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Invited: Searching massive epigenome data for evolutionarily conserved sequence motifs

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1 Author(s)
Shinichi Morishita ; Department of Computational Biology, University of Tokyo, Japan

The epigenome, such as nucleosome structure and DNA methylation, regulates expression of genes. Searching for evolutionarily conserved sequence motifs essential for controlling the epigenome is a fundamental problem in biology. Collecting massive epigenome data has been becoming increasingly feasible because of the wide-spread availability of next-generation sequencing technology. Thus, there have been growing interests in the genome-wide analysis of the epigenome. There are some issues to be resolved. Care has to be taken to select samples so as to reduce false-positive findings. Processing enormous epigenome data is a computationally intensive task and needs a suite of software techniques such as suffix array, error correction, customizable data visualization, machine learning, and efficient database management. In this talk, I will overview these issues and their solutions, and discuss remaining bioinformatics problems.

Published in:

Computational Advances in Bio and Medical Sciences (ICCABS), 2011 IEEE 1st International Conference on

Date of Conference:

3-5 Feb. 2011