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Abstract:
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With the rapid advancement in high-throughput technology, extensive repeated measurements have been taken to monitor the system-wide dynamics in many scientific investigations. A typical example is dynamic gene regulatory network studies, in which a series of biological experiments, e.g., DNA microarray, ChIP-chip, are conducted sequentially during a biological process (e.g., cell cycle). The various measurements are then integrated to construct the gene regulatory network. However, the constructed gene regulatory networks in the literature are primarily "static," (i.e., gene clustering membership and transcription factor binding remain unchanged throughout the whole biological process). Therefore dynamic information on cell activities can not be retrieved from such networks.
In this talk, we discuss a flexible functional data approach that overcomes the aforementioned obstacles.
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