Conditional Gaussian graphical model for estimating personalized disease symptom networks
Sign Up to like & getrecommendations! Published in 2021 at "Statistics in Medicine"
DOI: 10.1002/sim.9274
Abstract: The co‐occurrence of symptoms may result from the direct interactions between these symptoms and the symptoms can be treated as a system. In addition, subject‐specific risk factors (eg, genetic variants, age) can also exert external… read more here.
Keywords: conditional gaussian; gaussian graphical; symptom networks; graphical model ... See more keywords
Graphical Model Selection for Gaussian Conditional Random Fields in the Presence of Latent Variables
Sign Up to like & getrecommendations! Published in 2019 at "Journal of the American Statistical Association"
DOI: 10.1080/01621459.2018.1434531
Abstract: ABSTRACT We consider the problem of learning a conditional Gaussian graphical model in the presence of latent variables. Building on recent advances in this field, we suggest a method that decomposes the parameters of a… read more here.
Keywords: presence latent; model; graphical model; model selection ... See more keywords
Covariate-adjusted Gaussian graphical model estimation with false discovery rate control
Sign Up to like & getrecommendations! Published in 2020 at "Communications in Statistics - Theory and Methods"
DOI: 10.1080/03610926.2020.1752385
Abstract: Abstract Recent genetic/genomic studies have shown that genetic markers can have potential effects on the dependence structure of genes. Motivated by such findings, we are interested in the estimation of covariate-adjusted Gaussian graphical model (CGGM).… read more here.
Keywords: adjusted gaussian; gaussian graphical; false discovery; graphical model ... See more keywords
Classification of LiDAR Point Clouds Using Supervoxel-Based Detrended Feature and Perception-Weighted Graphical Model
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing"
DOI: 10.1109/jstars.2019.2951293
Abstract: Interpretation of 3-D scene through LiDAR point clouds has been a hot research topic for decades. To utilize measured points in the scene, assigning unique tags to the points of the scene with labels linking… read more here.
Keywords: graphical model; perception weighted; point clouds; supervoxel based ... See more keywords
Exploring complaints by female and male patients at Swedish hospitals using a probabilistic graphical model
Sign Up to like & getrecommendations! Published in 2018 at "Scandinavian Journal of Caring Sciences"
DOI: 10.1111/scs.12560
Abstract: BACKGROUND Patients' complaints have been highlighted as important for constructively improving healthcare services. In so doing, it may be important to identify disparities in experiences based on patients' demographics, such as sex. AIM To explore… read more here.
Keywords: improvement suggestions; using probabilistic; graphical model; male patients ... See more keywords
Incomplete graphical model inference via latent tree aggregation
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DOI: 10.1177/1471082x18786289
Abstract: Graphical network inference is used in many fields such as genomics or ecology to infer the conditional independence structure between variables, from measurements of gene expression or species abundances for instance. In many practical cases,… read more here.
Keywords: aggregation; network; model inference; model ... See more keywords
Incorporating networks in a probabilistic graphical model to find drivers for complex human diseases
Sign Up to like & getrecommendations! Published in 2017 at "PLoS Computational Biology"
DOI: 10.1371/journal.pcbi.1005580
Abstract: Discovering genetic mechanisms driving complex diseases is a hard problem. Existing methods often lack power to identify the set of responsible genes. Protein-protein interaction networks have been shown to boost power when detecting gene-disease associations.… read more here.
Keywords: incorporating networks; graphical model; conflux; gene ... See more keywords
SourceSet: A graphical model approach to identify primary genes in perturbed biological pathways
Sign Up to like & getrecommendations! Published in 2019 at "PLoS Computational Biology"
DOI: 10.1371/journal.pcbi.1007357
Abstract: Topological gene-set analysis has emerged as a powerful means for omic data interpretation. Although numerous methods for identifying dysregulated genes have been proposed, few of them aim to distinguish genes that are the real source… read more here.
Keywords: sourceset graphical; model approach; graphical model; approach identify ... See more keywords