Veldhoven, A. http://repub.eur.nl/res/aut/15802/ List of Publications en http://repub.eur.nl/static-eur/img/logo.png RePub, Erasmus University Rotterdam http://repub.eur.nl Anni 2.0: A multipurpose text-mining tool for the life sciences (Article) http://repub.eur.nl/res/pub/30346/ 2008-06-12T00:00:00Z Anni 2.0 is an online tool (http://biosemantics.org/anni/) to aid the biomedical researcher with a broad range of information needs. Anni provides an ontology-based interface to MEDLINE and retrieves documents and associations for several classes of biomedical concepts, including genes, drugs and diseases, with established text-mining technology. In this article we illustrate Anni's usability by applying the tool to two use cases: interpretation of a set of differentially expressed genes, and literature-based knowledge discovery. Storing, linking, and mining microarray databases using SRS. (Article) http://repub.eur.nl/res/pub/13873/ 2005-07-27T00:00:00Z BACKGROUND: SRS (Sequence Retrieval System) has proven to be a valuable platform for storing, linking, and querying biological databases. Due to the availability of a broad range of different scientific databases in SRS, it has become a useful platform to incorporate and mine microarray data to facilitate the analyses of biological questions and non-hypothesis driven quests. Here we report various solutions and tools for integrating and mining annotated expression data in SRS. RESULTS: We devised an Auto-Upload Tool by which microarray data can be automatically imported into SRS. The dataset can be linked to other databases and user access can be set. The linkage comprehensiveness of microarray platforms to other platforms and biological databases was examined in a network of scientific databases. The stored microarray data can also be made accessible to external programs for further processing. For example, we built an interface to a program called Venn Mapper, which collects its microarray data from SRS, processes the data by creating Venn diagrams, and saves the data for interpretation. CONCLUSION: SRS is a useful database system to store, link and query various scientific datasets, including microarray data. The user-friendly Auto-Upload Tool makes SRS accessible to biologists for linking and mining user-owned databases.