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| Seminar Schedule (Seminar Organizer: Prof. Ziv Bar-Joseph) | |
Machine Learning Lunchtime Chats
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Spring 2007 Seminar
Date: April 12, 2007 Time: 2:00 PM - 3:00 PM Location: 1507 Newell-Simon Hall Speaker: Yanxin Shi LTI PhD Student, ML MS Student Title: Continuous Hidden Process Model for Time Series Expression Experiments Abstract: When analyzing gene expression experiments researchers are often interested in identifying the set of biological processes that are up or down regulated under the experimental condition studied. Current approaches, including clustering expression profiles and averaging the expression profiles of genes known to participate in specific processes, fail to provide an accurate estimate of the activity levels of many biological processes. In this talk, I will introduce a probabilistic Continuous Hidden Process Model (CHPM) for time series expression data. CHPM can simultaneously determine the most probable assignment of genes to processes and the level of activation of these processes over time. To infer model parameters CHPM uses multiple time series datasets and incorporates prior biological knowledge. Applying CHPM to both simulated expression data and yeast expression data, we show that our algorithm produces more accurate functional assignments for genes compared to other expression analysis methods. The inferred process activity levels can be used to study the relationships between biological processes. New biological experiments were also conducted, confirming some of the process activity levels predicted by CHPM.