Dina Elsayad

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Solving duster identification problem on large amount of data is known to be time consuming. Almost au the state of art clustering techniques focuses on sequential algorithms which suffer from me problem of long runtime. So, parallel algorithms are needed. One of the attempts is a parallel minimum spanning tree (MST)-based clustering technique, called(More)
Clustering is partitioning a set of observation into groups called clusters, where the observation in the same group has a common characteristic. One of the best known algorithms for solving the microarrays data clustering problem using minimum spanning tree (MST) is CLUMP algorithm (Clustering algorithm through MST in Parallel) which identifies a dense(More)
Clustering problem is one of the hottest research fields in microarrays data analysis. In Clustering, a set of observations are assigned into subsets (called clusters) such that observations in the same cluster are similar in some sense. One of the clustering approaches is based on the minimum spanning tree (MST). The MST-based clustering techniques consist(More)
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