Microarray annotation and biological information on function.
OBJECTIVE
Many methods for statistical analysis of gene expression studies by DNA microarrays produce lists of genes as output. To understand gene lists in terms of traditional biology, e.g. which pathways may be affected, it is necessary to get appropriate annotations for the probes on an array.


METHODS
Problems arise with the different sources that have been used by manufacturers to design microarray probes, and their association to biological entities like genes, transcripts and proteins. Function annotation is of crucial importance, and systems like Gene Ontology can be used for this purpose. It arranges annotation terms in a hierarchical manner and thus makes annotations in a gene list amenable to automated analysis.


RESULTS
Several methods for analyses of gene function are described. The hierarchical nature of systems like Gene Ontology particularly suggests using methods from graph theory.


CONCLUSIONS
The main problem in annotating microarray probes and inferring affected functional modules is the incompleteness and degree of error in current biological databases. Initial approaches to make use of functional annotation exist, but have to be extended, in particular with respect to estimating the statistical significance of results.
Brors
B
B
Dept. Theoretical Bioinformatics, German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. b.brors@dkfz.de
D019295:Computational Biology; D015342:DNA Probes; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D015894:Genome, Human / Q000235:genetics*; D006801:Humans; D009687:Nuclear Proteins / Q000145:classification; D020411:Oligonucleotide Array Sequence Analysis; D015513:Oncogene Proteins / Q000145:classification; D011379:Prognosis; D012333:RNA, Messenger / Q000032:analysis
D015342:DNA Probes; D009687:Nuclear Proteins; D015513:Oncogene Proteins; D012333:RNA, Messenger