We developed a new methodology SegMine for semantic analysis of microarray data by exploiting general biological knowledge, and a new workflow environment Orange4WS which supports web service integration. The SegMine methodology consists of two main steps. First, a semantic subgroup discovery algorithm is used to construct semantically annotated rules that identify enriched gene sets. Then, link discovery service BioMine is used for the creation and visualization of new biological hypotheses. The utility of SegMine, implemented as a set of workflows in Orange4WS, is demonstrated in two microarray data analysis applications. In the analysis of senescence in human stem cells, the use of SegMine resulted in three novel research hypotheses that can improve the understanding of underlying mechanisms of senescence and the identification of candidate marker genes.
COBISS.SI-ID: 25208871
We developed a novel Service-oriented Knowledge Discovery framework and its implementation in a service-oriented data mining environment Orange4WS (Orange for Web Services), based on the existing Orange data mining toolbox and its visual programming environment, which enables manual composition of data mining workflows. The new service-oriented data mining environment Orange4WS includes the following new features: simple use of web services as remote components that can be included into a data mining workflow; simple incorporation of relational data mining algorithms; a knowledge discovery ontology to describe workflow components (data, knowledge and data mining services) in an abstract and machine-interpretable way, and its use by a planner that enables automated composition of data mining workflows. These new features are show-cased in three real-world scenarios.
COBISS.SI-ID: 25004071