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https://hdl.handle.net/11147/4914
Title: | Mining frequent patterns from microarray data | Authors: | Yıldız, Barış Şelale, Hatice |
Keywords: | Data mining Microarray Frequent pattern mining Bioinformatics |
Publisher: | Institute of Electrical and Electronics Engineers Inc. | Source: | Yıldız, B., and Şelale, H. (2011, May 2-5). Mining frequent patterns from microarray data. Paper presented at the 6th International Symposium on Health Informatics and Bioinformatics. doi:10.1109/HIBIT.2011.6450819 | Abstract: | The rapid development of computers and increasing amount of collected data made data mining a popular analysis tool. Data mining research is interrelated to many fields and one of the most important ones is bioinformatics. Among many techniques, mining association rules or frequent patterns is one of the most studied techniques in computer science and it is applicable to bioinformatics. Association analysis of gene expressions may be used as decision support mechanism for finding genes that are in same pathway. In this work, publicly available yeast microarray data has been analyzed using an efficient frequent pattern mining algorithm Matrix Apriori and frequently co-over-expressed genes have been identified. © 2011 IEEE. | Description: | 6th International Symposium on Health Informatics and Bioinformatics, HIBIT 2011; Izmir; Turkey; 2 May 2011 through 5 May 2011 | URI: | http://doi.org/10.1109/HIBIT.2011.6450819 http://hdl.handle.net/11147/4914 |
ISBN: | 9781450775342 |
Appears in Collections: | Molecular Biology and Genetics / Moleküler Biyoloji ve Genetik Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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