A Framework for associated pattern mining over Microarray database

Nilamadhab Mishra

Abstract


Microarray database is a typical Relational database ,which contains a large number of columns and a small number of rows, and it poses a great challenge for existing associated pattern mining algorithms that discover patterns in item enumeration space.
Here I want to Review some algorithms which helps to explore the row enumeration space to mine associated patterns. The row enumeration algorithms are used to avoid searching the large number of columns /items enumeration space, but those algorithms can try to search the associated patterns in the row enumeration space. The column enumeration algorithms can not be scaled to microarray database, where as it is possible to scale the row enumeration algorithms to microarray database. So I can right to say that the associated patterns /rules can be the better search substitutes, which can minimize the search time and complexcity. So instead of searching the large number of columns in a microarray database (bioinformatics database), its associated framing patterns should be searched

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