Evidence map›Paper›PMID 17570735›Full record

ArticleMolecular diagnosis & therapy2007

DGEM--a microarray gene expression database for primary human disease tissues.

Yuni Xia, Andrew Campen, Dan Rigsby, Ying Guo, Xingdong Feng, Eric W Su, Mathew Palakal, Shuyu Li

Abstract read
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In one paragraph

Article in Molecular diagnosis & therapy, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 31% 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

1 citing paper in PubMed, 8 citations in OpenAlex.

  1. Article
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

8 authors at 4 institutions in 1 country.

Yuni XiaDepartment of Computer and Information Science, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana, USA.
Andrew Campen
Dan Rigsby
Ying Guo
Xingdong Feng
Eric W Su
Mathew Palakal
Shuyu Li
Indiana University – Purdue University Indianapolis · USEli Lilly (United States) · USUniversity of Indianapolis · USUniversity of Illinois Urbana-Champaign · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene expression patterns can reflect gene regulations in human tissues under normal or pathologic conditions. Gene expression profiling data from studies of primary human disease samples are particularly valuable since these studies often span many years in order to collect patient clinical information and achieve a large sample size. Disease-to-Gene Expression Mapper (DGEM) provides a beneficial community resource to access and analyze these data; it currently includes Affymetrix oligonucleotide array datasets for more than 40 human diseases and 1400 samples. The data are normalized to the same scale and stored in a relational database. A statistical-analysis pipeline was implemented to identify genes abnormally expressed in disease tissues or genes whose expressions are associated with clinical parameters such as cancer patient survival. Data-mining results can be queried through a web-based interface at http://dgem.dhcp.iupui.edu/. The query tool enables dynamic generation of graphs and tables that are further linked to major gene and pathway resources that connect the data to relevant biology, including Entrez Gene and Kyoto Encyclopedia of Genes and Genomes (KEGG). In summary, DGEM provides scientists and physicians a valuable tool to study disease mechanisms, to discover potential disease biomarkers for diagnosis and prognosis, and to identify novel gene targets for drug discovery. The source code is freely available for non-profit use, on request to the authors.

Indexed as

Databases, GeneticGene Expression ProfilingAlgorithmsBiomarkersDrug TherapyGenetic Diseases, InbornHumansInformation Storage and RetrievalInternetOligonucleotide Array Sequence AnalysisSoftwareBiomarkers

Identifiers

PMID17570735
OpenAlexW2094703935

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.