Biology is now an information-intensive science and various research areas, like molecular biology, evolutionary biology or environmental biology, heavily depend on the availability and the efficient use of information. Data mining, that regroups several techniques for analyzing very large datasets, is used to solve problems in an increasing number of biological applications. This article focuses on the analysis of transcriptome, that reflects gene activity in a given cell population at a given time. We describe research themes in transcriptomics related to domain knowledge in biology. We are particularly interested in the way this knowledge can be efficiently combined and used during the various phases of a data mining process, in the most acknowledged applications in transcriptomics.