Please use this identifier to cite or link to this item:
https://scholarbank.nus.edu.sg/handle/10635/102691
DC Field | Value | |
---|---|---|
dc.title | A new clustering method for microarray data analysis. | |
dc.contributor.author | Zhang, L. | |
dc.contributor.author | Zhu, S. | |
dc.date.accessioned | 2014-10-28T02:28:35Z | |
dc.date.available | 2014-10-28T02:28:35Z | |
dc.date.issued | 2002 | |
dc.identifier.citation | Zhang, L.,Zhu, S. (2002). A new clustering method for microarray data analysis.. Proc IEEE Comput Soc Bioinform Conf 1 : 268-275. ScholarBank@NUS Repository. | |
dc.identifier.issn | 15553930 | |
dc.identifier.uri | http://scholarbank.nus.edu.sg/handle/10635/102691 | |
dc.description.abstract | A novel clustering approach is introduced to overcome data missing and inconsistency of gene expression levels under different conditions in the stage of clustering. It is based on the so-called smooth score, which is defined for measuring the deviation of the expression level of a gene and the average expression level of all the genes involved under a condition. We present an efficient greedy algorithm for finding clusters with smooth score below a threshold after studying its computational complexity. The algorithm was tested intensively on random matrixes and a yeast data. It was shown to perform well in finding co-regulation patterns in a test with the yeast data. | |
dc.source | Scopus | |
dc.type | Article | |
dc.contributor.department | MATHEMATICS | |
dc.description.sourcetitle | Proc IEEE Comput Soc Bioinform Conf | |
dc.description.volume | 1 | |
dc.description.page | 268-275 | |
dc.identifier.isiut | NOT_IN_WOS | |
Appears in Collections: | Staff Publications |
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