Evidence map›Paper›PMID 15222896›Full record

ArticleBMC genomics2004

Feature extraction and signal processing for nylon DNA microarrays.

F Lopez, J Rougemont, B Loriod, A Bourgeois, L Loï, F Bertucci, P Hingamp, R Houlgatte, S Granjeaud

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In one paragraph

Article in BMC genomics, 2004. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
–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, 1 synthesis or guideline pooled it.

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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

9 authors.

F LopezTAGC, INSERM-ERM 206, Parc Scientifique de Luminy, 13288 Marseille, France. lopez@tagc.univ-mrs.fr
J Rougemont
B Loriod
A Bourgeois
L Loï
F Bertucci
P Hingamp
R Houlgatte
S Granjeaud

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHigh-density DNA microarrays require automatic feature extraction methodologies and softwares. These can be a potential source of non-reproducibility of gene expression measurements. Variation in feature location or in signal integration methodology may be a significant contribution to the observed variance in gene expression levels.

resultsWe explore sources of variability in feature extraction from DNA microarrays on Nylon membrane with radioactive detection. We introduce a mathematical model of the signal emission and derive methods for correcting biases such as overshining, saturation or variation in probe amount. We also provide a quality metric which can be used qualitatively to flag weak or untrusted signals or quantitatively to modulate the weight of each experiment or gene in higher level analyses (clustering or discriminant analysis).

conclusionsOur novel feature extraction methodology, based on a mathematical model of the radioactive emission, reduces variability due to saturation, neighbourhood effects and variable probe amount. Furthermore, we provide a fully automatic feature extraction software, BZScan, which implements the algorithms described in this paper.

Indexed as

Oligonucleotide Array Sequence AnalysisAlgorithmsAnimalsArabidopsis ProteinsBiasBreast NeoplasmsCarbon-Oxygen LigasesCluster AnalysisDensitometryDiscriminant AnalysisDNA, NeoplasmDNA, PlantGene Expression ProfilingHumansImage Processing, Computer-AssistedMiceArabidopsis ProteinsCarbon-Oxygen Ligaseschlorophyll synthetaseDNA, NeoplasmDNA, PlantNylonsPhosphorus RadioisotopesRNA, Messenger

Identifiers

PMID15222896
PMCPMC471548

What OpenQuestion holds

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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.