Evidence map›Paper›PMID 27899563›Full record

ArticleNucleic acids research2017

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 Eun Jang, Byounggun Kim, Sunkyu Kim, Byungwook Lee and 2 more

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
57citing papers in PubMed, 1 pooled it
5.6field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

57 citing papers in PubMed, 1 synthesis or guideline pooled it, 85 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 4 institutions in 2 countries.

Myunggyo LeeDepartment of Bio-Information Science, Ewha Womans University, Seoul 03760, Republic of Korea.ORCID 0000-0003-2015-3939
Kyubum LeeDepartment of Computer Science and Engineering, Korea University, Seoul 02841, Republic of Korea.ORCID 0000-0003-2015-3939
Namhee YuDepartment of Life Science, Ewha Womans University, Seoul 03760, Republic of Korea.
Insu JangKorean Bioinformation Center, Korean Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea.
Ikjung ChoiEwha Research Center for Systems Biology, Ewha Womans University, Seoul 03760, Republic of Korea.
Pora KimCenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA.
Ye Eun JangDepartment of Bio-Information Science, Ewha Womans University, Seoul 03760, Republic of Korea.
Byounggun KimInterdisciplinary Graduate Program in Bioinformatics, Korea University, Seoul 02841, Republic of Korea.
Sunkyu KimInterdisciplinary Graduate Program in Bioinformatics, Korea University, Seoul 02841, Republic of Korea.
Byungwook LeeKorean Bioinformation Center, Korean Research Institute of Bioscience and Biotechnology, Daejeon 34141, Republic of Korea.ORCID 0000-0003-2015-3939
Jaewoo KangDepartment of Computer Science and Engineering, Korea University, Seoul 02841, Republic of Korea kangj@korea.ac.kr.
Sanghyuk LeeDepartment of Bio-Information Science, Ewha Womans University, Seoul 03760, Republic of Korea sanghyuk@ewha.ac.kr.ORCID 0000-0003-2015-3939
Ewha Womans University · KRKorea University · KRKorea Research Institute of Bioscience and Biotechnology · KRThe University of Texas Health Science Center at Houston · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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/.

Indexed as

Databases, GeneticData MiningTranscriptomeComputational BiologyGene Expression ProfilingHumansNeoplasmsOncogene Proteins, FusionSoftwareUser-Computer InterfaceOncogene Proteins, Fusion

Identifiers

PMID27899563
PMCPMC5210563
OpenAlexW2557863110

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.