ChimerDB 3.0: An enhanced database for fusion genes from cancer transcriptome and literature data mining

Myunggyo Lee; Kyubum Lee; Namhee Yu; Insu Jang; Ikjung Choi; Pora Kim; Ye EunJang; Byounggun Kim; Sunkyu Kim; Byungwook Lee; Jaewoo Kang; Sanghyuk Lee

ChimerDB 3.0: An enhanced database for fusion genes from cancer transcriptome and literature data mining

Myunggyo Lee, Kyubum Lee, Namhee Yu, Insu Jang, Ikjung Choi, Pora Kim, Ye EunJang, Byounggun Kim, Sunkyu Kim, Byungwook Lee, Jaewoo Kang, Sanghyuk Lee

Research output: Contribution to journal › Article › peer-review

70 Citations (Scopus)

Abstract

Fusion gene is an important class of therapeutic targets and prognostic markers in cancer. ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep sequencing data and manual curations. In this update, the database coverage was enhanced considerably by adding two new modules of The Cancer Genome Atlas (TCGA) RNA-Seq analysis and PubMed abstract mining. ChimerDB 3.0 is composed of three modules of ChimerKB, ChimerPub and ChimerSeq. ChimerKB represents a knowledgebase including 1066 fusion genes with manual curation that were compiled from public resources of fusion genes with experimental evidences. ChimerPub includes 2767 fusion genes obtained from text mining of PubMed abstracts. ChimerSeq module is designed to archive the fusion candidates from deep sequencing data. Importantly, we have analyzed RNA-Seq data of the TCGA project covering 4569 patients in 23 cancer types using two reliable programs of FusionScan and TopHat-Fusion. The new user interface supports diverse search options and graphic representation of fusion gene structure. ChimerDB 3.0 is available at http://ercsb.ewha.ac.kr/fusiongene/.

Original language	English
Pages (from-to)	D784-D789
Journal	Nucleic acids research
Volume	45
Issue number	D1
Publication status	Published - 2017 Jan 1

Bibliographical note

Publisher Copyright:
© The Author(s) 2016.

ASJC Scopus subject areas

Genetics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

@article{eca351a396394b5b987300a9bfb42127,

title = "ChimerDB 3.0: An enhanced database for fusion genes from cancer transcriptome and literature data mining",

abstract = "Fusion gene is an important class of therapeutic targets and prognostic markers in cancer. ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep sequencing data and manual curations. In this update, the database coverage was enhanced considerably by adding two new modules of The Cancer Genome Atlas (TCGA) RNA-Seq analysis and PubMed abstract mining. ChimerDB 3.0 is composed of three modules of ChimerKB, ChimerPub and ChimerSeq. ChimerKB represents a knowledgebase including 1066 fusion genes with manual curation that were compiled from public resources of fusion genes with experimental evidences. ChimerPub includes 2767 fusion genes obtained from text mining of PubMed abstracts. ChimerSeq module is designed to archive the fusion candidates from deep sequencing data. Importantly, we have analyzed RNA-Seq data of the TCGA project covering 4569 patients in 23 cancer types using two reliable programs of FusionScan and TopHat-Fusion. The new user interface supports diverse search options and graphic representation of fusion gene structure. ChimerDB 3.0 is available at http://ercsb.ewha.ac.kr/fusiongene/.",

author = "Myunggyo Lee and Kyubum Lee and Namhee Yu and Insu Jang and Ikjung Choi and Pora Kim and Ye EunJang and Byounggun Kim and Sunkyu Kim and Byungwook Lee and Jaewoo Kang and Sanghyuk Lee",

note = "Publisher Copyright: {\textcopyright} The Author(s) 2016.",

year = "2017",

month = jan,

day = "1",

language = "English",

volume = "45",

pages = "D784--D789",

journal = "Nucleic acids research",

issn = "0305-1048",

publisher = "Oxford University Press",

number = "D1",

}

TY - JOUR

T1 - ChimerDB 3.0

T2 - An enhanced database for fusion genes from cancer transcriptome and literature data mining

AU - Lee, Myunggyo

AU - Lee, Kyubum

AU - Yu, Namhee

AU - Jang, Insu

AU - Choi, Ikjung

AU - Kim, Pora

AU - EunJang, Ye

AU - Kim, Byounggun

AU - Kim, Sunkyu

AU - Lee, Byungwook

AU - Kang, Jaewoo

AU - Lee, Sanghyuk

PY - 2017/1/1

Y1 - 2017/1/1

N2 - Fusion gene is an important class of therapeutic targets and prognostic markers in cancer. ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep sequencing data and manual curations. In this update, the database coverage was enhanced considerably by adding two new modules of The Cancer Genome Atlas (TCGA) RNA-Seq analysis and PubMed abstract mining. ChimerDB 3.0 is composed of three modules of ChimerKB, ChimerPub and ChimerSeq. ChimerKB represents a knowledgebase including 1066 fusion genes with manual curation that were compiled from public resources of fusion genes with experimental evidences. ChimerPub includes 2767 fusion genes obtained from text mining of PubMed abstracts. ChimerSeq module is designed to archive the fusion candidates from deep sequencing data. Importantly, we have analyzed RNA-Seq data of the TCGA project covering 4569 patients in 23 cancer types using two reliable programs of FusionScan and TopHat-Fusion. The new user interface supports diverse search options and graphic representation of fusion gene structure. ChimerDB 3.0 is available at http://ercsb.ewha.ac.kr/fusiongene/.

AB - Fusion gene is an important class of therapeutic targets and prognostic markers in cancer. ChimerDB is a comprehensive database of fusion genes encompassing analysis of deep sequencing data and manual curations. In this update, the database coverage was enhanced considerably by adding two new modules of The Cancer Genome Atlas (TCGA) RNA-Seq analysis and PubMed abstract mining. ChimerDB 3.0 is composed of three modules of ChimerKB, ChimerPub and ChimerSeq. ChimerKB represents a knowledgebase including 1066 fusion genes with manual curation that were compiled from public resources of fusion genes with experimental evidences. ChimerPub includes 2767 fusion genes obtained from text mining of PubMed abstracts. ChimerSeq module is designed to archive the fusion candidates from deep sequencing data. Importantly, we have analyzed RNA-Seq data of the TCGA project covering 4569 patients in 23 cancer types using two reliable programs of FusionScan and TopHat-Fusion. The new user interface supports diverse search options and graphic representation of fusion gene structure. ChimerDB 3.0 is available at http://ercsb.ewha.ac.kr/fusiongene/.

UR - http://www.scopus.com/inward/record.url?scp=85016141538&partnerID=8YFLogxK

M3 - Article

C2 - 27899563

AN - SCOPUS:85016141538

SN - 0305-1048

VL - 45

SP - D784-D789

JO - Nucleic acids research

JF - Nucleic acids research

IS - D1

ER -

ChimerDB 3.0: An enhanced database for fusion genes from cancer transcriptome and literature data mining

Abstract

Bibliographical note

ASJC Scopus subject areas

UN SDGs

Other files and links

Fingerprint

Cite this