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Search: WFRF:(Pagnani A)

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  • Cvijovic, Marija, 1977, et al. (author)
  • Bridging the gaps in systems biology
  • 2014
  • In: Molecular Genetics and Genomics. - : Springer Science and Business Media LLC. - 1617-4615 .- 1617-4623. ; 289:5, s. 727-734
  • Journal article (peer-reviewed)abstract
    • Systems biology aims at creating mathematical models, i.e., computational reconstructions of biological systems and processes that will result in a new level of understanding-the elucidation of the basic and presumably conserved "design" and "engineering" principles of biomolecular systems. Thus, systems biology will move biology from a phenomenological to a predictive science. Mathematical modeling of biological networks and processes has already greatly improved our understanding of many cellular processes. However, given the massive amount of qualitative and quantitative data currently produced and number of burning questions in health care and biotechnology needed to be solved is still in its early phases. The field requires novel approaches for abstraction, for modeling bioprocesses that follow different biochemical and biophysical rules, and for combining different modules into larger models that still allow realistic simulation with the computational power available today. We have identified and discussed currently most prominent problems in systems biology: (1) how to bridge different scales of modeling abstraction, (2) how to bridge the gap between topological and mechanistic modeling, and (3) how to bridge the wet and dry laboratory gap. The future success of systems biology largely depends on bridging the recognized gaps.
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3.
  • Thurfjell, L., et al. (author)
  • Automatic Detection of Hypoperfused Areas in SPECT Brain Scans
  • 1998
  • In: IEEE Transactions on Nuclear Science. - : Institute of Electrical and Electronics Engineers (IEEE). - 0018-9499 .- 1558-1578. ; 45:4, s. 2149-2154
  • Journal article (peer-reviewed)abstract
    • Describes a method for automatic identification of areas with perfusion changes in SPECT brain images. An intersubject registration technique is used to stereotactically register images from a selected control group allowing for reference images to be created by averaging the subjects image data. An individual SPECT brain scan can be brought into registration with the reference image and comparison to the normal reference group can be made by subtracting the two volumes. Furthermore, since the variance in the reference group is known, a z-score image or an image coded in standard deviations, can be computed. The SPECT reference volume is defined in the same coordinate system as a brain atlas, and anatomical labeling of areas of interest is possible. The authors show results from the creation of an average image based on 11 individuals and from its comparison with pathological cases
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