Article

A new classification method using array Comparative Genome Hybridization data, based on the concept of Limited Jumping Emerging Patterns.

Faculty of Electronics and Information Technology of Warsaw University of Technology, Institute of Computer Science, Nowowiejska 15/19, Warsaw, 00-665, Poland.
BMC Bioinformatics (Impact Factor: 3.02). 02/2009; 10 Suppl 1:S64. DOI: 10.1186/1471-2105-10-S1-S64
Source: PubMed

ABSTRACT Classification using aCGH data is an important and insufficiently investigated problem in bioinformatics. In this paper we propose a new classification method of DNA copy number data based on the concept of limited Jumping Emerging Patterns. We present the comparison of our limJEPClassifier to SVM which is considered the most successful classifier in the case of high-throughput data.
Our results revealed that the classification performance using limJEPClassifier is significantly higher than other methods. Furthermore, we show that application of the limited JEP's can significantly improve classification, when strongly unbalanced data are given.
Nowadays, aCGH has become a very important tool, used in research of cancer or genomic disorders. Therefore, improving classification of aCGH data can have a great impact on many medical issues such as the process of diagnosis and finding disease-related genes. The performed experiment shows that the application of Jumping Emerging Patterns can be effective in the classification of high-dimensional data, including these from aCGH experiments.

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    ABSTRACT: In this paper, we propose a new classification algorithm based on Jumping Emerging Patterns (JEPs), that have the highest impact on classification accuracy. The core idea of our method is the application of a new ¿REAL/ALL¿ coefficient, which is used to compare the discriminating power among various groups of JEPs. The efficacy of the proposed approach was confirmed by tests performed on both synthetic and real data sets. The results show that our method may significantly improve the classification performance in comparison to other classifiers based on JEPs.
    Proceedings of the International Multiconference on Computer Science and Information Technology, IMCSIT 2009, Mragowo, Poland, 12-14 October 2009; 01/2009

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