| Current high-throughput technology in genomics creates a large amount of biological data. Bioinformatics approaches are directed towards understanding such data on a systems biology level. Advanced mathematical methods like principal component analysis, clustering, neural networks, support vector machine (SVM) approaches and neural networks can help to find patterns in the data. However, to really understand the data the patterns must be combined with existing knowledge. One of the approaches to do so is to associate these data to functional classifications such as can be found in the Gene Ontology. Other methods focus on using biological pathways coming from both public and private pathway databases like KEGG, WikiPathways, Reactome, and MetaCore. Some of... |
