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Research Article

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Mol. Cells 2013; 36(5): 472-475

Published online November 8, 2013

https://doi.org/10.1007/s10059-013-0249-9

© The Korean Society for Molecular and Cellular Biology

EPITRANS: A Database that Integrates Epigenome and Transcriptome Data

Soo Young Cho, Jin Choul Chai, Soo Jun Park, Hyemyung Seo, Chae-Bong Sohn, and Young Seek Lee

Author Info. +

1Depatment of Molecular and Life Sciences, Hanyang University, Ansan 425-791, Korea, 2Laboratory of Developmental Biology and Genomics, College of Veterinary Medicine, Research Institute for Veterinary Science, Brain Korea 21 Program for Veterinary Science, 3Interdisciplinary Program for Bioinformatics, Program for Cancer Biology and BIO-MAX Institute, Seoul National University, Seoul 151-742, Korea, 4MRC Harwell, Mammalian Genetics Unit, Harwell Science and Innovation Campus, Oxfordshire, United Kingdom, 5Bio-Medical IT Convergence Research Department, ETRI, Daejeon 305-700, Korea, 6Department of Electronics and Communications Engineering, Kwangwoon University, Seoul 139-701, Korea, 7These authors contributed equally to this work.

Received: September 5, 2013; Accepted: September 10, 2013

Abstract

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Epigenetic modifications affect gene expression and thereby govern a wide range of biological processes such as differentiation, development and tumorigenesis. Recent initiatives to define genome-wide DNA methy-lation and histone modification profiles by microarray and sequencing methods have led to the construction of databases. These databases are repositories for international epigenetic consortiums or provide mining results from PubMed, but do not integrate the epigenetic information with gene expression changes. In order to overcome this limitation, we constructed EPITRANS, a novel database that visualizes the relationships between gene expression and epigenetic modifications. EPITRANS uses combined analysis of epigenetic modification and gene expression to search for cell function-related epigenetic and transcriptomic al-terations (Freely available on the web at http://epitrans.org).

Keywords database, epigenome, transcriptome

Article

Research Article

Mol. Cells 2013; 36(5): 472-475

Published online November 30, 2013 https://doi.org/10.1007/s10059-013-0249-9

Copyright © The Korean Society for Molecular and Cellular Biology.

EPITRANS: A Database that Integrates Epigenome and Transcriptome Data

Soo Young Cho, Jin Choul Chai, Soo Jun Park, Hyemyung Seo, Chae-Bong Sohn, and Young Seek Lee

1Depatment of Molecular and Life Sciences, Hanyang University, Ansan 425-791, Korea, 2Laboratory of Developmental Biology and Genomics, College of Veterinary Medicine, Research Institute for Veterinary Science, Brain Korea 21 Program for Veterinary Science, 3Interdisciplinary Program for Bioinformatics, Program for Cancer Biology and BIO-MAX Institute, Seoul National University, Seoul 151-742, Korea, 4MRC Harwell, Mammalian Genetics Unit, Harwell Science and Innovation Campus, Oxfordshire, United Kingdom, 5Bio-Medical IT Convergence Research Department, ETRI, Daejeon 305-700, Korea, 6Department of Electronics and Communications Engineering, Kwangwoon University, Seoul 139-701, Korea, 7These authors contributed equally to this work.

Received: September 5, 2013; Accepted: September 10, 2013

Abstract

Epigenetic modifications affect gene expression and thereby govern a wide range of biological processes such as differentiation, development and tumorigenesis. Recent initiatives to define genome-wide DNA methy-lation and histone modification profiles by microarray and sequencing methods have led to the construction of databases. These databases are repositories for international epigenetic consortiums or provide mining results from PubMed, but do not integrate the epigenetic information with gene expression changes. In order to overcome this limitation, we constructed EPITRANS, a novel database that visualizes the relationships between gene expression and epigenetic modifications. EPITRANS uses combined analysis of epigenetic modification and gene expression to search for cell function-related epigenetic and transcriptomic al-terations (Freely available on the web at http://epitrans.org).

Keywords: database, epigenome, transcriptome

Mol. Cells
Nov 30, 2023 Vol.46 No.11, pp. 655~725
COVER PICTURE
Kim et al. (pp. 710-724) demonstrated that a pathogen-derived Ralstonia pseudosolanacearum type III effector RipL delays flowering time and enhances susceptibility to bacterial infection in Arabidopsis thaliana. Shown is the RipL-expressing Arabidopsis plant, which displays general dampening of the transcriptional program during pathogen infection, grown in long-day conditions.
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