scholarly journals Spinal Muscle Atrophy Disease Modelling as Bayesian Network

2021 ◽  
Vol 2128 (1) ◽  
pp. 012015
Author(s):  
Mohammed Ezzat Helal ◽  
Manal Ezzat Helal ◽  
Professor Sherif Fadel Fahmy
Keyword(s):  
Bayesian Inference ◽  
Muscle Atrophy ◽  
Graphical Models ◽  
Genome Wide Association Study ◽  
Monte Carlo Sampling ◽  
Disease Modelling ◽  
Gene Expressions ◽  
Study Results ◽  
Two Stages ◽  
Future Work

Abstract We investigate the molecular gene expressions studies and public databases for disease modelling using Probabilistic Graphical Models and Bayesian Inference. A case study on Spinal Muscle Atrophy Genome-Wide Association Study results is modelled and analyzed. The genes up and down-regulated in two stages of the disease development are linked to prior knowledge published in the public domain and co-expressions network is created and analyzed. The Molecular Pathways triggered by these genes are identified. The Bayesian inference posteriors distributions are estimated using a variational analytical algorithm and a Markov chain Monte Carlo sampling algorithm. Assumptions, limitations and possible future work are concluded.

scholarly journals Fast Bayesian inference in large Gaussian graphical models

Biometrics ◽  
2019 ◽  
Vol 75 (4) ◽  
pp. 1288-1298
Author(s):  
Gwenaël G. R. Leday ◽  
Sylvia Richardson
Keyword(s):  
Bayesian Inference ◽  
Graphical Models ◽  
Gaussian Graphical Models

scholarly journals Dual-stage sugar substitution in Tommy Atkins mango

2019 ◽  
Vol 23 (1) ◽  
pp. 60-64
Author(s):  
Rafael A. B. de Medeiros ◽  
Zilmar M. P. Barros ◽  
Carlos B. O. de Carvalho ◽  
Antonio C. D. Coêlho ◽  
Maria I. S. Maciel ◽  
...  
Keyword(s):  
Quality Parameters ◽  
Ultrasonic Waves ◽  
Total Phenolic ◽  
Second Stage ◽  
Study Results ◽  
Fruit Samples ◽  
Dual Stage ◽  
Sugar Replacement ◽  
Two Stages ◽  
High Calorie

ABSTRACT The dual-stage sugar substitution technique (D3S) was used to induce sugar replacement in mango. It involved two stages, in which high-calorie sugars were partially removed from the fruit samples in the first stage and, in the second one, low-calorie sugar was incorporated into the mango. Ultrasonic waves can be applied in one or both stages and their use was also evaluated in this study. Results showed that submitting samples to ultrasonic waves (25 kHz) in both stages and their immersion in Stevia-based solution (250 or 500 g kg-1) in the second stage for 10, 20 and 30 min of processing gave higher water loss during the process, while greater solids gain could be achieved by applying ultrasound only in the first stage. Samples were also evaluated in terms of some quality parameters. The use of this technique resulted in samples with higher values of total phenolic content and changes in color parameters (L*, a* and b*). When samples were subjected to ultrasonic waves in both stages, a higher carotenoid retention was observed.

scholarly journals Effect of Resistance Training Along with Curcumin Supplementation on Expression of Some Regulator Genes Associated with Cardiac Muscle Structure in Obese Rats

Thrita ◽  
2020 ◽  
Vol 9 (2) ◽  
Author(s):  
Atefeh Rauofi ◽  
Sirous Farsi ◽  
Seyed Ali Hosseini
Keyword(s):  
Physical Activity ◽  
Resistance Training ◽  
Cardiac Muscle ◽  
Muscle Atrophy ◽  
Synergistic Effects ◽  
Training Group ◽  
Control Group ◽  
Gene Expressions ◽  
Obese Rats ◽  
Reduced Physical Activity

Background: Reduced physical activity can cause obesity and metabolic syndrome, leading to fibrosis in cardiac muscles and premature cardiac aging. Physical activity, along with herbal supplements, can have a synergistic effect on preventing cardiac muscle proteolysis. Objectives: In this study, the effects of curcumin and resistance training were assessed on cardiac muscle atrophy in obese rats. Methods: Twenty-four male Sprague rats were categorized into four groups, including the placebo, resistance training, curcumin, and resistance training + curcumin. Resistance training was performed three times a week with three sets in each session, repeated five times for eight weeks. During this time, 150 mg/kg curcumin was administered through gavage. Twenty-four hours after finishing resistance training, surgery was performed on the cardiac muscle, and gene expressions of PGC1-α, FOXO1, Murf-1, Atrogin, Collagen1, and Collagen 3 were assessed with real-time PCR. Results: The expression of PGC1-α and FOXO1 genes in both resistance training and resistance training+curcumin groups significantly increased and decreased, respectively, compared to the control group (P = 0.001). The MuRF1 expression in the curcumin+resistance training group decreased significantly (P = 0.013) compared to the placebo and curcumin groups. The expression of collagen type 1 and type 2 in all the three treatment groups had significant decreases compared to the placebo group (P < 0.05). Conclusions: Considering the results of this study, resistance training and curcumin supplement each alone can prevent cardiac muscle atrophy. However, the simultaneous use of curcumin supplement and resistance training can lead to synergistic effects.

scholarly journals TFutils: Data structures for transcription factor bioinformatics

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 152
Author(s):  
Benjamin J. Stubbs ◽  
Shweta Gopaulakrishnan ◽  
Kimberly Glass ◽  
Nathalie Pochet ◽  
Celine Everaert ◽  
...  
Keyword(s):  
Transcription Factor ◽  
Transcription Factors ◽  
Data Structures ◽  
Binding Sites ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Bioconductor Package ◽  
Genome Wide ◽  
Study Results ◽  
Integrative Analyses

DNA transcription is intrinsically complex. Bioinformatic work with transcription factors (TFs) is complicated by a multiplicity of data resources and annotations. The Bioconductor package TFutils includes data structures and functions to enhance the precision and utility of integrative analyses that have components involving TFs. TFutils provides catalogs of human TFs from three reference sources (CISBP, HOCOMOCO, and GO), a catalog of TF targets derived from MSigDb, and multiple approaches to enumerating TF binding sites. Aspects of integration of TF binding patterns and genome-wide association study results are explored in examples.

scholarly journals Efficient Bayesian inference of fully stochastic epidemiological models with applications to COVID-19

2021 ◽  
Vol 8 (8) ◽  
pp. 211065
Author(s):  
Yuting I. Li ◽  
Günther Turk ◽  
Paul B. Rohrbach ◽  
Patrick Pietzonka ◽  
Julian Kappler ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Information Matrix ◽  
Monte Carlo Sampling ◽  
Epidemiological Models ◽  
Large Populations ◽  
Model Evidence ◽  
Age Structured ◽  
The Uk ◽  
Functional Central Limit

Epidemiological forecasts are beset by uncertainties about the underlying epidemiological processes, and the surveillance process through which data are acquired. We present a Bayesian inference methodology that quantifies these uncertainties, for epidemics that are modelled by (possibly) non-stationary, continuous-time, Markov population processes. The efficiency of the method derives from a functional central limit theorem approximation of the likelihood, valid for large populations. We demonstrate the methodology by analysing the early stages of the COVID-19 pandemic in the UK, based on age-structured data for the number of deaths. This includes maximum a posteriori estimates, Markov chain Monte Carlo sampling of the posterior, computation of the model evidence, and the determination of parameter sensitivities via the Fisher information matrix. Our methodology is implemented in PyRoss, an open-source platform for analysis of epidemiological compartment models.

scholarly journals Bayesian Uncertainty Estimation for Gaussian Graphical Models and Centrality Indices

2021 ◽  
Author(s):  
Joran Jongerling ◽  
Sacha Epskamp ◽  
Donald Ray Williams
Keyword(s):  
Bayesian Estimation ◽  
Graphical Models ◽  
Estimation Methods ◽  
Centrality Measures ◽  
Gaussian Graphical Models ◽  
Graphical Lasso ◽  
Study Results ◽  
Partial Correlations ◽  
Good Coverage ◽  
Better Than

Gaussian Graphical Models (GGMs) are often estimated using regularized estimation and the graphical LASSO (GLASSO). However, the GLASSO has difficulty estimating(uncertainty in) centrality indices of nodes. Regularized Bayesian estimation might provide a solution, as it is better suited to deal with bias in the sampling distribution ofcentrality indices. This study therefore compares estimation of GGMs with a Bayesian GLASSO- and a Horseshoe prior to estimation using the frequentist GLASSO in an extensive simulation study. Results showed that out of the two Bayesian estimation methods, the Bayesian GLASSO performed best. In addition, the Bayesian GLASSOperformed better than the frequentist GLASSO with respect to bias in edge weights, centrality measures, correlation between estimated and true partial correlations, andspecificity. With respect to sensitivity the frequentist GLASSO performs better.However, sensitivity of the Bayesian GLASSO is close to that of the frequentist GLASSO (except for the smallest N used in the simulations) and tends to be favored over the frequentist GLASSO in terms of F1. With respect to uncertainty in the centrality measures, the Bayesian GLASSO shows good coverage for strength andcloseness centrality. Uncertainty in betweenness centrality is estimated less well, and typically overestimated by the Bayesian GLASSO.

scholarly journals Using the MR-Base platform to investigate risk factors and drug targets for thousands of phenotypes

2019 ◽  
Vol 4 ◽  
pp. 113 ◽  
Author(s):  
Venexia M Walker ◽  
Neil M Davies ◽  
Gibran Hemani ◽  
Jie Zheng ◽  
Philip C Haycock ◽  
...  
Keyword(s):  
Risk Factors ◽  
Web Application ◽  
Drug Targets ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
R Package ◽  
Sensitivity Analyses ◽  
Link Type ◽  
Study Results

Mendelian randomization (MR) estimates the causal effect of exposures on outcomes by exploiting genetic variation to address confounding and reverse causation. This method has a broad range of applications, including investigating risk factors and appraising potential targets for intervention. MR-Base has become established as a freely accessible, online platform, which combines a database of complete genome-wide association study results with an interface for performing Mendelian randomization and sensitivity analyses. This allows the user to explore millions of potentially causal associations. MR-Base is available as a web application or as an R package. The technical aspects of the tool have previously been documented in the literature. The present article is complementary to this as it focuses on the applied aspects. Specifically, we describe how MR-Base can be used in several ways, including to perform novel causal analyses, replicate results and enable transparency, amongst others. We also present three use cases, which demonstrate important applications of Mendelian randomization and highlight the benefits of using MR-Base for these types of analyses.

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