Evidence map›Paper›PMID 26523133›Full record

ArticleGenomics & informatics2015

A Database of Gene Expression Profiles of Korean Cancer Genome.

Seon-Kyu Kim, In-Sun Chu

Abstract read
In one paragraph

Article in Genomics & informatics, 2015. 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

2 authors.

Seon-Kyu KimMedical Genomics Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea. ; Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea. ; Department of Bioinformatics, Korea University of Science and Technology, Daejeon 34131, Korea.
In-Sun ChuKorean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon 34141, Korea. ; Department of Bioinformatics, Korea University of Science and Technology, Daejeon 34131, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Because there are clear molecular differences entailing different treatment effectiveness between Korean and non-Korean cancer patients, identifying distinct molecular characteristics of Korean cancers is profoundly important. Here, we report a web-based data repository, namely Korean Cancer Genome Database (KCGD), for searching gene signatures associated with Korean cancer patients. Currently, a total of 1,403 cancer genomics data were collected, processed and stored in our repository, an ever-growing database. We incorporated most widely used statistical survival analysis methods including the Cox proportional hazard model, log-rank test and Kaplan-Meier plot to provide instant significance estimation for searched molecules. As an initial repository with the aim of Korean-specific marker detection, KCGD would be a promising web application for users without bioinformatics expertise to identify significant factors associated with cancer in Korean.

Indexed as

biological markersdatabasegenomicsKoreanneoplasmsprognosis

Identifiers

PMID26523133
PMCPMC4623446

What OpenQuestion holds

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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.