1:00 pm Tuesday, April 4, 2006
Biomathematics Seminar : Uncovering Principles of Biology and Physics From DNA Microarray Data with Blind Source Separation Models by
Orly Alter [mail] (Department of Biomedical Engineering, Institute for Cellular and Molecular Biology, UT Austin) in RLM 12.166
DNA microarrays make it possible, for the first time, to record the complete genomic signals that guide the progression of cellular processes. I will discuss the first data-driven models that were created from these genome-scale data, using blind source separation models. -- Models of RNA expression data from yeast and human during their cell cycle programs and DNA-binding data from yeast transcription factors and replication initiation proteins predict a novel mechanism of regulation, which correlates replication initiation with transcription. The predicted mechanism is in agreement with current understanding of replication initiation and is supported by recent experimental results. -- A recent model of mRNA gene transcript size data from yeast predicts an asymmetry in RNA gel electrophoresis band broadening. The predicted asymmetry can be explained with a transformation of coordinates to the frame of reference in which the RNA molecules are stationary. -- 1. Alter, Brown & Botstein, PNAS 97, 10101 (2000). 2. Alter, Brown & Botstein, PNAS 100, 3351 (2003). 3. Alter & Golub, PNAS 101, 16577 (2004). 4. Alter & Golub, PNAS 102, 17559 (2005).
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