Systematic interpretation of microarray data using experiment annotations
نویسندگان
چکیده
منابع مشابه
Supplement to: Systematic interpretation of microarray data using experiment annotations
Analysis-interfering artifacts (yeast data). The Eurofan II Node B2 project [1, 2, 3, 4, 5, 6, 7] was an enterprise to study the S. cerevisiae transcriptome under various experimental conditions (such as high and low glucose concentrations, calcium shortage or heat shock) on a consistent platform. The investigated dataset comprises 229 out of 253 hybridizations performed by five European groups...
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MOTIVATION New biological systems technologies give scientists the ability to measure thousands of bio-molecules including genes, proteins, lipids and metabolites. We use domain knowledge, e.g. the Gene Ontology, to guide analysis of such data. By focusing on domain-aggregated results at, say the molecular function level, increased interpretability is available to biological scientists beyond w...
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MOTIVATION The functional interpretation of microarray datasets still represents a time-consuming and challenging task. Up to now functional categories that are relevant for one or more experimental context(s) have been commonly extracted from a set of regulated genes and presented in long lists. RESULTS To facilitate interpretation, we integrated Gene Ontology (GO) annotations into Correspon...
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MOTIVATION Microarray technology provides access to expression levels of thousands of genes at once, producing large amounts of data. These datasets are valuable only if they are annotated by sufficiently detailed experiment descriptions. However, in many databases a substantial number of these annotations is in free-text format and not readily accessible to computer-aided analysis. RESULTS T...
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ژورنال
عنوان ژورنال: BMC Genomics
سال: 2006
ISSN: 1471-2164
DOI: 10.1186/1471-2164-7-319