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Biclustering Based on Monotone Galois Connnection

Student: Verezubova Viktoriya

Supervisor: Sergei Kuznetsov

Faculty: Faculty of Computer Science

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2017

The project is intended to study problems related to the biclustering. In the work some principles of biclusterization methods based on formal concept analysis and Galois conformities in particular are given. Algorithms Disclosed and BLOSOM are reviewed in the context of monotone Galois conformities. These methods are analyzed and compared in the context of CPU time using the real medical dataset. The received biclusters are visualized. The study can be used for further inquiry of biclustering methods and improving data mining. Furthermore, the results of the study are intended to be applied to the practical problems in bioinformatics, medicine and other fields.

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