Abstract
BackgroundInnovations in biological and biomedical imaging produce complex high-content and multivariate image data. For decision-making and generation of hypotheses, scientists need novel information technology tools that enable them to visually explore and analyze the data and to discuss and communicate results or findings with collaborating experts from various places.ResultsIn this paper, we present a novel Web2.0 approach, BioIMAX, for the collaborative exploration and analysis of multivariate image data by combining the webs collaboration and distribution architecture with the interface interactivity and computation power of desktop applications, recently called rich internet application.ConclusionsBioIMAX allows scientists to discuss and share data or results with collaborating experts and to visualize, annotate, and explore multivariate image data within one web-based platform from any location via a standard web browser requiring only a username and a password. BioIMAX can be accessed at http://ani.cebitec.uni-bielefeld.de/BioIMAX with the username "test" and the password "test1" for testing purposes.
Highlights
Innovations in biological and biomedical imaging produce complex high-content and multivariate image data
In contrast to the aforementioned solutions, we propose a free, fully web-based software approach, called BioIMAX (BioImage Mining, Analysis and eXploration), developed to augment both an easy initial exploratory access to a large variety of complex multivariate image data and a convenient collaboration of geographically distributed scientists via the web
With BioIMAX we have demonstrated the potential of Web2.0 technologies for the analysis of complex bioimage data
Summary
Innovations in biological and biomedical imaging produce complex high-content and multivariate image data. In the last two decades, innovative biological and biomedical imaging technologies greatly improved our understanding of structures of molecules, cells and tissue and increasingly have become high-throughput and highcontent applications. These new technologies produce a deluge of complex bioimage and meta data. Biologists and clinicians are faced with the difficult task of discovering and extracting knowledge based on the newly acquired data to generate hypotheses or diagnoses. They need software tools for data analysis, and this poses new challenges to the image computing community in consequence.
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