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| Seminar Schedule (Seminar Organizer: Prof. Ziv Bar-Joseph) | |
Machine Learning Lunchtime Chats
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Spring 2007 Seminar
Date: January 10, 2007 Time: 10:00 AM - 11:00 AM (Refreshments) Location: 3305 Newell-Simon Hall Speaker: Jason Ernst PhD Candidate Title: Computational Methods for Analyzing and Modeling Gene Regulation Dynamics Abstract: Gene regulation is a central biological process whose disruption can lead to many diseases. This process is largely controlled by a dynamic network of protein-DNA interactions that controls the expression of the specific genes needed for responses to stimuli. Time series microarray gene expression experiments have become a widely used technique to study the dynamics of this process. The proposed thesis will introduce new computational methods designed to use data from these experiments to analyze and model the dynamics of gene regulation. The first method, STEM (Short Time-series Expression Miner), is a clustering algorithm and software specifically designed for short time series expression experiments (~8 time points or fewer), which represent the substantial majority of experiments in this domain. The second method, DREM (Dynamic Regulatory Events Miner), integrates static data about transcription factor-gene interactions with time series expression data to model regulatory networks while taking into account their dynamic nature. The method is based on an Input-Output Hidden Markov Model and works by identifying bifurcation points, places in the time series where the expression of a subset of genes diverges from the rest of the genes. Applying the method to study yeast response to stress, the method has made new predictions for yeast that have been experimentally validated. Finally we will discuss additional challenges and our proposed solutions so that DREM can be applied effectively to higher organisms such as human. Thesis Committee: Ziv Bar-Joseph (Chair), Zoubin Ghahramani, Naftali Kaminski (Univ. of Pittsburgh), Zoltan Oltvai (Univ. of Pittsburgh), Eric Xing