Abstract
Two-dimensional Electrophoresis Gel Images Scan (2dEGIS) implements a mix of computational methods for processing two-dimensional electrophoresis gel images. For advancing the analysis in case-control sample studies, a multi-component decomposition-approximation approach is presented, based on: (1) A global scan aimed to detect discriminative patterns with just a few components; (2) A more localized image scan through aggregated components; (3) The exploration of specific regions with maximal localization power. The tool 2dEGIS represents a novel unifying instrument for the computational analysis of gel images.
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