A Platform for Processing Expression of Short Time Series (PESTS)

Background: Time course microarray profiles examine the expression of genes over a time domain. They are necessary in order to determine the complete set of genes that are dynamically expressed under given conditions, and to determine the interaction between these genes. Because of cost and resource issues, most time series datasets contain less than 9 points and there are few tools available geared towards the analysis of this type of data. Results: To this end, we introduce a platform for Processing Expression of Short Time Series (PESTS). It was designed with a focus on usability and interpretability of analyses for the researcher. As such, it implements several standard techniques for comparability as well as visualization functions. However, it is designed specifically for the unique methods we have developed for significance analysis, multiple test correction and clustering of short time series data. The central tenet of these methods is the use of biologically relevant features...

• Type: Journal
• Year: 2011
• Where: BMCBI
• Authors: Anshu Sinha, Marianthi Markatou
• Keywords: Artificial Intelligence, BMCBI 2011, Short Time Series, Time Series, Visualization Functions