Functional specifications of an integrated proteomics information management and analysis platform

Detecting proteins in human blood holds the promise of a revolution in cancer diagnosis. Also, the ability to perform laboratory operations on small scales using miniaturized (lab-on-a-chip) devices has many benefits. Designing and fabricating such systems is extremely challenging, but physicists and engineers are beginning to construct such highly integrated and compact labs on chips with exciting functionality. This paper focuses on the presentation of the requirements of the information technology layer in such an integrated platform been developed in the LOCCANDIA project. LOCCANDIA is a specific targeted research project (STREP) funded under the 6th framework program of the EC. Its ultimate objective is to develop an innovative nano- technology based (lab-on-a-chip) platform for the medical- proteomics field. The paper presents the main engineering aspects, challenges and architecture for creating an Integrated Clinico-Proteomic Environment. The environment will be used to monitor and document the analysis and discovery chain and to allow the physician to interpret the digital spectrogram data delivered by the mass spectrometer, for diagnostic purposes.

[1]  Alistair J. P. Brown,et al.  PEDRo: A database for storing, searching and disseminating experimental proteomics data , 2004, BMC Genomics.

[2]  Jean-Charles Sanchez,et al.  MSight: An image analysis software for liquid chromatography‐mass spectrometry , 2005, Proteomics.

[3]  R. Aebersold,et al.  Mass spectrometry-based proteomics , 2003, Nature.

[4]  M. Heller,et al.  Mass spectrometry‐based analytical tools for the molecular protein characterization of human plasma lipoproteins , 2005, Proteomics.

[5]  Rolf Apweiler,et al.  Advances in the development of common interchange standards for proteomic data , 2004, Proteomics.

[6]  R. Lequin Enzyme immunoassay (EIA)/enzyme-linked immunosorbent assay (ELISA). , 2005, Clinical chemistry.

[7]  Chris F. Taylor,et al.  A common open representation of mass spectrometry data and its application to proteomics research , 2004, Nature Biotechnology.

[8]  R. Vasan,et al.  Biomarkers of Cardiovascular Disease: Molecular Basis and Practical Considerations , 2006, Circulation.

[9]  M. Girolami,et al.  Clinical proteomics: A need to define the field and to begin to set adequate standards , 2007, Proteomics. Clinical applications.

[10]  Maciek Sasinowski,et al.  What is mzXML good for? , 2005, Expert review of proteomics.

[11]  M. Hilario,et al.  Processing and classification of protein mass spectra. , 2006, Mass spectrometry reviews.

[12]  Tomoko Umaki,et al.  Possible detection of pancreatic cancer by plasma protein profiling. , 2005, Cancer research.

[13]  Ron D Appel,et al.  Proteome informatics I: Bioinformatics tools for processing experimental data , 2006, Proteomics.

[14]  Fredrik Levander,et al.  Automated reporting from gel‐based proteomics experiments using the open source Proteios database application , 2007, Proteomics.