Extracting binary signals from microarray time-course data
نویسندگان
چکیده
منابع مشابه
Extracting binary signals from microarray time-course data
This article presents a new method for analyzing microarray time courses by identifying genes that undergo abrupt transitions in expression level, and the time at which the transitions occur. The algorithm matches the sequence of expression levels for each gene against temporal patterns having one or two transitions between two expression levels. The algorithm reports a P-value for the matching...
متن کاملExtracting meaning from microarray data.
Gene expression is complex: many mRNAs change in abundance in response to a new condition. But while some of these expression changes may be direct, many may be downstream, indirect effects. One of the major problems of microarray data analysis is distinguishing between these changes. Some of the most common methods of analysis are discussed, in the context of their ability to distinguish betwe...
متن کاملDynamic Modelling of Microarray Time Course Data
The analysis of gene expression profiles, obtained from DNA microarray experiments, is used to discover relationships between genes and to discern groups of genes involved common processes. The principal aim of this paper is to introduce dynamic modelling of microarray time course data. A novel approach to identify similar gene expression profiles is presented. Using parametric modelling, we de...
متن کاملExtracting galactic binary signals from the first round of Mock LISA Data Challenges
We report on the performance of an end-to-end Bayesian analysis pipeline for detecting and characterizing galactic binary signals in simulated LISA data. Our principal analysis tool is the Blocked-Annealed Metropolis Hasting (BAM) algorithm, which has been optimized to search for tens of thousands of overlapping signals across the LISA band. The BAM algorithm employs Bayesian model selection to...
متن کاملExtracting three-way gene interactions from microarray data
MOTIVATION It is an important and difficult task to extract gene network information from high-throughput genomic data. A common approach is to cluster genes using pairwise correlation as a distance metric. However, pairwise correlation is clearly too simplistic to describe the complex relationships among real genes since co-expression relationships are often restricted to a specific set of bio...
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: Nucleic Acids Research
سال: 2007
ISSN: 1362-4962,0305-1048
DOI: 10.1093/nar/gkm284