Microarrays allow monitoring of gene expression for tens of thousands of genes in parallel and are being used routinely to generate huge amounts of valuable data. Handling and analysis of such data are becoming major bottlenecks in the utilization of the technology. To enable the researcher to interpret the results postanalysis, we have developed a laboratory information management system for microarrays (LIMaS) with an n-tier Java front-end and relational database to record and manage large-scale expression data preanalysis. This system enables the laboratory to replace the paper trail with an efficient and fully customizable interface giving it the ability to adapt to any working practice, e.g., handling many resources used to form many products (chaining of resources). The ability to define sets of activities, resources, and workflows makes LIMaS MIAME-supportive.