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Visualization and differentiation of proteins in tissue are problems of increasing interest in computational systems biology, bioinformatics, and image processing. A platform for generating such proteomic information is matrix-assisted laser desorption ionization mass spectrometry (MALDI-MS). In imaging MALDI-MS, spatial information and protein expression can be created. However, data from imaging MALDI-MS spectra require considerable signal processing to generate quantitative results and to provide input to later classification algorithms. To compare MALDI-MS spectra at different spatial locations (sample-to-sample comparisons) or classify parts of the spectra, a processing step called baseline correction is essential. This paper reports a robust algorithm for computing the baseline correction of MALDI-MS spectra. The algorithm requires few user inputs and is suitable for automatically processing a large number of spectra, as is the case when generating images. The results of our algorithm are validated on a dataset of spectra available for comparison purposes.

This article describes NetGraph, an object-oriented toolset for risk assessment applications. There are two significant aspects of NetGraph functionality. Firstly, NetGraph is a graphical knowledge acquisition tool for risk assessment, designed for robust structuring and efficient use of domain knowledge. A component library facility in NetGraph helps the domain expert to store and easily retrieve frequently encountered objects in complex systems. Time spent in designing fault trees is significantly reduced by the help of a cut/paste facility that allows the expert to easily define new fault trees by retrieving subtrees (components) of previously defined fault trees and putting them together. A second aspect of NetGraph is fault tree analysis. Fault trees designed in NetGraph can be used by either experts or operators to analyze fault behavior and probability of complex systems. A hypertext interface is also being developed to provide efficient communication of risks to individuals.