title: Translational meta-analysis tool for temporal gene expression profiles.
abstract: Widespread use of microarray technology that led to highly complex datasets often is addressing similar or related biological questions. In translational medicine research is often based on measurements that have been obtained at different points in time. However, the researcher looks at them as a progression over time. If a biological stimulus shows an effect on a particular gene that is reversed over time, this would show, for instance, as a peak in the gene's temporal expression profile. Our program SPOT helps researchers find these patterns in large sets of microarray data. We created the software tool using open-source platforms and the Semantic Web tool Protégé-OWL.
authors.affiliation: School of Computing and Information Systems, Grand Valley State University, Allendale, MI, USA. tuschg@gvsu.edu
authors.forename: Guenter
authors.initials: G
authors.lastname: Tusch
authors.forename: Olvi
authors.initials: O
authors.lastname: Tole
mesh_terms: D001185:Artificial Intelligence; D057225:Data Mining / Q000379:methods*; D003628:Database Management Systems; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D008498:Medical Record Linkage / Q000379:methods*; D015201:Meta-Analysis as Topic; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D012984:Software; D057170:Translational Research, Biomedical / Q000379:methods*