Evidence map›Paper›PMID 29312567›Full record

ArticleOncotarget2017

B-CAN: a resource sharing platform to improve the operation, visualization and integrated analysis of TCGA breast cancer data.

Can-Hong Wen, Shao-Min Ou, Xiao-Bo Guo, Chen-Feng Liu, Yan-Bo Shen, Na You, Wei-Hong Cai, Wen-Jun Shen, Xue-Qin Wang, Hai-Zhu Tan

Abstract read
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Can-Hong WenDepartment of Statistical Science, School of Mathematics, Sun Yat-Sen University, Guangzhou, China.
Shao-Min OuDepartment of Physics and Computer Applications, Shantou University Medical College, Guangzhou, China.
Xiao-Bo GuoDepartment of Statistical Science, School of Mathematics, Sun Yat-Sen University, Guangzhou, China.
Chen-Feng LiuDepartment of Statistical Science, School of Mathematics, Sun Yat-Sen University, Guangzhou, China.
Yan-Bo ShenDepartment of Statistical Science, School of Mathematics, Sun Yat-Sen University, Guangzhou, China.
Na YouDepartment of Statistical Science, School of Mathematics, Sun Yat-Sen University, Guangzhou, China.
Wei-Hong CaiDepartment of Computer Science, Shantou University, Guangzhou, China.
Wen-Jun ShenDepartment of Bioinformatics, Shantou University Medical College, Guangzhou, China.
Xue-Qin WangJoint Institute of Engineering, Sun Yat-Sen University, Carnegie Mellon University, Guangzhou, China.
Hai-Zhu TanDepartment of Physics and Computer Applications, Shantou University Medical College, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breast cancer is a high-risk heterogeneous disease with myriad subtypes and complicated biological features. The Cancer Genome Atlas (TCGA) breast cancer database provides researchers with the large-scale genome and clinical data via web portals and FTP services. Researchers are able to gain new insights into their related fields, and evaluate experimental discoveries with TCGA. However, it is difficult for researchers who have little experience with database and bioinformatics to access and operate on because of TCGA's complex data format and diverse files. For ease of use, we build the breast cancer (B-CAN) platform, which enables data customization, data visualization, and private data center. The B-CAN platform runs on Apache server and interacts with the backstage of MySQL database by PHP. Users can customize data based on their needs by combining tables from original TCGA database and selecting variables from each table. The private data center is applicable for private data and two types of customized data. A key feature of the B-CAN is that it provides single table display and multiple table display. Customized data with one barcode corresponding to many records and processed customized data are allowed in Multiple Tables Display. The B-CAN is an intuitive and high-efficient data-sharing platform.

Indexed as

breast cancerdata customizationdata visualizationprivate data centerTCGA

Identifiers

PMID29312567
PMCPMC5752480

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Registered trials

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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.