Li Lab: Difference between revisions
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Our lab is focused on the design and application of statistical and computational algorithms to elucidate global transcription regulatory mechanism. | |||
An elaborate system of transcription regulation is responsible for the morphological and behavioral complexity in higher eukaryotes. This regulatory system consists of diverse trans-acting protein factors and cis-acting regulatory DNA sequences. Recently, Chromatin ImmunoPrecipitation coupled with whole genome tiled microarray (ChIP-chip) and/or next-generation sequencing (Solexa, SOLid and 454) has evolved as a powerful and unbiased technique to study genome-wide in vivo binding of the trans-acting protein factors. The application of this technology to multiple factors and/or in multiple conditions allows biologists to study how trans-factors differentially regulate transcription in a combinatorial manner. However, it also poses great challenges for the development of effective algorithms, the key link between massive raw data and biological hypotheses. | |||
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Revision as of 12:32, 14 November 2007
Research InformationOur lab is focused on the design and application of statistical and computational algorithms to elucidate global transcription regulatory mechanism. An elaborate system of transcription regulation is responsible for the morphological and behavioral complexity in higher eukaryotes. This regulatory system consists of diverse trans-acting protein factors and cis-acting regulatory DNA sequences. Recently, Chromatin ImmunoPrecipitation coupled with whole genome tiled microarray (ChIP-chip) and/or next-generation sequencing (Solexa, SOLid and 454) has evolved as a powerful and unbiased technique to study genome-wide in vivo binding of the trans-acting protein factors. The application of this technology to multiple factors and/or in multiple conditions allows biologists to study how trans-factors differentially regulate transcription in a combinatorial manner. However, it also poses great challenges for the development of effective algorithms, the key link between massive raw data and biological hypotheses.
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