High-throughput technologies have led to the rapid generation of large-scale datasets about genes and gene products. These technologies have also shifted our research focus from “single genes” to “gene sets” and “gene networks”. We are developing bioinformatics tools to help biologists in exploring these gene sets and networks. WebGestalt (http://genereg.ornl.gov/webgestalt/) is an integrated data mining system for exploring gene sets. WebGestalt is composed of four modules: gene set management, information retrieval, organization/visualization, and statistics. The management module uploads, saves, retrieves and deletes gene sets, as well as performing Boolean operations to generate the unions, intersections or differences between different gene sets. The information retrieval module currently retrieves information for up to 20 attributes for all genes in a gene set. The organization/visualization module organizes and visualizes gene sets in various biological contexts, including Gene Ontology, tissue expression pattern, chromosome distribution, metabolic and signaling pathways, protein domain information and publications. The statistics module recommends and performs statistical tests to suggest biological areas that are important to a gene set and warrant further investigation. GeNetViz is a gene network visualization system, in which Gene Ontology or other functional information can be superimposed. We are working on algorithms to reveal interesting patterns from the given networks. These systems would help translating high throughput experimental data into a better understanding of the underlying biological processes.