Results 61 to 70 of about 15,569,368 (309)
Organoids in pediatric cancer research
FEBS Letters, EarlyView.Organoid technology has revolutionized cancer research, yet its application in pediatric oncology remains limited. Recent advances have enabled the development of pediatric tumor organoids, offering new insights into disease biology, treatment response, and interactions with the tumor microenvironment.
Carla Ríos Arceo, Jarno Drost
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Models for the Response of a Mixture
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1968 Summary Care needs to be exercised in the choice of model for a mixture system. The polynomial model, for example, cannot satisfactorily account for components which are inert or have additive effects and its coefficients lose their interpretative value when the variables are the proportions of components in the mixture.
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FEBS Letters, EarlyView.Structural and biochemical characterisations show that the planar cell polarity (PCP) protein Inturned harbours a unique PDZ‐like domain that does not bind canonical PDZ‐binding motifs (PBMs) like that of another PCP protein Vangl2. In contrast, the apical‐basal polarity protein Scribble contains four PDZ domains that bind Vangl2, but one PDZ domain ...
Stephan Wilmes +4 more
wiley +1 more source
Computational aspects of N-mixture models [PDF]
, 2015 The N-mixture model is widely used to estimate the abundance of a population in the presence of unknown detection probability from only a set of counts subject to spatial and temporal replication (Royle, 2004, Biometrics 60,105–115).
Morgan, Byron J. T. +3 more
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A classification method for binary predictors combining similarity measures and mixture models
Dependence Modeling, 2015 In this paper, a new supervised classification method dedicated to binary predictors is proposed. Its originality is to combine a model-based classification rule with similarity measures thanks to the introduction of new family of exponential kernels ...
Sylla Seydou N. +4 more
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An Integrated Approach for Making Inference on the Number of Clusters in a Mixture Model
Entropy, 2019 This paper presents an integrated approach for the estimation of the parameters of a mixture model in the context of data clustering. The method is designed to estimate the unknown number of clusters from observed data.
Erlandson Ferreira Saraiva +3 more
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CoRRWidely used deep latent variable models (DLVMs), in particular Variational Autoencoders (VAEs), employ overly simplistic priors on the latent space. To achieve strong clustering performance, existing methods that replace the standard normal prior with a Gaussian mixture model (GMM) require defining the number of clusters to be close to the number of ...
Andrew Stirn, David A. Knowles
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Structural insights into an engineered feruloyl esterase with improved MHET degrading properties
FEBS Letters, EarlyView.A feruloyl esterase was engineered to mimic key features of MHETase, enhancing the degradation of PET oligomers. Structural and computational analysis reveal how a point mutation stabilizes the active site and reshapes the binding cleft, expading substrate scope.
Panagiota Karampa +5 more
wiley +1 more source
The role of pitch and timbre in voice gender categorization
Frontiers in Psychology, 2012 Voice gender perception can be thought of as a mixture of low-level perceptual feature extraction and higher-level cognitive processes. Although it seems apparent that voice gender perception would rely on low-level pitch analysis, many lines of research
Cyril R Pernet, Pascal eBelin
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Regularized joint mixture models
J. Mach. Learn. Res., 2019 Regularized regression models are well studied and, under appropriate conditions, offer fast and statistically interpretable results. However, large data in many applications are heterogeneous in the sense of harboring distributional differences between latent groups. Then, the assumption that the conditional distribution of response Y given features X
Konstantinos Perrakis +3 more
openaire +6 more sources