DDMaker perform local density analysis and generates pseudocolor maps of the spatial distribution of imaged cellular structures in 2D images, starting from either RGB color, grey level or binary images. DDMaker local density analysis permit to selectively denoise the signal, visualize and quantify its distribution and threshold the image basing on local density.
PocketAnalyzerPCA combines a geometric algorithm for detecting pockets in proteins with Principal Component Analysis and clustering. This enables visualization and analysis of pocket conformational distributions of large sets of protein structures.
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Our goal is to create an open source framework and toolset for modeling dynamic cellular network functions, and to develop a user community committed to using, extending and exploiting these tools to further our knowledge of biologic processes.