Filters








178 Hits in 6.3 sec

Temporal Bayesian classifiers for modelling muscular dystrophy expression data

Allan Tucker, Peter A.C. 't Hoen, Veronica Vinciotti, Xiaohui Liu
2006 Intelligent Data Analysis  
In this paper we focus on data that has been generated to explore different types of muscular dystrophy.  ...  We show that this classifier improves the classification of microarray data and at the same time ensures that the models can easily be analysed by biologists by incorporating time transparently.  ...  The MDX mouse is a mouse model for Duchenne muscular dystrophy, beta-sarcoglyan-deficient (BSG) and gamma-sarcoglycan-deficient (GSG) mice are mouse models for Limb-Girdle Muscular Dystrophies 2E and 2C  ... 
doi:10.3233/ida-2006-10504 fatcat:64f2f4fl3zfnlnfs5dgyq5hola

Introduction

Joost N. Kok, José María Peña, Arno Siebes
2006 Intelligent Data Analysis  
In the article Temporal Bayesian Classifiers for Modeling Muscular Dystrophy Expression Data by Tucker et al. apply et al. applies Bayesian methods to time series of micro-array data.  ...  Experimental evaluation has been done on data concerning Muscular Dystrophy.  ... 
doi:10.3233/ida-2006-10501 fatcat:bym6xgqdcrambor4ajoagja64q

Effective Classification and Gene Expression Profiling for the Facioscapulohumeral Muscular Dystrophy

Félix F. González-Navarro, Lluís A. Belanche-Muñoz, Karen A. Silva-Colón, Ruben Artero
2013 PLoS ONE  
The Facioscapulohumeral Muscular Dystrophy (FSHD) is an autosomal dominant neuromuscular disorder whose incidence is estimated in about one in 400,000 to one in 20,000.  ...  Unfortunately, the complete mechanisms responsible for the molecular pathogenesis and progressive muscle weakness still remain unknown.  ...  , fascioscapulohumeral muscular dystrophy, Emery Dreifuss muscular dystrophy, Becker muscular dystrophy, Duchenne muscular dystrophy, calpain 3, dysferlin, and the FKRP using U133A and U133B array design  ... 
doi:10.1371/journal.pone.0082071 pmid:24349187 pmcid:PMC3862578 fatcat:5c5hno6ktnfolnomfu5ydfkp3q

Continuous time Bayesian network classifiers

F. Stella, Y. Amer
2012 Journal of Biomedical Informatics  
Learning and inference for the class of continuous time Bayesian network classifiers are addressed, in the case where complete data are available.  ...  A learning algorithm for the continuous time naive Bayes classifier and an exact inference algorithm for the class of continuous time Bayesian network classifiers are described.  ...  They have been used to diagnose muscular dystrophy from gene expression data [12] and for spatio-temporal understanding of the visual field deterioration [13] .  ... 
doi:10.1016/j.jbi.2012.07.002 pmid:22846170 fatcat:4rerz43a3bhxbencjw4ewq3yjy

Wormnet: a crystal ball for Caenorhabditis elegans

Stephen E Von Stetina, Susan E Mango
2008 Genome Biology  
DAPC components are primarily expressed in muscle cells, and mutation of several DAPC genes are linked to muscular dystrophies [19] .  ...  In addition, the current version of Wormnet does not rely on explicit spatial or temporal expression data.  ... 
doi:10.1186/gb-2008-9-6-226 pmid:18533047 pmcid:PMC2481412 fatcat:3hnhle4jkfgerknipzz6y2275m

A Review of Mathematical Models for Muscular Dystrophy: A Systems Biology Approach [article]

Amanda N. Cameron and Matthew T. Houston and Juan B. Gutierrez
2016 arXiv   pre-print
Muscular dystrophy (MD) describes generalized progressive muscular weakness due to the wasting of muscle fibers.  ...  This article reviews mathematical models of MD that characterize molecular and cellular components implicated in MD progression. A biological background for these processes is also presented.  ...  Instead continuous models like dynamic Bayesian networks [69] and temporal Bayesian classifiers [98] can be constructed.  ... 
arXiv:1610.03521v2 fatcat:fz23b66q2fcozo5dglmdyla2nu

Abstracts from "Imaging in Neuromuscular Disease 2019: Second International Conference on Imaging in Neuromuscular Disease, 17th – 19th November 2019 | Berlin, Germany"

2019 Journal of Neuromuscular Diseases  
Based on natural history data of muscle MRI-T2 and fat fraction (FF) in DMD from the ImagingDMD Consortium, MoveDMD was designed as a proofof-concept trial with MRI in 4-7 year old boys with DMD not on  ...  gastrocnemius, tibialis anterior, tibialis posterior and peroneals) comprising muscles at different stages of the disease process, could be highly predictive of function and provide greater sensitivity than data  ...  Background: Facioscapulohumeral muscular dystrophy (FSHD) is an inherent muscular dystrophy. Its key genetic defect is a loss of DUX4 suppression leading expression of the DUX4 protein.  ... 
doi:10.3233/jnd-199002 pmid:31744016 pmcid:PMC6918898 fatcat:c2q4eqos5racxibieebsslw2oe

Cluster and propensity based approximation of a network

John Michael Ranola, Peter Langfelder, Kenneth Lange, Steve Horvath
2013 BMC Systems Biology  
To illustrate the practical utility of the CPBA of a network, we apply it to gene expression data and to a bi-partite network model for diseases and disease genes from the Online Mendelian Inheritance  ...  The models in this article generalize current models for both correlation networks and multigraph networks. Correlation networks are widely applied in genomics research.  ...  dystrophy-dystroglycanopathy (limb-girdle) Muscular dystrophy-dystroglycanopathy (congenital) 2 2 7.05 3 Ullrich congenital muscular dystrophy Bethlem myopathy 14 14 6.48 4 Iminoglycinuria  ... 
doi:10.1186/1752-0509-7-21 pmid:23497424 pmcid:PMC3663730 fatcat:o27e7rszorgltpnjfdyncdkivq

Estimation of the covariance matrix of random effects in longitudinal studies

Yan Sun, Wenyang Zhang, Howell Tong
2007 Annals of Statistics  
Motivated by data typified by a set from Bangladesh pertinent to the use of contraceptives, we propose a random effect varying-coefficient model, and an estimation procedure for the within cluster correlation  ...  Simulations suggest that the proposed estimation is practicable for finite samples and resistent against mild forms of model misspecification.  ...  Empirical Bayes accomodation of batch-effects in microarray data using identical replicate reference samples: Application to RNA expression profiling of blood from Duchenne muscular dystrophy patients.  ... 
doi:10.1214/009053607000000523 fatcat:x6u3qclakrgr3bkryyxq4ooaaa

16th International Congress on Neuromuscular Diseases, 21 - 22 & 28 - 29 May 2021 Virtual, Worldwide

2021 Journal of Neuromuscular Diseases  
Only 7% of the patients were positive for ganglioside antibodies and the patients positive for the campylobacter IgG antibody accounted for about 4.7% of the subjects and those positive for IgA antibody  ...  An improvement was shown for Abstracts S5 Serum samples were screened for immunoglobulin G(IgG), IgA and IgM antibodies against C.jejuni using the ELISA (ELISA kits, Serion, Germany) and anti-gangliosid  ...  We previously showed that overexpression of the prodomain reverses muscular atrophy in a rodent model of caveolin3-defi cient muscular dystrophy (Ohsawa, J Clin Invest 116, 2006).  ... 
doi:10.3233/jnd-219006 pmid:34334417 fatcat:5ixajewia5d3hhpkwj4yqyb32a

Translational research on Myology and Mobility Medicine: 2021 semi-virtual PDM3 from Thermae of Euganean Hills, May 26 - 29, 2021

Ugo Carraro
2021 European Journal of Translational Myology  
CD82 expression appeared decreased in human Duchenne muscular dystrophy (DMD) muscle, suggesting a functional link to muscular dystrophy, yet whether this decrease is a consequence of dystrophic pathology  ...  Keywords: Tetraspanin; CD82; muscular dystrophy.  ...  as a possible therapeutic approach to counteract the progression of the dystrophic phenotypeKeywords: inflammation; oxidative stress; muscular dystrophies; HMGB1.  ... 
doi:10.4081/ejtm.2021.9743 pmid:33733717 pmcid:PMC8056169 fatcat:o3mhlmnpknccvog4vt3cnb27vm

Signal Processing and Classification Approaches for Brain-Computer Interface [chapter]

Tarik Al-ani, Dalila Tr
2010 Intelligent and Biosensors  
Hoffman and the EPFL-Brain-Computer team for the data and the software given in (Hoffman et al., 2008) that they were used in this work. The authors would like also to thank Dr. A.  ...  Bashashati for his authorization to use or modify some figures given in the paper to illustrate some sections given in this chapter. Anderson, C.W. & Sijercic, Z. (1996).  ...  Nonlinear Bayesian Classifiers (NBC) This section introduces one Bayesian classifier used for BCI: hidden Markov models (HMMs). This Classifier produces nonlinear decision boundaries.  ... 
doi:10.5772/7032 fatcat:jusb6fypyncytbn4d6bdvdk2xe

Expression profiling and identification of novel genes involved in myogenic differentiation

KINGA K. TOMCZAK, VOICHITA D. MARINESCU, MARCO F. RAMONI, DESPINA SANOUDOU, FEDERICA MONTANARO, MEI HAN, LOUIS M. KUNKEL, ISAAC S. KOHANE, ALAN H. BEGGS
2004 The FASEB Journal  
Cluster analysis specific for time-ordered microarray experiments classified 2895 genes and ESTs with variable expression levels between proliferating and differentiating cells into 22 clusters with distinct  ...  Skeletal muscle differentiation is a complex, highly coordinated process that relies on precise temporal gene expression patterns.  ...  This work was supported by NIH grants R01 AR44345 and P01 NS40828, the Muscular Dystrophy Association of the USA, the Joshua Frase Foundation and the Lee and Penny Anderson Family Foundation.  ... 
doi:10.1096/fj.03-0568fje pmid:14688207 fatcat:5cawscbcrfdcpmg3tcztqfqf3q

Distinctive morphological and gene/protein expression signatures during myogenesis in novel cell lines from extraocular and hindlimb muscle

John D. Porter, Sheri Israel, Bendi Gong, Anita P. Merriam, Jason Feuerman, Sangeeta Khanna, Henry J. Kaminski
2006 Physiological Genomics  
The lack of appropriate in vitro models, to dissociate the cell-autonomous and non-cell-autonomous mechanisms behind allotype diversity, has been a barrier to such studies.  ...  Taken together, these data show that myoblast lineage plays a significant role in the divergence of the distinctive muscle groups or allotypes.  ...  assistance with data analysis; and Maziar Assadi for helpful discussions.  ... 
doi:10.1152/physiolgenomics.00234.2004 pmid:16291736 fatcat:2avgpdjf2rb35mmq72agsqguje

Expression profiles of switch-like genes accurately classify tissue and infectious disease phenotypes in model-based classification

Michael Gormley, Aydin Tozeren
2008 BMC Bioinformatics  
Use of a model-based clustering algorithm accurately classified more than 400 microarray samples into 19 different tissue types on the basis of bimodal gene expression.  ...  Bimodal expression patterns were also highly effective in differentiating between infectious diseases in model-based clustering of microarray data.  ...  Expectationmaximization [17] [18] [19] or Bayesian methods [20] [21] [22] are used for optimization.  ... 
doi:10.1186/1471-2105-9-486 pmid:19014681 pmcid:PMC2620272 fatcat:yuwhfkvdyfdunahib7tuvet4gy
« Previous Showing results 1 — 15 out of 178 results