TITLE

Semiparametric approach to characterize unique gene expression trajectories across time

PUB. DATE
January 2006
SOURCE
BMC Genomics;2006, Vol. 7, p233
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
No abstract available.
ACCESSION #
43688193

 

Related Articles

  • Conditional clustering of temporal expression profiles. Ling Wang; Montano, Monty; Rarick, Matt; Sebastiani, Paola // BMC Bioinformatics;2008, Vol. 9, Special section p1 

    Background: Many microarray experiments produce temporal profiles in different biological conditions but common cluster techniques are not able to analyze the data conditional on the biological conditions. Results: This article presents a novel technique to cluster data from time course...

  • Meta-analysis of Inter-species Liver Co-expression Networks Elucidates Traits Associated with Common Human Diseases. Kai Wang; Narayanan, Manikandan; Hua Zhong; Tompa, Martin; Schadt, Eric E.; Jun Zhu // PLoS Computational Biology;Dec2009, Vol. 5 Issue 12, p1 

    Co-expression networks are routinely used to study human diseases like obesity and diabetes. Systematic comparison of these networks between species has the potential to elucidate common mechanisms that are conserved between human and rodent species, as well as those that are species-specific...

  • Shape Invariant Modeling of Pricing Kernels and Risk Aversion. Grith, Maria; Härdle, Wolfgang; Park, Juhyun // Journal of Financial Econometrics;Spring2013, Vol. 11 Issue 2, p370 

    Several empirical studies reported that pricing kernels exhibit a common pattern across different markets. The main interest in pricing kernels lies in validating the presence of the peaks and their variability in location among curves. Motivated by this observation we investigate the problem of...

  • A method to identify differential expression profiles of time-course gene data with Fourier transformation. Jaehee Kim; Ogden, Robert Todd; Haseong Kim // BMC Bioinformatics;2013, Vol. 14 Issue 1, p2 

    Background Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is...

  • Alternated estimation in semi-parametric space-time branching-type point processes with application to seismic catalogs. Adelfio, Giada; Chiodi, Marcello // Stochastic Environmental Research & Risk Assessment;Feb2015, Vol. 29 Issue 2, p443 

    An estimation approach for the semi-parametric intensity function of a class of space-time point processes is introduced. In particular we want to account for the estimation of parametric and nonparametric components simultaneously, applying a forward predictive likelihood to semi-parametric...

  • Marginal semiparametric multivariate accelerated failure time model with generalized estimating equations. Chiou, Sy; Kang, Sangwook; Kim, Junghi; Yan, Jun // Lifetime Data Analysis;Oct2014, Vol. 20 Issue 4, p599 

    The semiparametric accelerated failure time (AFT) model is not as widely used as the Cox relative risk model due to computational difficulties. Recent developments in least squares estimation and induced smoothing estimating equations for censored data provide promising tools to make the AFT...

  • Bayesian latent structure models with space-time dependent covariates. Cai, Bo; Lawson, Andrew B; Hossain, Md Monir; Choi, Jungsoon // Statistical Modelling: An International Journal;Jun2012, Vol. 12 Issue 3, p145 

    Spatial-temporal data requires flexible regression models which can model the dependence of responses on space- and time-dependent covariates. In this paper, we describe a semiparametric space-time model from a Bayesian perspective. Nonlinear time dependence of covariates and the interactions...

  • SEMIPARAMETRIC THURSTONIAN MODELS FOR RECURRENT CHOICES: A BAYESIAN ANALYSIS. Ansari, Asim; Iyengar, Raghuram // Psychometrika;Dec2006, Vol. 71 Issue 4, p631 

    We develop semiparametric Bayesian Thurstonian models for analyzing repeated choice decisions involving multinomial, multivariate binary or multivariate ordinal data. Our modeling framework has multiple components that together yield considerable flexibility in modeling preference utilities,...

  • Tamoxifen-elicited uterotrophy: cross-species and cross-ligand analysis of the gene expression program. Kwekel, Joshua C.; Forgacs, Agnes L.; Burgoon, Lyle D.; Williams, Kurt J.; Zacharewski, Timothy R. // BMC Medical Genomics;2009, Vol. 2, p1 

    Background: Tamoxifen (TAM) is a well characterized breast cancer drug and selective estrogen receptor modulator (SERM) which also has been associated with a small increase in risk for uterine cancers. TAM's partial agonist activation of estrogen receptor has been characterized for specific gene...

  • A Semiparametric Model for Hyperspectral Anomaly Detection. Rosario, Dalton // Journal of Electrical & Computer Engineering;2012, p1 

    Using hyperspectral (HS) technology, this paper introduces an autonomous scene anomaly detection approach based on the asymptotic behavior of a semiparametric model under a multisample testing and minimum-order statistic scheme. Scene anomaly detection has a wide range of use in remote sensing...

Share

Read the Article

Courtesy of THE LIBRARY OF VIRGINIA

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics