earticle

영어

The first thing that comes to mind when trying to bring genes from a list into some biologically meaningfully context is gene ontology(GO), an expert-curated database assigning genes to various functional categories. And there are two ways to carry the analysis beyond GO classification deeper into biology: going to the molecular level, which is promoter and regulatory network analysis, or employing the vast-accumulated knowledge from the literature to carry out pathway analysis. This knowledge is scattered throughout numerous scientific publications. Scientific literature is a source of the most reliable and comprehensive knowledge about molecular interaction networks. Pathway and network analyses are rapidly becoming the mainstream tools for functional interpretation of high-throughput data. Pathway analysis tools are also popular for the analysis of drug action and validation of drug efficacy and toxicity. In this talk we will discuss pathway-centric methods we apply to high throughput, genomic scale
experiments. Using several case studies, we will illustrate how pathway-centric methods
allow us to extract insights from multiple experiments that may otherwise be overlooked.