In cancer, Transforming Growth Factor beta (TGFbeta) increases proliferation and promotes invasion via selective loss of signalling pathways. Oesophageal adenocarcinoma arises from Barrett's oesophagus, progresses rapidly and is usually fatal. The contribution of perturbed TGFbeta signalling in the promotion of metastasis in this disease has not been elucidated. We therefore investigated the ro...

10 The adaptive lasso is a commonly applied penalty for variable selection in regression mod11 eling. Like all penalties though, its performance depends critically on the choice of tuning 12 parameter. One method for choosing the tuning parameter is via information criteria, such as 13 those based on AIC and BIC. However, these criteria were developed for use with unpenal14 ized maximum likelih...

In many scientific studies, the response variable bears a generalized nonlinear regression relationship with a certain covariate of interest, which may, however, be confounded by other covariates with unknown functional form. We propose a new class of models, the partly parametric generalized additive model (PPGAM) for doing generalized nonlinear regression with the confounding covariate effect...

We discuss the problem of model selection in Genetic Programming using the framework provided by Statistical Learning Theory, i.e. Vapnik-Chervonenkis theory (VC). We present empirical comparisons between classical statistical methods (AIC, BIC) for model selection and the Structural Risk Minimization method (based on VC-theory) for symbolic regression problems. Empirical comparisons of differe...

Model selection is commonly based on some variation of the BIC or minimum message length criteria, such as MML and MDL. In either case the criterion is split into two terms: one for the model (data code length/model complexity) and one for the data given the model (message length/data likelihood). For problems such as change detection, unsupervised segmentation or data clustering it is common p...

Title of Document: THE MIXTURE DISTRIBUTION POLYTOMOUS RASCH MODEL USED TO ACCOUNT FOR RESPONSE STYLES ON RATING SCALES: A SIMULATION STUDY OF PARAMETER RECOVERY AND CLASSIFICATION ACCURACY Youngmi Cho, Doctor of Philosophy, 2013 Directed By: Professor Jeffrey R. Harring Professor George B. Macready Department of Human Development and Quantitative Methodology Response styles presented in rating...

The widely used model for evolutionary relationships is a bifurcating tree with all taxa/observations placed at the leaves. This is not appropriate if the taxa have been densely sampled across evolutionary time and may be in a direct ancestral relationship, or if there is not enough information to fully resolve all the branching points in the evolutionary tree. In this article, we present a fas...

bic is a novel gene identified at a common retroviral integration site in avian leukosis virus-induced lymphomas and has been implicated as a collaborator with c-myc in B lymphomagenesis. It lacks an extensive open reading frame and is believed to function as an untranslated RNA (W. Tam, Gene 274:157-167, 2001; W. Tam, D. Ben-Yehuda, and W. S. Hayward, Mol. Cell. Biol. 17:1490-1502, 1997). The ...

BACKGROUND Innate immune responses are fine-tuned by small noncoding RNA molecules termed microRNAs (miRs) that modify gene expression in response to the environment. During acute infections, miRs can be secreted in extracellular vesicles (EV) to facilitate cell-to-cell genetic communication. The purpose of this study was to characterize the baseline population of miRs secreted in EVs in the ai...

Motivation: A stepwise structural equation modeling algorithm (SSEM) has been developed to infer genetic networks from time course microarray data. Besides observed variables, SSEM also incorporates hidden variables in order to depict regulations from proteins and other molecules that are not measured by microarrays. SSEM can learn the structure of a genetic network from microarray data. We hav...