Evidence map›Paper›PMID 16790046›Full record

ArticleBMC bioinformatics2006

Web-based analysis of the mouse transcriptome using Genevestigator.

Oliver Laule, Matthias Hirsch-Hoffmann, Tomas Hruz, Wilhelm Gruissem, Philip Zimmermann

Abstract read
In one paragraph

Article in BMC bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

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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

5 authors.

Oliver LauleInstitute of Plant Sciences, ETH Zurich, 8092 Zurich, Switzerland. ola@ethz.ch
Matthias Hirsch-Hoffmann
Tomas Hruz
Wilhelm Gruissem
Philip Zimmermann

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGene function analysis often requires a complex and laborious sequence of laboratory and computer-based experiments. Choosing an effective experimental design generally results from hypotheses derived from prior knowledge or experimentation. Knowledge obtained from meta-analyzing compendia of expression data with annotation libraries can provide significant clues in understanding gene and network function, resulting in better hypotheses that can be tested in the laboratory. DESCRIPTION: Genevestigator is a microarray database and analysis system allowing context-driven queries. Simple but powerful tools allow biologists with little computational background to retrieve information about when, where and how genes are expressed. We manually curated and quality-controlled 3110 mouse Affymetrix arrays from public repositories. Data queries can be run against an annotation library comprising 160 anatomy categories, 12 developmental stage groups, 80 stimuli, and 182 genetic backgrounds or modifications. The quality of results obtained through Genevestigator is illustrated by a number of biological scenarios that are substantiated by other types of experimentation in the literature.

conclusionThe Genevestigator-Mouse database effectively provides biologically meaningful results and can be accessed at https://www.genevestigator.ethz.ch.

Indexed as

Databases, GeneticInformation Storage and RetrievalInternetTranscription, GeneticAnimalsDatabase Management SystemsGene Expression ProfilingMiceOligonucleotide Array Sequence AnalysisReproducibility of ResultsUser-Computer Interface

Identifiers

PMID16790046
PMCPMC1533866

What OpenQuestion holds

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LicenceCC BY
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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.