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While only semi-quantitative due to possible differing labeling and hybridization efficiencies that could occur during microarray experiments, information on gene intensities is provided since the intensity data aid in pathway interpretation of possible carbon flow.
In order to make the mapping file useful for studies involving grape microarray experiments, information from two microarray platforms was used, the Array Ready Oligo Set Vitis vinifera (grape) AROS V1.0 Oligo Set (Operon, Qiagen) covering 14,562 transcripts and the GeneChip® Vitis vinifera Genome Array with 14,496 probesets (Affymetrix).
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ArrayTrack is logically constructed of three linked components: a) a library (LIB) that mirrors critical data in public databases; b) a database (MicroarrayDB) that stores microarray experiment information that is Minimal Information About a Microarray Experiment (MIAME) compliant; and c) tools (TOOL) that operate on experimental and public data for knowledge discovery.
However, with the existing Web Services no microarray experiments or information on microbial gene regulatory networks can be accessed.
The challenge of discovering novel regulatory interactions or validating existing networks can be addressed by comparing groups of genes with similar expression profiles that have been identified in microarray experiments with information about the known regulatory network of an organism.
Minimum Information About a Microarray Experiment (MIAME) information about this experiment has been deposited in NCBI's Gene Expression Omnibus (GEO) [64].
Minimum Information About a Microarray Experiment (MIAME) information about this experiment has been deposited to the NCBI's Gene Expression Omnibus (GEO) database [ 38].
Raw microarray data have been curated and accepted in GEO (a public repository for microarray data, aimed at storing MIAME (Minimum Information About Microarray Experiments) compliant data in accordance with MGED (Microarray Gene Expression Data) recommendations.
Ontologies can also be used to describe the information model, such as the MGED (Microarray Gene Expression Data) ontology describing microarray experiments or hospital information coded using the ICD-10 (International Classification of Diseases) coding system, so that the data can easily flow across systems that use the same model (4 ).
The resulting databases from microarray experiments contained additional information which may be useful for future investigations.
Microarray experiments provide more information than what the authors can interpret alone.
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