background prostate cancer is a serious genetic disease known as the first widespread cancer in men, yet the molecular changes required for the cancer progression is not fully understood. availability of high-throughput gene expression data has led to the development of various computational methods for the identification of critical genes involved in the cancer. methods in this paper, we show ...

MOTIVATION Gene regulatory networks underlying temporal processes, such as the cell cycle or the life cycle of an organism, can exhibit significant topological changes to facilitate the underlying dynamic regulatory functions. Thus, it is essential to develop methods that capture the temporal evolution of the regulatory networks. These methods will be an enabling first step for studying the dri...

INTRODUCTION Our objective was to re-analyse the data used in an industry-funded working paper to study the effect of plain packaging on youth smoking prevalence in Australia, allowing for other tobacco control measures introduced over the period 2001-2013, and using a more appropriate method of analysis. METHODS Monthly smoking prevalence and sample sizes from repeat cross-sectional surveys we...

The development of a country is intimately linked to the industrial that responsible for wealth generation, jobs and income, however, it followed by serious environmental impacts caused production incorrect disposal waste. present research aimed characterize solid waste management system in metallurgic companies from Joaçaba/SC. For this, instrument was applied containing twelve open questions ...

Multiple Logistic Regression Just as in OLS regression, logistic models can include more than one predictor. The analysis options are similar to regression. One can choose to select variables, as with a stepwise procedure, or one can enter the predictors simultaneously, or they can be entered in blocks. Variations of the likelihood ratio test can be conducted in which the chi-square test (G) is...

Logistic regression is the most common method used to model binary response data. When the response is binary, it typically takes the form of 1/0, with 1 generally indicating a success and 0 a failure. However, the actual values that 1 and 0 can take vary widely, depending on the purpose of the study. For example, for a study of the odds of failure in a school setting, 1 may have the value of f...