An Integrated approach using Epigenetic data: Identifying Transcription Factor Binding Sites and Constructing Genome-wide Transcriptional Maps

Speaker:	Dr. Kyoung-Jae WON
		University of California, San Diego, USA

Title:		"An Integrated approach using Epigenetic data:
		 Identifying Transcription Factor Binding Sites and
		 Constructing Genome-wide Transcriptional Maps"

Date:		Monday, 12 April 2010

Time:		4:00pm - 5:00pm

Venue:		Lecture Theater F (near lifts 25/26) HKUST

Abstract:

Identification of transcription factors (Tfs) target loci in a specific
tissue or at a specific developmental stage is crucial for understanding
transcriptional regulation in eukaryotes. However, genome-wide prediction
of TF binding sites in eukaryotes has suffered from limited information,
which is needed to accurately identify functional elements.

To this end, we present an integrated approach, called Chromia, that
integrates sequence information and epigenetic information. Chromia is
composed of a hidden Markov model that integrates information from
multiple sources. Using epigenetic signatures and a motif score as input,
Chromia captures the characteristic patterns of a TF binding motif
occurrences and the histone modification signature associated with
regulatory elements such as promoters and enhancers. We demonstrated its
usefulness on genome-wide predictions of target loci of 13 TFs in the
mouse embryonic stem (mES).

Furthermore, we constructed the genome-wide transcriptional networks in
human embryonic stem cells and the differentiated cells. Defining a node
as a TF or a gene and an edge as a regulatory interaction, a graph can
represent the transcriptional network in a cell. The regulatory
interactions can be inferred by using the integrated model in a condition
specific manner. Statistical analysis on the core-network will unveil
crucial components for self-renewal in stem cells. Moreover, comparative
analysis of epigenetic states identified regulatory elements related to
cell differentiation


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Biography:

Kyoungjae Won received the BS and MS degree in electronics from Chung-Ang
University, Korea and the Ph.D. degree in electronics and computer science
from the University of Southampton, U.K.  Under the volunteer program of
the South Korean government, he worked as an academic staff at the
National University of Hanoi, Vietnam.  He worked as a postdoctoral fellow
at University of Copenhagen, Denmark, and University of California, San
Diego, US. His research interests include bioinformatics, computational
biology and machine learning.