Group SCAD regression analysis for microarray time course gene expression data
نویسندگان
چکیده
منابع مشابه
Group SCAD regression analysis for microarray time course gene expression data
MOTIVATION Since many important biological systems or processes are dynamic systems, it is important to study the gene expression patterns over time in a genomic scale in order to capture the dynamic behavior of gene expression. Microarray technologies have made it possible to measure the gene expression levels of essentially all the genes during a given biological process. In order to determin...
متن کاملTime-Course Gene Set Analysis for Longitudinal Gene Expression Data
Gene set analysis methods, which consider predefined groups of genes in the analysis of genomic data, have been successfully applied for analyzing gene expression data in cross-sectional studies. The time-course gene set analysis (TcGSA) introduced here is an extension of gene set analysis to longitudinal data. The proposed method relies on random effects modeling with maximum likelihood estima...
متن کاملStatistical methods for analysis of time course gene expression data.
Since many biological systems or regulatory networks are dynamic systems, gene expression levels measured over different time points during a given biological process can often provide more insights about the underlying system. These gene expression data measured over time are often called the time-course gene expression data. One unique feature of such data is the time dependency of the gene e...
متن کاملData Analysis: Microarray Gene Expression
Most genomic data within the NextBio platform are generated using the Affymetrix platform (Figure 2). Ideally, all Affymetrix data would be imported as CEL files, and processed using the same normalization method, such as Robust Multi-array Average (RMA)1; however, for pre-existing experiments, this is often impossible. In this case, probeset-level Microarray Suite version 5 (MAS5) intensities2...
متن کاملFourier Analysis of Time Course Microarray Data and its Relevance to Gene Expression Dynamics
One of the exciting, ongoing research areas within the fields of bioinformatics and systems biology is the elucidation of gene and protein networks. While there is a large and important effort towards identifying the specific interactions among genes and proteins, there is also a need to understand the dynamics of gene and protein expression over time. The goal of this study is to use methods f...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Bioinformatics
سال: 2007
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/btm125