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          Institute: MPI für biologische Kybernetik     Collection: Biologische Kybernetik     Display Documents



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ID: 471950.0, MPI für biologische Kybernetik / Biologische Kybernetik
Data Mining for Biologists
Authors:Tsuda, K.
Editors:Li, X.; Ng, S.-K.
Place of Publication:Hershey, PA, USA
Publisher:Medical Information Science Reference
Date of Publication (YYYY-MM-DD):2009-05
Title of Book:Biological Data Mining in Protein Interaction Networks
Start Page:14
End Page:27
Physical Description:14
Review Status:not specified
Audience:Not Specified
Intended Educational Use:No
Abstract / Description:In this tutorial chapter, we review basics about frequent pattern mining algorithms, including itemset mining, association rule mining and graph mining. These algorithms can find frequently appearing substructures in discrete data. They can discover structural motifs, for example, from mutation data, protein structures and chemical compounds. As they have been primarily used for business data, biological applications are not so common yet, but their potential impact would be large. Recent advances in computers including multicore machines and ever increasing memory capacity support the application of such methods to larger datasets. We explain technical aspects of the algorithms, but do not go into details. Current biological applications are summarized and possible future directions are given.
External Publication Status:published
Document Type:InBook
Communicated by:Holger Fischer
Affiliations:MPI für biologische Kybernetik/Empirical Inference (Dept. Schölkopf)
Identifiers:URL:http://www.igi-pub.com/reference/details.asp?ID=33...
LOCALID:5368
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