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- Dina Elsayad, A. Khalifa, Mohammed Essam Khalifs, El-Saved El-Horbaty
- 2012 8th International Conference on Informatics…
- 2012

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)

- Amal Khalifa, Dina Elsayad, Ryan Charette, L. A. Rimm
- 2014

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)

- Dina Elsayad
- 2013

Microarrays technology allows us to measure the expression level of hundreds of thousands of genes simultaneously. The microarrays data analysis process involves various heavy computational tasks such as clustering. The clustering can be defined as partitioning a dataset into groups where objects in the same group are similar in somehow. CLUMP (clustering… (More)

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