1. Network P2P for exploring and visualization of proteomic data: possibility of handling data and analysing them under different perspectives
- Author
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Michele Maffia, Silvio Maglio, L.D. Serbanati, A. Massafra, I. De Mitri, Daniele Vergara, G. Mercurio, G. De Nunzio, A. Agrusti, Marco Favetta, G. Marsella, Rosella Cataldo, A. Vasilateanu, G., Mercurio, S., Maglio, A., Agrusti, DE NUNZIO, Giorgio, Cataldo, Rosella, DE MITRI, Ivan, M., Favetta, A., Massafra, Marsella, Giovanni, Vergara, Daniele, Maffia, Michele, A., Vasilateanu, L. D., Serbanati, and Favetta, Marco
- Subjects
Contextualization ,tumor ,Group method of data handling ,Computer science ,business.industry ,Computer Assisted Diagnosis ,Comparability ,computer.file_format ,Data science ,Visualization ,image processing ,Metadata ,2DGE ,Data visualization ,ebXML ,Medical Images ,Instrumentation (computer programming) ,business ,computer - Abstract
Our group has started a project aiming at the development of analysis algorithms devoted to images produced by two-dimensional electrophoresis (2-DE) for general applications in the field of proteomics. General analysis problems have been addressed, with the ultimate goal of the maximization of the "automation level" of the analysis procedure, without reducing the accuracy now reachable only with manual intervention. For this, the group is analyzing 2-DE images that are already stored or that will be produced by means of the instrumentation and the know-how of the biologists participating to the project. It's obvious that the "key" for the project success is primarily the availability of many images produced by different groups, but especially their "comparability", and their significant "clinical contextualization". For these reasons, the group has started the implementation of federation of heterogeneous bio banks of images founded on open Registry/Repository for P2P architecture (ebXML RR)[1], on images stored with standard metadata for their comparability (EFMI MIP) [2], and on standard electronic documents for their clinical contextualization (HL7 CDA) [3]. This paper summarizes the concepts of the initiative and describes possibility of handling data and analysing them under different perspectives.
- Published
- 2008