SegMine workflows for semantic microarray data analysis in Orange4WS.

摘要: In experimental data analysis, bioinformatics researchers increasingly rely on tools that enable the composition and reuse of scientific workflows. The utility current workflow environments can be significantly increased by offering advanced mining services as components. Such support, for instance, knowledge discovery from diverse distributed sources (such GO, KEGG, PubMed, databases). Specifically, cutting-edge analysis approaches, such semantic mining, link discovery, visualization, have not yet been made available to investigating complex biological datasets. We present a new methodology, SegMine, microarray exploiting general knowledge, environment, Orange4WS, with integrated support web in which SegMine methodology is implemented. consists two main steps. First, subgroup algorithm used construct elaborate rules identify enriched gene sets. Then, service creation visualization hypotheses. implemented set workflows demonstrated applications. senescence human stem cells, use resulted three novel research hypotheses could improve understanding underlying mechanisms identification candidate marker genes. Compared systems, offers improved hypothesis generation interpretation an easy-to-use environment.