Life science research aims at understanding the relationships in genomics, proteomics and metabolomics on all levels of biological self organization, dealing with data of increasing dimension and complexity. Bioimages represent a new data domain in this context, gaining growing attention since it closes important gaps left by the established molecular techniques. We present a new, web-based strategy that allows a new way of collaborative bioimage interpretaion through knowledge integration. We show, how this can be supported by combining data mining algorithms running on powerful compute servers and a next generation rich internet application (RIA) front-end offering database/project management and high-level tools for exploratory data analysis and annotation. We demonstrate our system BioIMAX using a bioimage dataset from High-Content Screening experiments to study bacterial infection in cell cultures.