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Embryo zebrafish segmentation using an improved hybrid method

JOURNAL OF MICROSCOPY 2013年第1期250卷 68-75页

作者： Wu, Tao Lu, Jianfeng Lu, Yanting Liu, Tianming Yang, Jingyu Nanjing Univ Sci & Technol Sch Comp Sci & Engn Nanjing 210094 Jiangsu Peoples R China Univ Georgia Dept Comp Sci Athens GA 30602 USA

Zebrafish is an invaluable vertebrate model in life science research and has been widely used in biological pathway analysis, molecular screening and disease modelling, among others. As a result, microscopic imaging has become an essential step in zebrafish phenotype analysis, and image segmentation thus plays an important role in the zebrafish microscopy analysis. Due to the nonuniform distribution of intensity and weak boundary in zebrafish microscope images, the traditionally used segmentation methods may lead to unsatisfactory result. Here, a novel hybrid method that integrates region and boundary information into active contour model is proposed to segment zebrafish embryos from the background, which performs better than traditional segmentation models. Meanwhile, how to utilize the gradient information effectively in image segmentation is still an open problem. In this paper, we propose to improve the aforementioned hybrid method in two aspects. Firstly, the mean grey value of background is estimated by the expectation maximization (EM) algorithm to constrain the active curve evolution. Secondly, an edge stopping function sensitive to gradient information is designed to stop curve evolution when the active curve reaches the embryo boundary. Experimental results show that the proposed methods can provide superior segmentation results compared to existing algorithms.

关键词： Active contour model edge stopping function expectation maximization algorithm image segmentation zebrafish embryo image

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Finite mixture of varying coefficient model: Estimation and component selection

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JOURNAL OF MULTIVARIATE ANALYSIS 2019年 171卷 452-474页

作者： Ye, Mao Lu, Zhao-Hua Li, Yimei Song, Xinyuan Purdue Univ Dept Stat 610 Purdue Mall W Lafayette IN 47907 USA St Jude Childrens Res Hosp Dept Biostat MS 768262 Danny Thomas Pl Memphis TN 38105 USA Chinese Univ Hong Kong Shenzhen Res Inst Shatin Hong Kong Peoples R China Chinese Univ Hong Kong Dept Stat Shatin Hong Kong Peoples R China

Heterogeneous longitudinal data have become prevalent in medical, biological, and social studies. This paper proposes a finite mixture of varying coefficient models for handling heterogeneous populations. Each component of the mixture is modeled by a varying coefficient mixed-effect model that characterizes the longitudinal relations among variables. The identifiability of the mixture model is studied. Regression splines with equally spaced knots are used to approximate the varying coefficient functions, and a nested expectation maximization algorithm is developed to obtain the maximum likelihood estimation. We propose a penalized likelihood method based on the smoothly clipped absolute deviation (SCAD) penalty for the component selection of finite mixture of varying coefficient model. A modified BIC-based criterion based on the SCAD penalty, the BICSCAD, is proposed for selecting the penalty parameter and spline space simultaneously. The asymptotic properties of parameter estimation and component selection consistency are studied under mild conditions. Simulation studies are conducted to illustrate the component selection, parameter estimation, and inference of the proposed method. The model is then applied to a heterogeneous longitudinal data set from a study of the treatment effect on the use of heroin in the California Civil Addict Program. (C) 2019 Elsevier Inc. All rights reserved.

关键词： expectation maximization algorithm Finite mixture model Model selection Random effects SCAD Varying coefficients

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Dynamics in cryo EM reconstructions visualized with maximum-likelihood derived variance maps

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JOURNAL OF STRUCTURAL BIOLOGY 2013年第3期181卷 195-206页

作者： Wang, Qiu Matsui, Tsutomu Domitrovic, Tatiana Zheng, Yili Doerschuk, Peter C. Johnson, John E. Cornell Univ Ithaca NY 14853 USA Scripps Res Inst Dept Mol Biol Menlo Pk CA 94025 USA SLAC Natl Accelerator Lab Stanford Synchrotron Radiat Lightsource Menlo Pk CA 94025 USA Scripps Res Inst Dept Mol Biol La Jolla CA USA Purdue Univ W Lafayette IN 47907 USA

CryoEM data capture the dynamic character associated with biological macromolecular assemblies by preserving the various conformations of the individual specimens at the moment of flash freezing. Regions of high variation in the data set are apparent in the image reconstruction due to the poor density that results from the lack of superposition of these regions. These observations are qualitative and, to date, only preliminary efforts have been made to quantitate the heterogeneity in the ensemble of particles that are individually imaged. We developed and tested a quantitative method for simultaneously computing a reconstruction of the particle and a map of the space-varying heterogeneity of the particle based on an entire data set. The method uses a maximum likelihood algorithm that explicitly takes into account the continuous variability from one instance to another instance of the particle. The result describes the heterogeneity of the particle as a variance to be plotted at every voxel of the reconstructed density. The test, employing time resolved data sets of virus maturation, not only recapitulated local variations obtained with difference map analysis, but revealed a remarkable time dependent reduction in the overall particle dynamics that was unobservable with classical methods of analysis. (c) 2012 Elsevier Inc. All rights reserved.

关键词： Time-resolved Single particle reconstruction Virus maturation Protein folding Quasi equivalence Cryo electron microscopy Nudaurelia Capensis Omega Virus Maximum likelihood estimation expectation maximization algorithm Heterogeneous particles Variance map

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Detecting DNA regulatory motifs by incorporating positional trends in information content

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GENOME BIOLOGY 2004年第7期5卷 1-21页

作者： Kechris, KJ van Zwet, E Bickel, PJ Eisen, MB Univ Calif Berkeley Dept Stat Berkeley CA 94720 USA Univ Calif Berkeley Lawrence Berkeley Lab Div Life Sci Dept Genome Sci Berkeley CA 94720 USA Univ Calif Berkeley Dept Mol & Cell Biol Ctr Integrat Genom Berkeley CA 94720 USA

On the basis of the observation that conserved positions in transcription factor binding sites are often clustered together, we propose a simple extension to the model-based motif discovery methods. We assign position-specific prior distributions to the frequency parameters of the model, penalizing deviations from a specified conservation profile. Examples with both simulated and real data show that this extension helps discover motifs as the data become noisier or when there is a competing false motif.

关键词： Prior Distribution Change Point Transcription Factor Binding Site Additional Data File expectation maximization algorithm

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4D Flexible Atom-Pairs: An efficient probabilistic conformational space comparison for ligand-based virtual screening

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JOURNAL OF CHEMINFORMATICS 2011年第1期3卷 1-17页

作者： Jahn, Andreas Rosenbaum, Lars Hinselmann, Georg Zell, Andreas Univ Tubingen Ctr Bioinformat Tubingen ZBIT D-72076 Tubingen Germany

Background: The performance of 3D-based virtual screening similarity functions is affected by the applied conformations of compounds. Therefore, the results of 3D approaches are often less robust than 2D approaches. The application of 3D methods on multiple conformer data sets normally reduces this weakness, but entails a significant computational overhead. Therefore, we developed a special conformational space encoding by means of Gaussian mixture models and a similarity function that operates on these models. The application of a model-based encoding allows an efficient comparison of the conformational space of compounds. Results: Comparisons of our 4D flexible atom-pair approach with over 15 state-of-the-art 2D- and 3D-based virtual screening similarity functions on the 40 data sets of the Directory of Useful Decoys show a robust performance of our approach. Even 3D-based approaches that operate on multiple conformers yield inferior results. The 4D flexible atom-pair method achieves an averaged AUC value of 0.78 on the filtered Directory of Useful Decoys data sets. The best 2D- and 3D-based approaches of this study yield an AUC value of 0.74 and 0.72, respectively. As a result, the 4D flexible atom-pair approach achieves an average rank of 1.25 with respect to 15 other state-of-the-art similarity functions and four different evaluation metrics. Conclusions: Our 4D method yields a robust performance on 40 pharmaceutically relevant targets. The conformational space encoding enables an efficient comparison of the conformational space. Therefore, the weakness of the 3D-based approaches on single conformations is circumvented. With over 100,000 similarity calculations on a single desktop CPU, the utilization of the 4D flexible atom-pair in real-world applications is feasible.

关键词： Virtual Screening expectation maximization algorithm Conformational Space Optimal Assignment Conformational Ensemble

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Multiple Content Selections Using Digital Signage Considering Changes in Purchasing Intentions

IEEJ Transactions on Electronics, Information and Systems

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IEEJ Transactions on Electronics, Information and Systems 2024年第12期144卷 1230-1237页

作者： Maeda, Yasunari School of Regional Innovation and Social Design Engineering Kitami Institute of Technology 165 Koen-cho Hokkaido Kitami090-8507 Japan

There is a lot of previous research on sales promotion strategy using digital signage. maximization of expected sales is one of important topics on sales promotion strategy using digital signage. In the previous research, maximization of expected sales considering changes in purchasing intentions for one content selection has been studied. The previous method can not be applied to multiple content selections. In this research, maximization of expected sales considering changes in purchasing intentions for multiple content selections is studied. In the proposed method, the expected sales amount is maximized with respect to a Bayes criterion based on statistical decision theory. The effectiveness of the proposed method is shown by some computational examples. The expected sales amount of the proposed method is greater than that of a comparison target. In this research, the expected sales amount is maximized under the condition that all probabilities are known. But the probabilities are unknown in real cases. An expansion of this research with unknown probabilities is one of further works. © 2024 The Institute of Electrical Engineers of Japan.

关键词： expectation maximization algorithm

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Inference for a series system with dependent masked data under progressive interval censoring

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JOURNAL OF APPLIED STATISTICS 2017年第1期44卷 3-15页

作者： Cai, Jing Shi, Yimin Liu, Bin Northwestern Polytech Univ Dept Appl Math Xian Peoples R China Guizhou Minzu Univ Coll Sci Guiyang Peoples R China

This paper considers the statistical analysis of masked data in a series system with Burr-XII distributed components. Based on progressively Type-I interval censored sample, the maximum likelihood estimators for the parameters are obtained by using the expectation maximization algorithm, and the associated approximate confidence intervals are also derived. In addition, Gibbs sampling procedure using important sampling is applied for obtaining the Bayesian estimates of the parameters, and Monte Carlo method is employed to construct the credible intervals. Finally, a simulation study is proposed to illustrate the efficiency of the methods under different removal schemes and masking probabilities.

关键词： Dependent masked data masking probability progressively Type-I interval censoring expectation maximization algorithm Gibbs sampling Monte Carlo method

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Collaborative filtering recommendation algorithm for e-commerce products based on Bayesian network

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International Journal of Reasoning-based Intelligent Systems 2024年第4期16卷 331-336页

作者： Wan, Hongli School of Computer Dalian Neusoft University of Information Dalian116023 China

In order to effectively improve the recommendation accuracy of collaborative screening of e-commerce products, ensure the results of collaborative screening of e-commerce products, and reduce the time consumption of collaborative screening of e-commerce products, this project plans to study the recommendation algorithm for collaborative screening of e-commerce products based on Bayesian networks. Use an identical method to determine the user selection of e-commerce platform. On this basis, a new method was adopted to conduct an overall similarity analysis of products in e-commerce platforms. Then, using Bayesian networks and expected maximum methods, establish a model of user interest in e-commerce products on e-commerce platforms, thereby completing joint screening of e-commerce products. Through testing the joint screening of different types of e-commerce products, it was found that this method had a recommendation rate of 91.6% and an accuracy rate of 95.9% in the joint screening of e-commerce products. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： expectation maximization algorithm

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Parameter Estimation for a Bidimensional Partially Observed Ornstein-Uhlenbeck Process with Biological Application

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SCANDINAVIAN JOURNAL OF STATISTICS 2010年第2期37卷 200-220页

作者： Favetto, Benjamin Samson, Adeline Univ Paris 05 Lab MAP5 UMR CNRS 8145 F-75006 Paris France

We consider a bidimensional Ornstein-Uhlenbeck process to describe the tissue microvascularization in anti-cancer therapy. Data are discrete, partial and noisy observations of this stochastic differential equation (SDE). Our aim is to estimate the SDE parameters. We use the main advantage of a one-dimensional observation to obtain an easy way to compute the exact likelihood using the Kalman filter recursion, which allows to implement an easy numerical maximization of the likelihood. Furthermore, we establish the link between the observations and an ARMA process and we deduce the asymptotic properties of the maximum likelihood estimator. We show that this ARMA property can be generalized to a higher dimensional underlying Ornstein-Uhlenbeck diffusion. We compare this estimator with the one obtained by the well-known expectation maximization algorithm on simulated data. Our estimation methods can be directly applied to other biological contexts such as drug pharmacokinetics or hormone secretions.

关键词： ARMA process expectation maximization algorithm hidden Markov model Kalman filter maximum likelihood estimation Ornstein-Uhlenbeck process partial observations

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SENSITIVITY AND SPECIFICITY OF DIAGNOSTIC-TESTS IN ACUTE MAXILLARY SINUSITIS DETERMINED BY MAXIMUM-LIKELIHOOD IN THE ABSENCE OF AN EXTERNAL STANDARD

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JOURNAL OF CLINICAL EPIDEMIOLOGY 1994年第12期47卷 1343-1352页

作者： DEBOCK, GH HOUWINGDUISTERMAAT, JJ SPRINGER, MP KIEVIT, J VANHOUWELINGEN, JC LEIDEN UNIV MED DECIS MAKING UNITLEIDENNETHERLANDS LEIDEN UNIV DEPT MED STAT2300 RA LEIDENNETHERLANDS

This study shows how to obtain maximum likelihood estimates of test sensitivities and specificities in case of lack of an external standard, using the expectation Maximisation (EM) algorithm. This method is used to compare four diagnostic tests in patients suspected of acute maxillary sinusitis. Data were analyzed from published studies. Antral aspiration is the test with the highest diagnostic value. The diagnostic value of a positive clinical examination (according to explicit criteria) and of a positive radiograph or ultrasound are comparable. A negative radiograph is of more diagnostic value than a negative clinical examination or ultrasound. The width of the confidence intervals may be too small, due to model deviations which may give incorrect standard errors. However, the estimated likelihood ratios adequately reflect the relative value of the diagnostic tests considered, even when the assumption of independence is dropped.

关键词： SENSITIVITY AND SPECIFICITY LIKELIHOOD RATIO expectation maximization algorithm ACUTE MAXILLARY SINUSITIS REFERENCE STANDARDS

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