MAP

Clustering methods are widely used in microarray data analysis. Nevertheless, the significance of clustering results has to be evaluated by domain knowledge. Because there were no common standards of biological databases, such as gene ontology, metabolic and regulatory pathways, etc, the interoperability among databases was not satisfactory. The recent development in “SOURCE” web site is encouraging; however, the cross-hybridization, alternative splicing, pathway and interaction information are not available. Besides, the users need to set up a priority to browse all the information. Therefore, we have developed Microarray Annotation Program (MAP,http://ymbc.ym. edu.tw/map/) to establish a user-centric bioinformatics environment for microarray data analysis

III. The Database was Constructed and Integrated into MAP.

MAP integrates the gene information (via GeneCards), alternative splicing (via PALS db, http://palsdb.ym.edu.tw/), pathway (via KEGG, BioCarta, and GenMAPP), cellular and functional roles (via Gene Ontology), inherited disease (via OMIM), literature (via PubGene), protein-protein interaction (via ProNet), protein domain (via Pfam), and cross-hybridization information among cDNAs (via CHANGE). The cross-hybridization information can be used to design probes to verify microarray data. Besides, this information can also be used to design probes for oligonucleotide array. If a significant gene list of a microarray experiment is also provided, MAP will create a Pathway-Gene Ontology profile (PG-profile). This profile summarizes the number of significant genes and number of probes of a given microarray for each pathway and each gene ontology category. Thus, this profile will help biologists determining the priority to view pathways and gene ontology categories.

Your suggestions for any improvements are encouraged. Please send them to g38903040@ym.edu.tw.

Last modified 21/August/2002 by Shih-Te Yang.