Piotr Pawliczek

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We propose here a parallel implementation of multidimensional scaling (MDS) method which can be used for visualization of large datasets of multidimensional data. Unlike in traditional approaches, which employ classical minimization methods for finding the global optimum of the “stress function”, we use a heuristic based on particle dynamics. This method(More)
Visual and interactive data exploration requires fast and reliable tools for embedding of an original data space in 3(2)-dimensional Euclidean space. Multidimensional scaling (MDS) is a good candidate. However, owing to at least O(M) memory and time complexity, MDS is computationally demanding for interactive visualization of data sets consisting of order(More)
The success of the clinical use of sequencing based tests (from single gene to genomes) depends on the accuracy and consistency of variant interpretation. Aiming to improve the interpretation process through practice guidelines, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) have published(More)
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