- Full Text
- View/download PDF
10. Hyperpolarized [1,13C]pyruvate in lysed human erythrocytes: effects of co-substrate supply on reaction time courses.
- Author
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Pagès, Guilhem, Tan, Yee Ling, and Kuchel, Philip W.
- Abstract
Hyperpolarized [1,
13 C]pyruvate was injected rapidly into haemolysates in which hydrolysis of nicotinamide adenine dinucleotide (phosphate) (NAD(P))/NAD(P)H had been inhibited with nicotinamide. Haemolysates provide a stable glycolytic system in which membrane permeability is not a flux-controlling step, and they enable the concentration of NADH to be adjusted experimentally while keeping the rest of the sample with the same composition as that of the cytoplasm of the cell (albeit diluted twofold at the time of injection of the [1,13 C]pyruvate). We showed that the maximum amplitude of the13 C NMR signal from the [1,13 C] l-lactate, produced from [1,13 C]pyruvate, and the time at which it occurred was dependent on NADH concentration, as predicted by enzyme-kinetic analysis. The main feature of such curves was dictated by the immediacy of the supply of the co-substrate of lactate dehydrogenase (LDH, EC 1.1.1.27), and we posit that this also pertains in vivo in various tissues including neoplasms. By constructing an appropriate mathematical model and by using a Markov-chain Monte Carlo approach, we fitted experimental data to estimate LDH and NADH concentrations. Experiments carried out with only endogenous NADH present enabled the estimation of its effective concentration in human RBCs; the ability to make this estimate is a special feature of the rapid-dissolution dynamic nuclear polarization method. We found an endogenous NADH concentration in human RBCs two to four times higher than previously reported. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]- Published
- 2014
- Full Text
- View/download PDF
11. Bayesian regression in SAS software.
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Sullivan, Sheena G and Greenland, Sander
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- *
REGRESSION analysis , *MARKOV chain Monte Carlo , *COMPUTER software , *BAYESIAN analysis , *PROPORTIONAL hazards models , *POISSON processes - Abstract
Bayesian methods have been found to have clear utility in epidemiologic analyses involving sparse-data bias or considerable background information. Easily implemented methods for conducting Bayesian analyses by data augmentation have been previously described but remain in scant use. Thus, we provide guidance on how to do these analyses with ordinary regression software. We describe in detail and provide code for the implementation of data augmentation for Bayesian and semi-Bayes regression in SAS® software, and illustrate their use in a real logistic-regression analysis. For comparison, the same model was fitted using the Markov-chain Monte Carlo (MCMC) procedure. The two methods required a similar number of steps and yielded similar results, although for the main example, data augmentation ran in about 0.5% of the time required for MCMC. We also provide online appendices with details and examples for conditional logistic, Poisson and Cox proportional-hazards regression. [ABSTRACT FROM PUBLISHER]
- Published
- 2013
- Full Text
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12. A Bayesian Approach for PK/PD Modeling with PD Data Below Limit of Quantification.
- Author
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Zhou, Huafeng, Hartford, Alan, and Tsai, Kuenhi
- Subjects
- *
BAYESIAN analysis , *PREDICATE calculus , *PHARMACOKINETICS , *MONTE Carlo method , *CASE studies - Abstract
A Bayesian approach to handling below limit of quantification (BLOQ) pharmacodynamic (PD) data in pharmacokinetic/pharmacodynamic (PK/PD) modeling is described. The inhibitory sigmoid Emax model is used to illustrate the implementation of the Bayesian approach for modeling BLOQ PD data. Details on how to implement this Bayesian approach via the Markov-chain Monte Carlo (MCMC) technique using WinBUGS software are presented. A simulation study was conducted to evaluate the performance of the proposed Bayesian approach and to compare the Bayesian approach with two other ad hoc approaches: replacing BLOQ data with LOQ, and ignoring the BLOQ data. The simulation study indicates that the proposed Bayesian approach performs better than the other two ad hoc approaches and should be considered in practice as a complementary tool for BLOQ data analysis. A case study with real PK/PD data is provided to illustrate the application of the Bayesian approach of handling BLOQ PD data in PK/PD modeling. [ABSTRACT FROM AUTHOR]
- Published
- 2012
- Full Text
- View/download PDF
13. Abrupt Motion Tracking Via Intensively Adaptive Markov-Chain Monte Carlo Sampling.
- Author
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Zhou, Xiuzhuang, Lu, Yao, Lu, Jiwen, and Zhou, Jie
- Subjects
- *
MARKOV processes , *MOTION analysis , *MONTE Carlo method , *ROBOT vision , *BAYESIAN analysis , *TRACKING algorithms , *STOCHASTIC approximation - Abstract
The robust tracking of abrupt motion is a challenging task in computer vision due to its large motion uncertainty. While various particle filters and conventional Markov-chain Monte Carlo (MCMC) methods have been proposed for visual tracking, these methods often suffer from the well-known local-trap problem or from poor convergence rate. In this paper, we propose a novel sampling-based tracking scheme for the abrupt motion problem in the Bayesian filtering framework. To effectively handle the local-trap problem, we first introduce the stochastic approximation Monte Carlo (SAMC) sampling method into the Bayesian filter tracking framework, in which the filtering distribution is adaptively estimated as the sampling proceeds, and thus, a good approximation to the target distribution is achieved. In addition, we propose a new MCMC sampler with intensive adaptation to further improve the sampling efficiency, which combines a density-grid-based predictive model with the SAMC sampling, to give a proposal adaptation scheme. The proposed method is effective and computationally efficient in addressing the abrupt motion problem. We compare our approach with several alternative tracking algorithms, and extensive experimental results are presented to demonstrate the effectiveness and the efficiency of the proposed method in dealing with various types of abrupt motions. [ABSTRACT FROM PUBLISHER]
- Published
- 2012
- Full Text
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14. Incremental Distributed Identification of Markov Random Field Models in Wireless Sensor Networks.
- Author
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Oka, Anand and Lampe, Lutz
- Subjects
- *
MARKOV random fields , *WIRELESS communications , *REMOTE sensing , *COMPUTER network management , *GAUSSIAN Markov random fields , *ENERGY consumption , *STOCHASTIC processes - Abstract
Wireless sensor networks (WSNs) comprise of highly power constrained nodes that observe a hidden natural field and reconstruct it at a distant data fusion center. Algorithmic strategies for extending the lifetime of such networks invariably require a knowledge of the statistical model of the underlying field. Since centralized model identification is communication intensive and eats into any potential power savings, we present a stochastic recursive identification algorithm which can be implemented in a fully distributed and scalable manner within the network. We demonstrate that it consumes modest resources relative to centralized estimation, and is stable, unbiased, and asymptotically efficient. [ABSTRACT FROM AUTHOR]
- Published
- 2009
- Full Text
- View/download PDF
15. Bayesian Inference in the Space of Topological Maps.
- Author
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Ranganathan, Ananth, Menegatti, Emanuele, and Dellaert, Frank
- Subjects
- *
ROBOTICS , *BAYESIAN analysis , *MAPS , *TOPOLOGY , *ALGORITHMS , *MONTE Carlo method - Abstract
While probabilistic techniques have previously been investigated extensively for performing inference over the space of metric maps, no corresponding general-purpose methods exist for topological maps. We present the concept of probabilistic topological maps (PTM5), a sample-based representation that approximates the posterior distribution over topologies, given available sensor measurements. We show that the space of topologies is equivalent to the intractably large space of set partitions on the set of available measurements. The combinatorial nature of the problem is overcome by computing an approximate, sample-based representation of the posterior. The PTM is obtained by performing Bayesian inference over the space of all possible topologies, and provides a systematic solution to the problem of perceptual aliasing in the domain of topological mapping. In this paper, we describe a general framework for modeling measurements, and the use of a Markov-chain Monte Carlo algorithm that uses specific instances of these models for odometry and appearance measurements to estimate the posterior distribution. We present experimental results that validate our technique and generate good maps when using odometry and appearance, derived from panoramic images, as sensor measurements. [ABSTRACT FROM AUTHOR]
- Published
- 2006
- Full Text
- View/download PDF
16. Hyperpolarized [1,13C]pyruvate in lysed human erythrocytes: effects of co-substrate supply on reaction time courses
- Author
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Pages, Guilhem, Tan, Yee Ling, Kuchel, Philip W., Agency for Science Technology and Research, Université Fédérale Toulouse Midi-Pyrénées, School of Molecular Bioscience, and The University of Sydney
- Subjects
dynamic nuclear polarization (DNP) ,[CHIM.ANAL]Chemical Sciences/Analytical chemistry ,NADH ,Markov-chain Monte Carlo (MCMC) ,13C-lactate ,red blood cells (RBCs) - Abstract
International audience; Hyperpolarized [1,13C]pyruvate was injected rapidly into haemolysates in which hydrolysis of nicotinamide adenine dinucleotide (phosphate) (NAD(P))/NAD(P)H had been inhibited with nicotinamide. Haemolysates provide a stable glycolytic system in which membrane permeability is not a flux-controlling step, and they enable the concentration of NADH to be adjusted experimentally while keeping the rest of the sample with the same composition as that of the cytoplasm of the cell (albeit diluted twofold at the time of injection of the [1,13C]pyruvate). We showed that the maximum amplitude of the 13C NMR signal from the [1,13C]l-lactate, produced from [1,13C]pyruvate, and the time at which it occurred was dependent on NADH concentration, as predicted by enzyme-kinetic analysis. The main feature of such curves was dictated by the immediacy of the supply of the co-substrate of lactate dehydrogenase (LDH, EC 1.1.1.27), and we posit that this also pertains in vivo in various tissues including neoplasms. By constructing an appropriate mathematical model and by using a Markov-chain Monte Carlo approach, we fitted experimental data to estimate LDH and NADH concentrations. Experiments carried out with only endogenous NADH present enabled the estimation of its effective concentration in human RBCs; the ability to make this estimate is a special feature of the rapid-dissolution dynamic nuclear polarization method. We found an endogenous NADH concentration in human RBCs two to four times higher than previously reported.
- Published
- 2014
- Full Text
- View/download PDF
17. Bayesian clustering of replicated time-course gene expression data with weak signals
- Author
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Sarah J. Bray, Audrey Qiuyan Fu, Simon Tavaré, and Steven Russell
- Subjects
FOS: Computer and information sciences ,Statistics and Probability ,Computer science ,0206 medical engineering ,02 engineering and technology ,Statistics - Applications ,01 natural sciences ,010104 statistics & probability ,symbols.namesake ,Resampling ,Prior probability ,Markov-chain Monte Carlo (MCMC) ,Applications (stat.AP) ,random effects ,0101 mathematics ,Cluster analysis ,mixture model ,business.industry ,Bayesian clustering ,Pattern recognition ,Markov chain Monte Carlo ,Mixture model ,Data set ,Dirichlet process ,multivariate analysis ,Modeling and Simulation ,microarray gene expression ,symbols ,label switching ,Chinese restaurant process ,Artificial intelligence ,Statistics, Probability and Uncertainty ,time series ,business ,020602 bioinformatics - Abstract
To identify novel dynamic patterns of gene expression, we develop a statistical method to cluster noisy measurements of gene expression collected from multiple replicates at multiple time points, with an unknown number of clusters. We propose a random-effects mixture model coupled with a Dirichlet-process prior for clustering. The mixture model formulation allows for probabilistic cluster assignments. The random-effects formulation allows for attributing the total variability in the data to the sources that are consistent with the experimental design, particularly when the noise level is high and the temporal dependence is not strong. The Dirichlet-process prior induces a prior distribution on partitions and helps to estimate the number of clusters (or mixture components) from the data. We further tackle two challenges associated with Dirichlet-process prior-based methods. One is efficient sampling. We develop a novel Metropolis-Hastings Markov Chain Monte Carlo (MCMC) procedure to sample the partitions. The other is efficient use of the MCMC samples in forming clusters. We propose a two-step procedure for posterior inference, which involves resampling and relabeling, to estimate the posterior allocation probability matrix. This matrix can be directly used in cluster assignments, while describing the uncertainty in clustering. We demonstrate the effectiveness of our model and sampling procedure through simulated data. Applying our method to a real data set collected from Drosophila adult muscle cells after five-minute Notch activation, we identify 14 clusters of different transcriptional responses among 163 differentially expressed genes, which provides novel insights into underlying transcriptional mechanisms in the Notch signaling pathway. The algorithm developed here is implemented in the R package DIRECT, available on CRAN., Published in at http://dx.doi.org/10.1214/13-AOAS650 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)
- Published
- 2013
18. Hyperpolarized [1,(13)C]pyruvate in lysed human erythrocytes: effects of co-substrate supply on reaction time courses.
- Author
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Pagès G, Tan YL, and Kuchel PW
- Subjects
- Glycolysis, Hemolysis, Humans, Hydrolysis, Kinetics, Markov Chains, Models, Chemical, Monte Carlo Method, Time Factors, Carbon-13 Magnetic Resonance Spectroscopy methods, Erythrocytes chemistry, L-Lactate Dehydrogenase blood, Lactates blood, NAD blood, Pyruvates blood
- Abstract
Hyperpolarized [1,(13)C]pyruvate was injected rapidly into haemolysates in which hydrolysis of nicotinamide adenine dinucleotide (phosphate) (NAD(P))/NAD(P)H had been inhibited with nicotinamide. Haemolysates provide a stable glycolytic system in which membrane permeability is not a flux-controlling step, and they enable the concentration of NADH to be adjusted experimentally while keeping the rest of the sample with the same composition as that of the cytoplasm of the cell (albeit diluted twofold at the time of injection of the [1,(13)C]pyruvate). We showed that the maximum amplitude of the (13)C NMR signal from the [1,(13)C]L-lactate, produced from [1,(13)C]pyruvate, and the time at which it occurred was dependent on NADH concentration, as predicted by enzyme-kinetic analysis. The main feature of such curves was dictated by the immediacy of the supply of the co-substrate of lactate dehydrogenase (LDH, EC 1.1.1.27), and we posit that this also pertains in vivo in various tissues including neoplasms. By constructing an appropriate mathematical model and by using a Markov-chain Monte Carlo approach, we fitted experimental data to estimate LDH and NADH concentrations. Experiments carried out with only endogenous NADH present enabled the estimation of its effective concentration in human RBCs; the ability to make this estimate is a special feature of the rapid-dissolution dynamic nuclear polarization method. We found an endogenous NADH concentration in human RBCs two to four times higher than previously reported., (Copyright © 2014 John Wiley & Sons, Ltd.)
- Published
- 2014
- Full Text
- View/download PDF
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